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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
d6bf7717-17a4-4dd6-8361-1ed75405df81 | quantifying-performance-of-bipedal-standing | 1711.07894 | null | http://arxiv.org/abs/1711.07894v1 | http://arxiv.org/pdf/1711.07894v1.pdf | Quantifying Performance of Bipedal Standing with Multi-channel EMG | Spinal cord stimulation has enabled humans with motor complete spinal cord
injury (SCI) to independently stand and recover some lost autonomic function.
Quantifying the quality of bipedal standing under spinal stimulation is
important for spinal rehabilitation therapies and for new strategies that seek
to combine spinal stimulation and rehabilitative robots (such as exoskeletons)
in real time feedback. To study the potential for automated electromyography
(EMG) analysis in SCI, we evaluated the standing quality of paralyzed patients
undergoing electrical spinal cord stimulation using both video and
multi-channel surface EMG recordings during spinal stimulation therapy
sessions. The quality of standing under different stimulation settings was
quantified manually by experienced clinicians. By correlating features of the
recorded EMG activity with the expert evaluations, we show that multi-channel
EMG recording can provide accurate, fast, and robust estimation for the quality
of bipedal standing in spinally stimulated SCI patients. Moreover, our analysis
shows that the total number of EMG channels needed to effectively predict
standing quality can be reduced while maintaining high estimation accuracy,
which provides more flexibility for rehabilitation robotic systems to
incorporate EMG recordings. | ['Kun Ho Kim', 'Joel W. Burdick', 'Yanan Sui'] | 2017-11-21 | null | null | null | null | ['electromyography-emg'] | ['medical'] | [ 5.37667096e-01 -1.80759765e-02 -6.51207089e-01 -1.18074015e-01
-8.65581870e-01 -5.82234740e-01 -1.18494779e-01 -7.60821640e-01
-8.50646257e-01 1.16712546e+00 5.30557930e-01 2.70554740e-02
-1.45178825e-01 -1.17357403e-01 -7.76160598e-01 -4.34248835e-01
-2.10318819e-01 5.18217385e-01 1.59650091e-02 -4.51556861e-01
3.66170168e-01 5.51157594e-01 -1.65106118e+00 3.81530583e-01
1.16917670e+00 7.92782366e-01 9.09092486e-01 5.24080217e-01
5.14044106e-01 3.60909164e-01 -7.55130172e-01 4.72882181e-01
2.24163741e-01 -6.28419995e-01 -6.24868691e-01 -6.94871545e-02
2.24039838e-01 -4.98152971e-01 -4.37000930e-01 8.73456597e-01
9.06482637e-01 -3.58496457e-02 5.31584501e-01 -9.74459767e-01
2.40976095e-01 5.28033078e-01 -5.99180534e-02 2.98109949e-01
5.90499759e-01 5.45012772e-01 2.64263302e-01 -1.97128043e-01
8.68228734e-01 6.40890539e-01 2.76288301e-01 9.14340675e-01
-1.34965241e+00 -7.45088756e-01 -6.62069917e-01 9.66639936e-01
-6.85771108e-01 -5.96324503e-01 3.01830441e-01 -4.79568124e-01
1.05259871e+00 4.02569950e-01 1.35542715e+00 1.30226958e+00
6.76486373e-01 7.25480855e-01 1.42735243e+00 -2.24179849e-01
2.00909317e-01 -5.43951213e-01 -5.37316576e-02 6.81860447e-02
2.60677457e-01 -1.14353737e-02 -7.39633799e-01 2.31451705e-01
6.74289465e-01 -9.16715637e-02 -9.20674384e-01 -1.74129486e-01
-1.58549976e+00 1.67341143e-01 3.71380001e-01 2.36616299e-01
-1.00139582e+00 3.84004772e-01 6.84218287e-01 4.67062473e-01
-3.06293309e-01 7.43518233e-01 -4.72254604e-01 -1.32412231e+00
-6.59448981e-01 9.52781178e-03 6.58753157e-01 6.21189237e-01
-8.80771056e-02 7.85090700e-02 -2.42314279e-01 1.03920364e+00
-5.44390023e-01 7.50731349e-01 8.26408982e-01 -1.70912302e+00
4.61475909e-01 5.59615195e-01 9.64264572e-03 -2.02145562e-01
-6.33988678e-01 -6.92866296e-02 -3.21370006e-01 6.67258978e-01
-3.27413827e-02 -5.37137508e-01 -7.93958545e-01 1.37775445e+00
-2.43245304e-01 -6.33163214e-01 -1.23097487e-01 1.39782095e+00
-2.03602210e-01 -1.91363826e-01 -1.28268495e-01 -4.01485264e-01
1.14070559e+00 -5.76665640e-01 -7.91732550e-01 -3.65701973e-01
5.86719453e-01 -5.05793914e-02 1.17892969e+00 7.05885231e-01
-9.59301233e-01 7.48391598e-02 -1.08464921e+00 4.66609985e-01
2.86145717e-01 9.49487314e-02 1.83719411e-01 3.17125887e-01
-7.02065408e-01 1.23234451e+00 -1.45337629e+00 -5.35081685e-01
1.81540921e-01 9.75811958e-01 -7.30781794e-01 1.90503702e-01
-1.08971047e+00 1.64613307e+00 1.42296106e-01 1.69729844e-01
-3.11165810e-01 -3.42614532e-01 -4.04508084e-01 -5.56407161e-02
8.95897821e-02 -9.49228048e-01 1.06963444e+00 -5.51961184e-01
-1.93239415e+00 7.00722277e-01 -5.59630953e-02 -1.80169284e-01
5.96735239e-01 -6.11357152e-01 -5.34380320e-03 7.35922933e-01
1.74931422e-01 2.51529753e-01 5.09613574e-01 -7.21623600e-01
2.57317498e-02 -9.16585147e-01 -6.91894531e-01 7.68547952e-01
-2.06095651e-01 7.24301487e-02 1.93869114e-01 -2.91465163e-01
1.24165758e-01 -1.23924148e+00 1.91412717e-02 -2.52283216e-02
-1.72472566e-01 3.40133816e-01 6.43750429e-01 -8.89701188e-01
5.60680449e-01 -1.94546723e+00 9.17737663e-01 1.45001635e-01
-2.20047191e-01 1.68650344e-01 3.06230843e-01 4.91570175e-01
4.28111441e-02 -3.54587585e-01 -2.43874997e-01 6.17642999e-01
-4.41422343e-01 6.89203024e-01 3.24250847e-01 4.83506858e-01
-3.75652790e-01 1.03441334e+00 -6.97679341e-01 -2.67835110e-01
3.98641765e-01 1.62277311e-01 -2.05137864e-01 1.26966894e-01
2.40722135e-01 7.27518737e-01 -9.61160753e-03 8.13043475e-01
-7.02010244e-02 2.38776013e-01 3.37244213e-01 -1.97486907e-01
1.29817843e-01 1.45063281e-01 -6.18402004e-01 2.01591325e+00
-1.36539474e-01 5.91685355e-01 7.46928751e-01 -1.03184366e+00
5.57676733e-01 6.94049656e-01 9.83005285e-01 -8.55114758e-01
4.30897444e-01 9.54762518e-01 3.57273996e-01 -1.06853986e+00
-6.64653182e-02 -5.85801065e-01 3.11553568e-01 2.32558072e-01
2.01280624e-01 -5.04323900e-01 1.06008910e-01 -3.09404433e-01
1.41645360e+00 5.90141058e-01 5.46508208e-02 -2.24885240e-01
-5.30739725e-02 3.09883893e-01 1.38668880e-01 3.68258566e-01
-3.38664889e-01 5.44135571e-01 2.25524291e-01 5.95847905e-01
-7.20601857e-01 -1.17968678e+00 -4.25996073e-02 7.06848919e-01
9.20937806e-02 2.63234705e-01 -8.54293883e-01 2.82613993e-01
5.09623170e-01 5.71468711e-01 -1.93025857e-01 -4.78166163e-01
-7.41357565e-01 -4.18703705e-01 3.52601856e-01 8.68757427e-01
-2.94729590e-01 -1.50018728e+00 -7.66348362e-01 4.84486341e-01
-6.89827561e-01 -9.56687331e-01 -4.90994640e-02 7.32995808e-01
-1.22848523e+00 -1.08308935e+00 -1.30204952e+00 -6.13643706e-01
2.56886721e-01 6.06143735e-02 -1.81639180e-01 -4.95465398e-01
-3.03829074e-01 3.49727482e-01 -5.07898629e-01 -1.27282843e-01
-2.09774315e-01 8.06263089e-03 7.16612279e-01 -7.53225923e-01
8.05472769e-03 -1.15028429e+00 -8.45631659e-01 4.92503107e-01
-2.87901193e-01 1.46998540e-01 1.15896165e+00 8.44117463e-01
5.83006978e-01 -9.93156374e-01 8.33005071e-01 -4.65122275e-02
1.12846816e+00 -2.40445748e-01 3.59846413e-01 -1.55821294e-01
-7.75171995e-01 -1.63328499e-01 5.63801944e-01 -4.08553660e-01
-7.42283702e-01 -4.25120071e-02 -1.38998657e-01 -3.42074990e-01
-1.73621241e-03 5.06998003e-01 2.30858758e-01 -2.21034735e-01
1.09982753e+00 5.19145131e-01 9.47483182e-01 -1.98706821e-01
5.69540635e-02 1.12962329e+00 1.31593680e+00 -5.46218276e-01
-1.83973566e-01 2.63878644e-01 9.26159620e-02 -7.00840414e-01
6.29407912e-03 -7.79667139e-01 -7.64623940e-01 -8.26668143e-01
7.16221988e-01 -5.73805869e-01 -1.17806852e+00 5.31544626e-01
-6.55895948e-01 -6.59598172e-01 -2.66127318e-01 1.28107369e+00
-1.52385163e+00 4.30068582e-01 -9.08736527e-01 -6.22140646e-01
-7.42698550e-01 -1.21768355e+00 1.06657827e+00 -4.25655581e-02
-8.60867977e-01 -8.42553079e-02 2.52642389e-02 7.74969280e-01
4.92627203e-01 5.12972236e-01 7.61570990e-01 4.73985635e-02
1.98488295e-01 -5.61922848e-01 2.55258262e-01 6.22825265e-01
3.37746918e-01 -8.02725434e-01 -3.73002321e-01 -3.26321006e-01
2.54339725e-01 -7.26590633e-01 2.69141525e-01 5.74571788e-01
9.39113677e-01 2.32476685e-02 -1.95938289e-01 3.26197833e-01
1.16169846e+00 1.45209953e-01 9.69713628e-01 5.70250332e-01
4.65919316e-01 7.19854414e-01 6.42879069e-01 -7.94040486e-02
-4.44614530e-01 7.92069137e-01 2.31542215e-01 3.45237553e-01
-1.66373417e-01 2.40492105e-01 5.81909895e-01 1.09116650e+00
-9.18069065e-01 2.89155096e-01 -6.52241647e-01 1.76572591e-01
-1.65639925e+00 -9.41802561e-01 -2.74037451e-01 2.02823853e+00
9.96643305e-01 3.30623500e-02 1.09538577e-01 5.05659699e-01
5.75523436e-01 -7.25031555e-01 -1.09266067e+00 -3.44603151e-01
7.82117546e-02 7.23495007e-01 9.63553131e-01 -6.94915876e-02
3.27891976e-01 4.00888473e-01 6.67195559e+00 4.02503520e-01
-1.42599416e+00 -8.61203969e-02 -8.02934051e-01 -6.40068710e-01
2.55787194e-01 -2.53052890e-01 1.92511469e-01 8.21164012e-01
1.02498043e+00 -4.29482371e-01 8.15611660e-01 6.61449492e-01
7.18485653e-01 -5.63473701e-01 -9.30276096e-01 5.90619206e-01
-1.66854069e-01 -1.15874135e+00 -5.42083025e-01 8.09583515e-02
3.44613135e-01 7.71259904e-01 -6.58668697e-01 -1.60148013e-02
-6.66923881e-01 -7.09659576e-01 5.89168549e-01 9.07955170e-01
1.27767861e+00 -3.12663376e-01 6.90488756e-01 6.78187132e-01
-5.01636863e-01 -3.13173562e-01 4.05180126e-01 -1.34158880e-01
7.49576330e-01 -1.51967943e-01 -5.63162267e-01 4.23980445e-01
4.22977716e-01 5.01653016e-01 7.99321458e-02 1.02580202e+00
-3.67300212e-01 3.06303769e-01 -4.98219341e-01 -4.26284015e-01
-4.12427515e-01 -2.11299226e-01 1.02189577e+00 4.86716717e-01
2.94562131e-01 9.47635919e-02 -3.84502262e-01 6.00602925e-01
2.84536719e-01 -1.34097517e-01 -4.38411295e-01 -2.22353294e-01
6.26077503e-02 7.95817733e-01 -3.25642556e-01 -1.90440118e-02
2.02153727e-01 1.31509471e+00 4.83416989e-02 4.08720434e-01
-1.41274199e-01 -6.07819140e-01 4.13320035e-01 4.29613560e-01
-4.90838617e-01 -6.37480557e-01 -7.29860783e-01 -1.06751990e+00
5.09791970e-01 -8.67615640e-01 -1.27258465e-01 -1.36404288e+00
-7.45039463e-01 -8.85988586e-03 -1.44748772e-02 -1.46939707e+00
-6.72024310e-01 -8.91079605e-01 -4.05912966e-01 9.13346767e-01
-5.62340915e-01 -2.06282273e-01 -3.65888327e-01 5.79987288e-01
4.03573126e-01 3.78871590e-01 1.03586817e+00 7.02472031e-02
-2.18803525e-01 -9.81584191e-02 2.84374177e-01 -4.79104817e-01
7.74571180e-01 -1.17548501e+00 -5.17662883e-01 3.22243840e-01
-9.13288653e-01 6.87150478e-01 9.50318456e-01 -9.04772758e-01
-1.85683858e+00 -9.84047055e-02 1.25645712e-01 -3.37652117e-03
5.81641614e-01 1.61837280e-01 -7.54243791e-01 1.94883898e-01
-1.43560424e-01 -5.93914449e-01 4.44963157e-01 -4.30318534e-01
7.62734294e-01 1.27056539e-01 -1.06990659e+00 6.86586320e-01
1.28506398e+00 -4.89206553e-01 -1.05983257e+00 4.31616038e-01
-6.76921308e-02 -3.60488623e-01 -1.19701433e+00 8.96420836e-01
1.45661354e+00 -2.67048806e-01 4.87737656e-01 -4.36588556e-01
4.88283575e-01 9.33935121e-02 -9.17349234e-02 -1.68297184e+00
2.51545519e-01 -3.90732437e-01 -2.22746268e-01 1.15830928e-01
1.06336482e-01 -5.22639334e-01 1.04422820e+00 5.07401168e-01
-4.90376472e-01 -1.08676863e+00 -1.22471356e+00 -1.25712287e+00
-6.42228872e-02 -1.13804288e-01 -3.99866492e-01 2.66390055e-01
1.40283751e+00 1.53734162e-01 -4.78304327e-01 -5.38496494e-01
3.21798503e-01 -2.52003931e-02 6.12226367e-01 -8.93959701e-01
-2.07052872e-01 -5.23080766e-01 -9.28740025e-01 -6.39909029e-01
8.29324052e-02 -1.17546153e+00 4.25959617e-01 -2.28366995e+00
8.27230662e-02 2.47138351e-01 -1.79095209e-01 3.73174042e-01
9.35184658e-02 3.63810398e-02 -8.37730095e-02 6.07746720e-01
2.90049255e-01 6.55357480e-01 1.81170547e+00 3.53676587e-01
-4.58587497e-01 2.40048125e-01 -3.35585713e-01 2.56060302e-01
7.97711551e-01 -6.16365612e-01 -4.81949374e-02 9.66467857e-02
-3.35768878e-01 7.54428864e-01 1.48956820e-01 -1.14661670e+00
2.70477414e-01 -2.26169452e-01 2.36610234e-01 -2.90067255e-01
5.19614100e-01 -7.51403570e-01 3.72510433e-01 1.04874861e+00
-2.52372772e-01 -5.59027195e-01 -1.69437796e-01 3.17288250e-01
-1.46416411e-01 -2.48553362e-02 5.38647115e-01 -8.41569677e-02
-4.00151342e-01 -2.49487236e-01 -1.06340051e+00 -3.07828993e-01
1.06086564e+00 -1.04273236e+00 -3.73639427e-02 -2.84438252e-01
-1.35310423e+00 4.07001555e-01 5.77098072e-01 4.58081901e-01
3.01076859e-01 -1.10769641e+00 -2.30735660e-01 -7.13217445e-03
1.24801777e-01 -5.09991288e-01 3.89419734e-01 1.71431112e+00
-6.98657930e-01 3.52149963e-01 -1.26647067e+00 -7.90541291e-01
-9.72579241e-01 -1.53214753e-01 3.08839798e-01 3.57411742e-01
-9.86025751e-01 1.11361578e-01 -7.79692352e-01 -6.14415258e-02
2.20987633e-01 -1.24961272e-01 -6.54498413e-02 -3.44117910e-01
-2.48852655e-01 7.52975821e-01 2.31225565e-01 -2.01750144e-01
-2.93131560e-01 2.36487672e-01 5.30936956e-01 -4.84211266e-01
1.42121434e+00 -2.35533178e-01 4.60581668e-02 6.73782110e-01
8.46151531e-01 -3.29059094e-01 -1.04428113e+00 5.33893585e-01
-2.27553844e-01 -2.60761410e-01 -2.08673358e-01 -1.34594965e+00
-5.89498520e-01 7.40219414e-01 6.98513031e-01 -3.28181773e-01
1.23827732e+00 -7.20404908e-02 1.03020990e+00 6.04993045e-01
1.06401753e+00 -1.57020676e+00 -2.37666756e-01 -2.45390654e-01
1.23622036e+00 -7.48785079e-01 -6.89760447e-02 -3.74488473e-01
-7.39396393e-01 1.22776437e+00 5.09365082e-01 -2.95764983e-01
2.72316933e-01 2.89131045e-01 5.95584922e-02 -2.47010842e-01
-2.23270506e-01 7.05704987e-02 2.09893927e-01 5.25168478e-01
1.55648023e-01 6.26447618e-01 -1.22848642e+00 5.69959044e-01
-3.95813346e-01 7.52661765e-01 7.23949075e-01 1.50368583e+00
-6.63848221e-01 -9.58444357e-01 -4.75019775e-02 1.34893882e+00
-3.96034122e-01 4.75862592e-01 -4.33182180e-01 7.39084482e-01
-3.29071611e-01 6.68763876e-01 -6.24706268e-01 -6.10734522e-01
1.06354558e+00 2.12615848e-01 1.04595494e+00 -7.78443396e-01
-5.21395922e-01 -1.14797853e-01 2.68101007e-01 -9.70650613e-01
-3.50689381e-01 -8.73656511e-01 -1.68547797e+00 2.07714289e-01
-4.06948179e-01 -9.53352675e-02 1.39448011e+00 1.02797270e+00
2.44792610e-01 6.21550262e-01 3.70122880e-01 -1.28985536e+00
-9.16916907e-01 -1.56905973e+00 -1.13477194e+00 3.49393129e-01
7.19440579e-02 -1.04962242e+00 -4.57718164e-01 -2.12971613e-01] | [6.879725456237793, 0.20546182990074158] |
9db5105d-2088-45a2-816a-72203b49a664 | a-deep-learning-framework-for-assessing | 1901.10435 | null | https://arxiv.org/abs/1901.10435v3 | https://arxiv.org/pdf/1901.10435v3.pdf | A Deep Learning Framework for Assessing Physical Rehabilitation Exercises | Computer-aided assessment of physical rehabilitation entails evaluation of patient performance in completing prescribed rehabilitation exercises, based on processing movement data captured with a sensory system. Despite the essential role of rehabilitation assessment toward improved patient outcomes and reduced healthcare costs, existing approaches lack versatility, robustness, and practical relevance. In this paper, we propose a deep learning-based framework for automated assessment of the quality of physical rehabilitation exercises. The main components of the framework are metrics for quantifying movement performance, scoring functions for mapping the performance metrics into numerical scores of movement quality, and deep neural network models for generating quality scores of input movements via supervised learning. The proposed performance metric is defined based on the log-likelihood of a Gaussian mixture model, and encodes low-dimensional data representation obtained with a deep autoencoder network. The proposed deep spatio-temporal neural network arranges data into temporal pyramids, and exploits the spatial characteristics of human movements by using sub-networks to process joint displacements of individual body parts. The presented framework is validated using a dataset of ten rehabilitation exercises. The significance of this work is that it is the first that implements deep neural networks for assessment of rehabilitation performance. | ['Y. Liao', 'M. Xian', 'A. Vakanski'] | 2019-01-29 | null | null | null | null | ['action-quality-assessment'] | ['computer-vision'] | [ 1.18653089e-01 -1.04878172e-01 -3.34917843e-01 -7.84340054e-02
-7.98560560e-01 5.96878119e-02 1.93790123e-02 8.64094123e-03
-8.30760300e-01 5.50389051e-01 8.79334331e-01 1.60026163e-01
-1.01413274e+00 -9.40168619e-01 -3.23368788e-01 -5.60918152e-01
-4.96860296e-01 5.48854053e-01 -4.72055152e-02 -2.99168944e-01
8.94523337e-02 6.15408778e-01 -1.69587326e+00 5.70957720e-01
5.36974549e-01 8.75196636e-01 1.57918483e-01 8.35545123e-01
3.85367066e-01 9.48335171e-01 -6.41368091e-01 3.03875953e-01
8.32823291e-03 -6.53219402e-01 -9.54741895e-01 2.01897342e-02
-2.63302743e-01 -5.18819630e-01 -6.11384928e-01 6.26433909e-01
9.36676264e-01 5.64254105e-01 1.03384852e+00 -9.27115977e-01
-8.14971447e-01 3.99700433e-01 2.77910054e-01 3.10717136e-01
3.89140964e-01 3.76841486e-01 7.05750525e-01 -4.32936996e-01
2.15458855e-01 8.65287602e-01 9.22004580e-01 5.82266033e-01
-1.05258501e+00 -4.91607226e-02 -6.44087493e-01 6.15796566e-01
-1.05747151e+00 -5.54546006e-02 6.11182094e-01 -8.43585074e-01
1.01107204e+00 2.80661464e-01 1.28163409e+00 8.02691877e-01
5.42921066e-01 9.44884360e-01 8.58703136e-01 -2.94636756e-01
4.60497856e-01 -7.52980590e-01 -8.90924856e-02 3.33665580e-01
-9.83433500e-02 3.34936768e-01 -4.49555606e-01 2.12350354e-01
9.79912996e-01 2.94549882e-01 -1.08905956e-01 -2.82809973e-01
-1.02919102e+00 5.50765812e-01 8.99419963e-01 7.18582034e-01
-1.11096954e+00 3.27671677e-01 3.31218660e-01 -6.87269727e-03
5.07577434e-02 4.31141369e-02 -3.96589786e-01 -5.63073099e-01
-1.06737375e+00 3.82608294e-01 1.89196870e-01 1.60410762e-01
1.09751306e-01 7.97214657e-02 -5.81946909e-01 7.13344336e-01
3.30083817e-01 2.86352217e-01 1.20235586e+00 -1.25146115e+00
8.44530538e-02 9.57620800e-01 -1.32271230e-01 -8.05327833e-01
-1.04446614e+00 -3.19341123e-01 -8.41005445e-01 8.65670025e-01
4.24391985e-01 -1.51081339e-01 -8.53798926e-01 1.48890924e+00
1.84445381e-01 -4.18875128e-01 1.38495088e-01 1.18171287e+00
6.51810884e-01 2.98125930e-02 3.49014670e-01 1.84446797e-01
1.29105687e+00 -6.64249957e-01 -8.23019564e-01 3.61207016e-02
6.61060274e-01 -2.17705101e-01 1.25006640e+00 3.16500753e-01
-1.20065725e+00 -8.52064073e-01 -8.85536194e-01 8.70643742e-03
-2.07351878e-01 6.51142657e-01 3.72660220e-01 4.33020949e-01
-1.09745312e+00 1.24155974e+00 -1.21948874e+00 -3.58931571e-01
3.88548762e-01 6.92150950e-01 -4.75168675e-01 4.45666492e-01
-1.01677370e+00 1.07380259e+00 4.23039347e-01 6.86728776e-01
-5.71821034e-01 -5.11003911e-01 -8.79091859e-01 1.29596945e-02
-4.56016839e-01 -9.44319904e-01 1.06924236e+00 -6.47220254e-01
-1.77581787e+00 5.98513365e-01 3.70395988e-01 -4.99490708e-01
5.00427365e-01 -7.11804092e-01 -3.00522238e-01 3.07685643e-01
-8.44017118e-02 3.70529115e-01 3.15332860e-01 -5.95430195e-01
-3.24709684e-01 -7.96517491e-01 -2.00480923e-01 4.57202196e-01
-5.48376858e-01 -2.42340222e-01 -9.61225629e-02 -5.41547656e-01
2.17876822e-01 -8.13771784e-01 -2.59659857e-01 7.02711642e-02
-1.81727841e-01 -1.02989785e-01 3.85011882e-01 -1.15632927e+00
1.33803046e+00 -1.86746502e+00 5.86877108e-01 2.00788498e-01
1.23180278e-01 2.25509539e-01 6.10063821e-02 4.69502419e-01
-1.82848588e-01 -4.28853214e-01 -3.33118647e-01 -3.85414474e-02
2.70861592e-02 3.58690321e-01 4.91140962e-01 5.01450360e-01
-1.17934167e-01 1.06140590e+00 -6.32663488e-01 -2.98888624e-01
7.32225478e-01 7.58511901e-01 -5.64265430e-01 2.04570860e-01
1.44145548e-01 5.15267313e-01 -2.66405314e-01 4.08938617e-01
-3.09362356e-02 6.96272627e-02 1.22932568e-01 -5.21345735e-01
1.46221414e-01 -3.06167528e-02 -1.06049502e+00 2.04564404e+00
-2.77867198e-01 5.98316729e-01 -2.01194927e-01 -1.07045770e+00
7.13742852e-01 3.98567468e-01 1.22431910e+00 -7.47032046e-01
6.44910872e-01 8.74380395e-02 1.90315526e-02 -1.14315999e+00
3.15905660e-01 -2.59751618e-01 -1.11543126e-01 4.73883182e-01
1.65968165e-01 2.11461335e-01 1.09067060e-01 -4.99559790e-01
1.43081951e+00 6.02455258e-01 2.98395216e-01 1.47105843e-01
3.58057290e-01 1.07622221e-01 1.83826745e-01 1.51042804e-01
-5.71073472e-01 5.82131505e-01 2.30577029e-02 -4.59709585e-01
-9.69159365e-01 -1.24841547e+00 2.88196981e-01 9.78036165e-01
-3.16831797e-01 9.13700555e-03 -9.66390193e-01 3.26239839e-02
1.55955583e-01 1.74964055e-01 -9.57465708e-01 -6.12407148e-01
-8.09286892e-01 -6.39985442e-01 6.85728014e-01 1.10490823e+00
3.46663773e-01 -1.79689860e+00 -1.11988306e+00 2.81023353e-01
-4.04331207e-01 -5.70079803e-01 3.19255213e-03 1.13672251e-02
-1.36498928e+00 -1.33711004e+00 -1.03243744e+00 -9.50935483e-01
2.30329290e-01 -4.24052984e-01 6.45078719e-01 -1.80400014e-01
-4.36029762e-01 6.00465655e-01 -2.67834038e-01 3.14959511e-02
-3.10285628e-01 -1.18121773e-01 1.96574181e-01 -3.46407056e-01
3.60836744e-01 -9.06460464e-01 -1.15919399e+00 2.47446224e-02
-9.08600211e-01 -2.25233853e-01 9.74642217e-01 6.88027978e-01
8.11471105e-01 6.42303228e-02 2.79630989e-01 1.64508238e-01
1.15850782e+00 -1.88132033e-01 3.57344061e-01 2.43800474e-04
-3.63575399e-01 5.14534786e-02 1.59192532e-01 -4.59565103e-01
-7.02500582e-01 5.25891446e-02 -6.31825387e-01 -2.90402710e-01
-4.19814557e-01 6.82924747e-01 1.34875029e-01 2.72296041e-01
1.01210701e+00 2.15282738e-01 4.15599883e-01 -6.33242786e-01
3.74044031e-01 5.94247222e-01 1.04314983e+00 -3.74300897e-01
1.55714035e-01 5.00224531e-01 1.80655703e-01 -5.66005707e-01
-3.24167252e-01 -5.84132373e-01 -9.63769972e-01 -9.66745198e-01
1.16191077e+00 -5.44774890e-01 -1.26216590e+00 6.44546509e-01
-7.29397297e-01 -7.61974514e-01 -8.59792769e-01 1.08564866e+00
-1.25879037e+00 3.13263476e-01 -9.27825928e-01 -7.95642972e-01
-7.08871424e-01 -9.56953883e-01 9.78070796e-01 1.24841206e-01
-6.19835675e-01 -8.83772314e-01 6.20356798e-01 4.47699845e-01
4.89234000e-01 7.53879964e-01 7.41880059e-01 -9.09556299e-02
1.65120974e-01 -6.45254016e-01 2.60736018e-01 6.47434115e-01
2.92321950e-01 -4.65898216e-01 -5.14289796e-01 -1.63715538e-02
-7.52964318e-02 -4.04993922e-01 4.46428746e-01 1.19932961e+00
1.01202142e+00 -1.27576932e-01 4.54346165e-02 3.03323299e-01
1.33889270e+00 2.99139805e-02 1.01661408e+00 5.70626080e-01
5.47383726e-01 7.46619761e-01 3.80232394e-01 4.23843920e-01
2.93339163e-01 6.82364643e-01 5.59111357e-01 -1.23243667e-01
-3.29409361e-01 8.98785293e-02 2.98027813e-01 8.45177770e-01
-8.43108237e-01 2.92102605e-01 -9.73135054e-01 5.91086447e-01
-1.93713880e+00 -1.32731581e+00 -1.29927933e-01 1.77412140e+00
5.51216841e-01 -3.17242555e-02 5.14996648e-01 7.88162649e-01
4.02857691e-01 -4.01675105e-01 -5.13815343e-01 -1.02654591e-01
2.13996530e-01 5.78027487e-01 2.92908102e-01 2.14200035e-01
-9.08724010e-01 4.22191352e-01 6.58839226e+00 4.48568881e-01
-7.56938696e-01 1.09205291e-01 -1.35222062e-01 -2.92278588e-01
3.15492362e-01 -6.81427240e-01 9.97239798e-02 1.75983101e-01
1.01891661e+00 6.03357852e-02 2.32040122e-01 7.34371364e-01
8.59511554e-01 -2.67775580e-02 -8.82387519e-01 6.70304537e-01
-6.57906607e-02 -1.04188704e+00 -3.19538713e-01 1.03426121e-01
1.61767498e-01 1.58121899e-01 1.80613607e-01 2.82880038e-01
1.62297025e-01 -1.07608342e+00 7.59425342e-01 1.21083176e+00
4.65444922e-01 -6.39092386e-01 7.99609244e-01 3.95140201e-01
-1.18589473e+00 -4.79967833e-01 6.05901144e-02 -4.08664972e-01
3.17155778e-01 5.15900925e-02 -3.65289390e-01 3.65624934e-01
8.48333001e-01 5.76927841e-01 -2.39928424e-01 1.15810525e+00
-3.79739106e-02 3.19404334e-01 -1.70334429e-01 -5.09977480e-03
9.33713615e-02 -1.35932103e-01 3.73569548e-01 9.90145206e-01
5.84888279e-01 -1.55783137e-02 -1.16944231e-01 5.28162599e-01
5.35671890e-01 2.22575754e-01 -5.02051651e-01 6.05088845e-02
-2.64756620e-01 7.82745123e-01 -5.09181321e-01 -1.89849902e-02
1.47790521e-01 1.05133927e+00 1.66941226e-01 3.48778725e-01
-4.52339172e-01 -2.33502984e-01 7.59370208e-01 2.85836518e-01
-1.45686239e-01 -3.15992266e-01 -6.22241378e-01 -5.03231704e-01
2.40081891e-01 -7.11311817e-01 5.89643478e-01 -9.59307373e-01
-9.87375259e-01 5.35956502e-01 -5.57115935e-02 -1.61364615e+00
-6.20386183e-01 -7.51812756e-01 -4.10193235e-01 9.40928936e-01
-6.00289226e-01 -9.04707432e-01 -5.01978457e-01 8.69693160e-01
4.06056434e-01 -2.21343916e-02 1.18445277e+00 4.88103569e-01
-3.57134312e-01 1.52366281e-01 1.35235563e-01 3.90249491e-01
1.48010746e-01 -1.13224375e+00 -2.80265927e-01 6.00834727e-01
-3.34115446e-01 5.37421763e-01 6.32399976e-01 -6.09690726e-01
-9.37207401e-01 -6.94172084e-01 5.35493135e-01 -3.53994250e-01
4.51688826e-01 5.89715600e-01 -6.44981146e-01 3.09662402e-01
-1.75263837e-01 -2.88592309e-01 1.07711864e+00 -1.85822159e-01
5.03300905e-01 1.09413654e-01 -1.15567732e+00 6.17453754e-01
1.10262156e+00 -5.91082036e-01 -8.86536002e-01 2.94470668e-01
1.37038797e-01 -3.99637014e-01 -1.43821633e+00 5.56565821e-01
1.07794559e+00 -9.62063909e-01 1.22019875e+00 -8.58489752e-01
8.08917761e-01 -2.30435908e-01 -1.86450899e-01 -1.21387076e+00
-5.60151041e-01 1.56808525e-01 -3.75823230e-01 3.47114354e-01
-4.77951542e-02 2.15348706e-01 1.24647737e+00 4.99582857e-01
-4.01420474e-01 -9.33479071e-01 -1.16485512e+00 -6.13815248e-01
6.26123846e-02 -8.83658707e-01 3.45495492e-01 3.75523299e-01
1.82658553e-01 -1.72437891e-01 -5.13657451e-01 -7.02164508e-03
5.63261509e-01 -2.41679221e-01 5.93595386e-01 -1.06392431e+00
-4.06634718e-01 -8.05436730e-01 -1.06826484e+00 -5.20936549e-01
-2.45360479e-01 -7.53900707e-01 1.83453783e-01 -2.45081496e+00
-1.97603986e-01 2.17589706e-01 -5.90882123e-01 5.00333786e-01
2.31383488e-01 4.11311090e-01 2.43725646e-02 2.38183782e-01
-1.00231074e-01 8.49488854e-01 1.41305697e+00 -1.42870769e-01
-7.08890557e-01 2.53202379e-01 -2.21351787e-01 7.72532105e-01
1.02558231e+00 -2.82327026e-01 -3.42896193e-01 -3.76426816e-01
-9.13671851e-02 2.80717939e-01 5.67513943e-01 -1.77914190e+00
1.41791508e-01 9.84295979e-02 6.67024374e-01 -7.82531202e-01
4.39332694e-01 -8.91014516e-01 4.80619043e-01 1.01183152e+00
-4.60229427e-01 3.62332687e-02 6.19523861e-02 4.52803552e-01
-3.23746711e-01 9.52952951e-02 5.00570416e-01 1.03280410e-01
-7.42780089e-01 1.72128931e-01 -7.55251467e-01 -3.53715181e-01
8.90201390e-01 -7.77610362e-01 3.74375254e-01 -1.74902916e-01
-1.68144250e+00 -1.41879544e-01 -8.86656642e-02 3.39266181e-01
8.48360300e-01 -1.86888659e+00 -4.43744004e-01 -7.07095712e-02
-2.87706722e-02 -4.14395392e-01 8.68462145e-01 1.05922115e+00
-7.43387580e-01 2.51639158e-01 -9.70535278e-01 -5.87900758e-01
-1.12690306e+00 1.42194390e-01 6.55016065e-01 -6.14167273e-01
-1.07025886e+00 3.02733243e-01 -5.57836473e-01 -5.37276566e-01
3.05768192e-01 -5.32717586e-01 -8.49294782e-01 -1.16253935e-01
4.27457213e-01 7.09928572e-01 8.81481469e-02 -8.51369381e-01
-2.48373479e-01 6.58914506e-01 7.87055314e-01 -4.27243412e-01
1.57011938e+00 -5.22122311e-04 2.00771362e-01 4.42601830e-01
1.07514060e+00 -6.66168451e-01 -1.20988882e+00 -1.19465366e-01
-8.76196921e-02 7.24810436e-02 1.38891652e-01 -7.36920655e-01
-1.09543967e+00 8.61563265e-01 1.32228827e+00 -1.74160033e-01
1.58555710e+00 -2.15482756e-01 9.61713076e-01 3.06201279e-01
1.70639783e-01 -1.27147651e+00 3.55721891e-01 1.68294773e-01
1.08913922e+00 -7.95178831e-01 -1.56911641e-01 4.35179830e-01
-5.37267148e-01 1.22974324e+00 2.96257079e-01 -3.34334582e-01
8.43191087e-01 6.14716671e-02 2.23307416e-01 -4.61342454e-01
7.31170699e-02 -4.94089484e-01 6.19627237e-01 8.42179656e-01
4.15337622e-01 4.06365186e-01 -6.35530412e-01 1.01197565e+00
-3.34982634e-01 7.07584500e-01 -6.98010847e-02 1.18133461e+00
-5.69106638e-01 -7.96988606e-01 -3.50936025e-01 4.68688399e-01
-3.51775825e-01 3.85557175e-01 3.66584025e-02 7.89745867e-01
2.85452902e-01 7.12133944e-01 -1.20702520e-01 -8.03380966e-01
9.19033587e-01 1.12827592e-01 6.81005239e-01 -2.89231986e-01
-7.94327676e-01 -1.54047117e-01 -1.77470937e-01 -7.55229771e-01
-7.39931703e-01 -5.83897293e-01 -1.44973028e+00 -1.96042717e-01
3.57484460e-01 -9.61236656e-02 7.58279860e-01 1.06998146e+00
8.02789256e-02 1.26734316e+00 -2.67623011e-02 -1.19761682e+00
-4.63043869e-01 -1.38247752e+00 -7.10849047e-01 6.64591074e-01
1.12036854e-01 -9.19891179e-01 8.33100602e-02 2.42723688e-01] | [7.10115909576416, 0.2620053291320801] |
06ff65b5-37b2-4f26-91f9-a38939f07547 | hierarchical-and-fast-graph-similarity | 2005.07115 | null | https://arxiv.org/abs/2005.07115v7 | https://arxiv.org/pdf/2005.07115v7.pdf | CoSimGNN: Towards Large-scale Graph Similarity Computation | The ability to compute similarity scores between graphs based on metrics such as Graph Edit Distance (GED) is important in many real-world applications. Computing exact GED values is typically an NP-hard problem and traditional algorithms usually achieve an unsatisfactory trade-off between accuracy and efficiency. Recently, Graph Neural Networks (GNNs) provide a data-driven solution for this task, which is more efficient while maintaining prediction accuracy in small graph (around 10 nodes per graph) similarity computation. Existing GNN-based methods, which either respectively embeds two graphs (lack of low-level cross-graph interactions) or deploy cross-graph interactions for whole graph pairs (redundant and time-consuming), are still not able to achieve competitive results when the number of nodes in graphs increases. In this paper, we focus on similarity computation for large-scale graphs and propose the "embedding-coarsening-matching" framework CoSimGNN, which first embeds and coarsens large graphs with adaptive pooling operation and then deploys fine-grained interactions on the coarsened graphs for final similarity scores. Furthermore, we create several synthetic datasets which provide new benchmarks for graph similarity computation. Detailed experiments on both synthetic and real-world datasets have been conducted and CoSimGNN achieves the best performance while the inference time is at most 1/3 of that of previous state-of-the-art. | ['Yueyang Wang', 'Haoyan Xu', 'Ziheng Duan', 'Jie Feng', 'Runjian Chen'] | 2020-05-14 | null | null | null | null | ['3d-human-action-recognition', 'graph-similarity'] | ['computer-vision', 'graphs'] | [-2.73726159e-03 2.95751635e-02 -1.87349785e-02 -2.76419014e-01
-4.49992359e-01 -4.61091936e-01 3.96187633e-01 8.75919938e-01
-4.22163278e-01 4.41554368e-01 -1.98729709e-01 -2.08239838e-01
-3.76923352e-01 -1.51728761e+00 -6.44113839e-01 -4.68751848e-01
-6.03682041e-01 5.97982645e-01 5.65969169e-01 -3.74742806e-01
2.39337921e-01 4.17889148e-01 -1.34917748e+00 -1.38824224e-01
1.06859088e+00 7.91045845e-01 9.66662541e-02 6.91910207e-01
-1.57906637e-01 2.87862241e-01 -3.88448060e-01 -8.53565872e-01
5.16853988e-01 -2.05268323e-01 -6.72422171e-01 -3.96121442e-01
5.91144800e-01 1.15006909e-01 -5.42908251e-01 1.50163066e+00
4.72496569e-01 2.28825971e-01 2.73992598e-01 -1.50704932e+00
-9.01008368e-01 9.00649071e-01 -5.42328119e-01 1.52566746e-01
4.01503384e-01 -6.24660440e-02 1.52751768e+00 -5.62496126e-01
5.19520938e-01 1.22786570e+00 9.25975025e-01 4.75772545e-02
-1.26213455e+00 -5.24764717e-01 1.01290964e-01 4.12171632e-01
-1.62554276e+00 2.09960237e-01 7.40755379e-01 -9.55478549e-02
1.11640298e+00 3.83793861e-01 7.58271098e-01 5.45579016e-01
2.68904448e-01 1.34286329e-01 6.75442457e-01 -1.76723793e-01
1.32778719e-01 -3.77900481e-01 2.06909090e-01 9.89971936e-01
6.26093924e-01 -8.82664919e-02 -1.29858732e-01 -1.79836467e-01
7.29107976e-01 3.07869315e-01 -2.55822808e-01 -4.41735715e-01
-1.44595766e+00 9.47152078e-01 1.21575141e+00 5.47888160e-01
-2.62337208e-01 3.88337106e-01 6.13352954e-01 8.11218679e-01
4.37253892e-01 6.32827759e-01 -8.25957954e-02 1.40918627e-01
-8.19499314e-01 1.78866655e-01 9.50059414e-01 9.43282962e-01
9.64569628e-01 -4.26803470e-01 -4.85340729e-02 7.32753515e-01
-1.55712321e-01 2.61272825e-02 4.70188856e-01 -4.43793893e-01
6.30490899e-01 1.20555878e+00 -5.15317559e-01 -1.82212687e+00
-2.77564555e-01 -3.50609422e-01 -1.39284194e+00 -2.02506945e-01
3.20973933e-01 2.83152103e-01 -8.56096983e-01 1.61568391e+00
3.80262583e-01 4.44330156e-01 -2.98199028e-01 6.86962724e-01
1.00950658e+00 5.14947176e-01 -2.55155206e-01 1.07267052e-01
1.04668009e+00 -1.24503207e+00 -3.09775203e-01 -2.58460548e-02
8.62112880e-01 -4.35569972e-01 1.20904005e+00 -9.65476856e-02
-1.12754762e+00 -4.95361000e-01 -1.20043600e+00 -1.24358207e-01
-7.88537920e-01 -4.00382787e-01 7.53750086e-01 4.42091644e-01
-1.48510802e+00 1.16626263e+00 -7.57446349e-01 -5.68332970e-01
1.80607527e-01 5.65235972e-01 -7.41138875e-01 -2.65993714e-01
-1.18870330e+00 6.54371858e-01 5.83378911e-01 6.29640520e-02
-4.17595625e-01 -6.75282419e-01 -1.05865848e+00 3.52365732e-01
5.66682637e-01 -6.43943191e-01 4.48462039e-01 -6.06463075e-01
-1.00025129e+00 7.56699800e-01 3.65522712e-01 -4.37024534e-01
2.00201035e-01 4.75265771e-01 -4.76345927e-01 3.70832309e-02
3.95809449e-02 5.37025452e-01 4.34882700e-01 -5.04134178e-01
-3.17221016e-01 -4.16298360e-01 3.96825254e-01 1.03984490e-01
-6.61142707e-01 -2.42897552e-02 -6.36496902e-01 -6.95313394e-01
2.65645951e-01 -9.98226941e-01 -3.14527571e-01 9.78852659e-02
-4.80914295e-01 -4.56417471e-01 5.49715757e-01 -5.12245715e-01
1.48856926e+00 -1.85927498e+00 3.20915341e-01 4.72182125e-01
8.49562526e-01 3.75822663e-01 -4.87050354e-01 7.53422737e-01
-1.65751025e-01 1.68149188e-01 -2.35502958e-01 -1.75257504e-01
1.79025352e-01 2.58146942e-01 3.17219913e-01 3.74700010e-01
9.78032351e-02 1.16747725e+00 -9.51528609e-01 -5.47955394e-01
7.35037550e-02 2.49151170e-01 -6.51629090e-01 2.70981997e-01
9.26779732e-02 -2.69708842e-01 -1.53405085e-01 5.85654676e-01
7.35792756e-01 -7.13004768e-01 4.38260227e-01 -3.96553755e-01
2.71260679e-01 7.75425360e-02 -1.32833660e+00 1.74339843e+00
-3.65256667e-01 3.05345744e-01 -1.23316139e-01 -1.20529234e+00
1.08445477e+00 -2.69137144e-01 2.17512906e-01 -4.99783218e-01
1.16980404e-01 2.07580999e-01 2.21733734e-01 -6.17229342e-02
4.42660868e-01 3.04425538e-01 -2.17028499e-01 3.16764861e-01
-1.09280308e-03 -1.77102368e-02 6.59878194e-01 5.50522864e-01
1.87159729e+00 -4.90539014e-01 3.56981874e-01 -3.39631945e-01
6.44170582e-01 -3.69155049e-01 3.96225691e-01 5.74964583e-01
-1.09393857e-01 5.12349784e-01 7.65302300e-01 -6.09180093e-01
-9.20844495e-01 -1.09977734e+00 4.87288326e-01 9.71695244e-01
4.82709289e-01 -9.04684842e-01 -8.30513954e-01 -8.35514665e-01
2.24564031e-01 8.17314982e-02 -6.40699387e-01 -3.58215928e-01
-4.95824665e-01 -7.06246376e-01 5.01177013e-01 5.50391078e-01
5.29379606e-01 -9.15004313e-01 1.51238307e-01 2.04705462e-01
5.98052219e-02 -1.19511318e+00 -7.62147784e-01 -1.31679535e-01
-7.48603761e-01 -1.21214139e+00 -3.83942097e-01 -9.17197526e-01
9.71206427e-01 3.93548965e-01 1.32970214e+00 7.24128842e-01
-3.32604349e-01 -1.36807576e-01 -3.68023247e-01 2.13145182e-01
-2.12421283e-01 3.67028147e-01 -1.68618500e-01 -1.20698959e-01
2.19404534e-01 -1.04329586e+00 -4.68588680e-01 3.36900562e-01
-8.71660709e-01 -2.38336939e-02 6.74333394e-01 9.37097371e-01
5.02222419e-01 2.23278835e-01 4.78278905e-01 -8.40921342e-01
9.65179443e-01 -3.24179918e-01 -7.82905757e-01 4.29532081e-01
-8.62896621e-01 2.08690420e-01 9.52842414e-01 -3.01518202e-01
-1.71163455e-01 -3.46478701e-01 -1.58880539e-02 -4.80684012e-01
2.92177439e-01 7.33764291e-01 -8.39108676e-02 -6.38844848e-01
4.25616115e-01 -6.11994117e-02 8.74311179e-02 -3.13299894e-01
2.90884465e-01 1.95203781e-01 4.28840160e-01 -3.68519634e-01
9.75008070e-01 9.38710794e-02 2.82446265e-01 -2.80137658e-01
-3.57030958e-01 -3.87676686e-01 -6.63836479e-01 4.61615771e-02
5.46748102e-01 -5.67720592e-01 -8.80437672e-01 3.81716579e-01
-1.00115144e+00 -1.12057619e-01 -4.91842739e-02 3.82794470e-01
-1.66292056e-01 7.63833880e-01 -8.28925848e-01 -7.61385486e-02
-6.19775832e-01 -1.14966691e+00 9.26299810e-01 6.32121637e-02
1.75691620e-02 -1.18882179e+00 1.62556455e-01 4.82549705e-02
5.36361575e-01 5.71794987e-01 1.18961072e+00 -8.32372069e-01
-7.44356453e-01 -4.62858647e-01 -7.77833402e-01 1.32789150e-01
1.52031541e-01 -8.26349631e-02 -1.95614263e-01 -6.42171383e-01
-7.77564704e-01 -1.14569254e-01 7.18122900e-01 -2.13383255e-03
1.27815437e+00 -2.44150162e-01 -4.48187351e-01 6.33063495e-01
1.68689406e+00 -3.95078599e-01 5.54042578e-01 9.06884223e-02
1.03852379e+00 4.16401118e-01 4.87290740e-01 1.31270945e-01
6.24765992e-01 6.46768272e-01 6.16916180e-01 -9.90492925e-02
-1.48742452e-01 -2.99792588e-01 8.71326849e-02 1.37140214e+00
-2.13058427e-01 -5.16186416e-01 -7.65999556e-01 5.43676734e-01
-2.03042340e+00 -6.66079044e-01 -1.96940795e-01 2.27126074e+00
5.44671535e-01 2.45375335e-01 9.13557857e-02 1.92177579e-01
1.14621997e+00 3.09065968e-01 -2.81230599e-01 -4.58908737e-01
2.07504511e-01 4.27260816e-01 5.26740789e-01 3.82858157e-01
-8.76083076e-01 9.24921393e-01 5.37812328e+00 9.64424014e-01
-9.41259205e-01 3.93456854e-02 3.18097144e-01 6.68846071e-02
-2.81949192e-01 3.74277495e-02 -3.93572748e-01 5.80393553e-01
7.82964826e-01 -3.60267967e-01 7.63532460e-01 6.84657931e-01
-3.91848624e-01 2.30787873e-01 -1.22367001e+00 1.10014307e+00
5.14647029e-02 -1.43379653e+00 5.88185452e-02 -2.97944881e-02
6.62391424e-01 1.94062427e-01 -3.41683745e-01 3.45946938e-01
4.98826832e-01 -1.02375615e+00 -2.39940137e-02 3.66780311e-01
7.27359593e-01 -8.83736789e-01 1.01378202e+00 7.56861567e-02
-1.82447207e+00 5.73349819e-02 -6.37264371e-01 -1.22197252e-02
4.88451347e-02 8.65110755e-01 -7.63835549e-01 9.68102813e-01
8.27677786e-01 7.93188632e-01 -8.25549304e-01 1.03299212e+00
-5.25216274e-02 8.21308419e-02 -4.03379917e-01 -3.36483538e-01
3.72286379e-01 -4.74657774e-01 4.54351157e-01 9.21744883e-01
5.50585926e-01 -2.26293012e-01 3.66152406e-01 8.92813385e-01
-4.75846857e-01 2.00074837e-01 -6.40073895e-01 -3.18357170e-01
6.21811450e-01 1.51861894e+00 -9.35737848e-01 -3.31315666e-01
-4.12004143e-01 1.10104692e+00 9.16063368e-01 -8.88494253e-02
-9.50058877e-01 -1.04084301e+00 6.86164200e-01 1.75428718e-01
2.97777951e-01 -3.58645588e-01 2.54548877e-01 -9.80024278e-01
3.30520838e-01 -6.92441463e-01 6.67879641e-01 -4.25992191e-01
-1.50481236e+00 8.34137380e-01 -2.09348351e-01 -8.58987093e-01
6.84363162e-03 -5.96504271e-01 -8.62003088e-01 6.05605960e-01
-1.20303285e+00 -1.21556246e+00 -8.20563078e-01 6.09763145e-01
-2.61040851e-02 5.06555177e-02 8.02001655e-01 6.35441601e-01
-5.14358521e-01 9.87762988e-01 5.36556058e-02 2.05261171e-01
5.67917287e-01 -1.39067554e+00 9.78363574e-01 7.85460532e-01
1.77642688e-01 5.57513893e-01 4.12702560e-01 -7.11751997e-01
-1.65157866e+00 -1.30132699e+00 9.54765201e-01 -8.91277194e-02
8.21579278e-01 -5.98489821e-01 -1.02016592e+00 5.33794761e-01
-3.05112973e-02 7.24102318e-01 3.08317721e-01 1.65077284e-01
-4.20571893e-01 -4.04925615e-01 -1.27581477e+00 6.55928969e-01
1.64623761e+00 -4.67924714e-01 -1.86410978e-01 2.82140255e-01
1.09865463e+00 -3.00863683e-01 -1.38010967e+00 5.41089714e-01
3.49412054e-01 -1.07110274e+00 1.05993211e+00 -5.71566045e-01
1.26803458e-01 -3.23660314e-01 -1.35046169e-01 -1.56620860e+00
-5.33886611e-01 -5.75726986e-01 3.25310379e-02 1.08748579e+00
2.66119778e-01 -9.18310523e-01 9.18131590e-01 2.78336495e-01
1.34831164e-02 -1.01396132e+00 -6.38761640e-01 -9.86731589e-01
-3.81339967e-01 -2.21787742e-03 1.09293258e+00 1.16823137e+00
5.26706167e-02 2.26191193e-01 -1.09788347e-02 2.17248350e-01
6.82588279e-01 3.27418983e-01 9.40217376e-01 -1.38996994e+00
-1.72337949e-01 -5.89690685e-01 -1.24547696e+00 -5.30777752e-01
1.43982276e-01 -1.33284485e+00 -3.34641039e-01 -1.65756369e+00
1.84474260e-01 -3.65923136e-01 -3.33805889e-01 4.50235218e-01
-2.51558721e-01 2.92675495e-01 1.13865919e-01 -2.41141155e-01
-8.12527239e-01 4.69914466e-01 1.09573686e+00 -2.72481352e-01
-5.35877794e-02 -3.11693251e-01 -4.70765144e-01 3.95717025e-01
6.30101204e-01 -4.50159401e-01 -4.38205719e-01 -2.84346074e-01
4.16615009e-01 -1.61316693e-01 3.73462707e-01 -1.08440804e+00
5.36620677e-01 6.32150173e-02 -1.20485485e-01 -3.56902063e-01
4.70431671e-02 -6.51193142e-01 3.46784711e-01 5.43617129e-01
-1.59690544e-01 6.31165981e-01 -1.34122923e-01 7.24755287e-01
-4.18087333e-01 3.51980962e-02 7.06173241e-01 -8.83051306e-02
-6.02996707e-01 8.63794088e-01 3.89043212e-01 5.46162501e-02
1.06864321e+00 -3.34749699e-01 -4.48183209e-01 -2.49939352e-01
-5.73243976e-01 2.20976889e-01 5.83374083e-01 4.11048561e-01
5.79526246e-01 -1.63279092e+00 -6.36762321e-01 1.06710054e-01
2.50125438e-01 -2.08490565e-02 1.69575617e-01 8.66463602e-01
-6.66381836e-01 6.96547404e-02 -3.05964738e-01 -3.73321980e-01
-1.52284682e+00 7.10708559e-01 2.30815396e-01 -8.39302778e-01
-5.22839367e-01 9.18393493e-01 1.91008598e-02 -9.02700126e-01
6.97280169e-02 -3.94712776e-01 1.70206517e-01 -2.09061950e-01
2.14773729e-01 6.55662835e-01 3.21063668e-01 -3.31190050e-01
-2.51042843e-01 6.38450921e-01 -2.09548354e-01 6.35594428e-01
1.41219568e+00 6.66765422e-02 -6.73016608e-01 -1.06254809e-01
1.54425442e+00 -2.42507577e-01 -5.04763663e-01 -4.11139458e-01
1.59591157e-02 -6.72653437e-01 -9.66800451e-02 -2.58331209e-01
-1.32505739e+00 7.96856463e-01 3.80843401e-01 6.22957408e-01
1.12682772e+00 -4.50399518e-02 1.13134193e+00 5.64271927e-01
3.76441717e-01 -1.01676404e+00 2.62108177e-01 2.87237942e-01
8.61197352e-01 -1.20281494e+00 8.28717500e-02 -7.25139320e-01
-1.14266589e-01 1.03171825e+00 8.68661821e-01 -5.19524276e-01
6.91406548e-01 7.65310228e-02 -7.00065851e-01 -4.76959020e-01
-5.99922717e-01 -9.19507071e-02 4.74435955e-01 3.86069000e-01
1.81222945e-01 3.09124768e-01 -4.76027191e-01 4.13995206e-01
-2.33309358e-01 -4.08536255e-01 2.13129327e-01 5.91859102e-01
-2.70297527e-01 -1.27167451e+00 1.86034396e-01 8.41823995e-01
-5.66002242e-02 -2.67422050e-01 -6.01838708e-01 8.99604142e-01
-9.33757499e-02 4.58474666e-01 8.58032405e-02 -7.16401756e-01
3.59095782e-01 -5.55553734e-01 4.50834394e-01 -4.78137493e-01
-7.53764212e-01 -6.07666969e-01 1.21484227e-01 -9.80432987e-01
-1.13312930e-01 -1.51511878e-01 -1.27324700e+00 -9.59355354e-01
-5.17437279e-01 9.77294594e-02 3.58522028e-01 5.75880527e-01
6.77626491e-01 4.40376669e-01 5.92913687e-01 -7.02381134e-01
-5.24881899e-01 -8.76161575e-01 -7.13158429e-01 5.80767632e-01
-1.40128389e-01 -5.72288752e-01 -4.57014859e-01 -6.88707471e-01] | [7.123830318450928, 6.193305492401123] |
10723ebe-387b-43ae-a0b1-3c50b030a6cb | bronchusnet-region-and-structure-prior | 2205.06947 | null | https://arxiv.org/abs/2205.06947v2 | https://arxiv.org/pdf/2205.06947v2.pdf | BronchusNet: Region and Structure Prior Embedded Representation Learning for Bronchus Segmentation and Classification | CT-based bronchial tree analysis plays an important role in the computer-aided diagnosis for respiratory diseases, as it could provide structured information for clinicians. The basis of airway analysis is bronchial tree reconstruction, which consists of bronchus segmentation and classification. However, there remains a challenge for accurate bronchial analysis due to the individual variations and the severe class imbalance. In this paper, we propose a region and structure prior embedded framework named BronchusNet to achieve accurate segmentation and classification of bronchial regions in CT images. For bronchus segmentation, we propose an adaptive hard region-aware UNet that incorporates multi-level prior guidance of hard pixel-wise samples in the general Unet segmentation network to achieve better hierarchical feature learning. For the classification of bronchial branches, we propose a hybrid point-voxel graph learning module to fully exploit bronchial structure priors and to support simultaneous feature interactions across different branches. To facilitate the study of bronchial analysis, we contribute~\textbf{BRSC}: an open-access benchmark of \textbf{BR}onchus imaging analysis with high-quality pixel-wise \textbf{S}egmentation masks and the \textbf{C}lass of bronchial segments. Experimental results on BRSC show that our proposed method not only achieves the state-of-the-art performance for binary segmentation of bronchial region but also exceeds the best existing method on bronchial branches classification by 6.9\%. | ['Hong Shen', 'Guanbin Li', 'Haofeng Li', 'Yu Wang', 'huan zhang', 'Haifan Gong', 'Wenhao Huang'] | 2022-05-14 | null | null | null | null | ['unet-segmentation'] | ['computer-vision'] | [ 4.39202487e-01 3.13951880e-01 -4.25327390e-01 -2.93981284e-01
-9.62325752e-01 -3.25417310e-01 -2.76590395e-03 8.71030465e-02
2.88684014e-02 2.75284946e-01 -2.43333325e-01 -4.95547116e-01
-3.25379848e-01 -7.86492944e-01 -3.91310662e-01 -1.01032925e+00
2.67415285e-01 8.58539164e-01 8.00730765e-01 1.58416435e-01
-1.96059555e-01 8.61922443e-01 -1.15190256e+00 5.46307743e-01
8.60038817e-01 1.25287712e+00 4.41658199e-01 8.39575410e-01
-4.67727244e-01 4.57129627e-01 -2.37326130e-01 -1.98119134e-01
3.08444798e-01 -6.09571755e-01 -7.65504837e-01 3.17748129e-01
4.97602671e-01 -3.07599511e-02 -1.10176578e-02 8.65981281e-01
4.36887026e-01 -1.41783789e-01 9.69226003e-01 -7.61360288e-01
2.16683134e-01 4.16366577e-01 -7.70146966e-01 4.80329871e-01
-4.12495106e-01 5.12010574e-01 1.03199947e+00 -5.48210979e-01
3.62287670e-01 1.03470874e+00 6.03617072e-01 5.98712921e-01
-1.06293130e+00 -6.72599614e-01 2.47742087e-02 5.45832813e-02
-1.05217099e+00 9.05836672e-02 6.64078712e-01 -5.09309173e-01
5.91939569e-01 6.52534127e-01 7.78374970e-01 5.97397625e-01
2.39177778e-01 6.93700552e-01 1.25270057e+00 -7.12833926e-02
-9.58826020e-02 -4.97408584e-02 3.57468188e-01 1.11602187e+00
2.66400248e-01 -5.36406003e-02 1.52398288e-01 -1.49119616e-01
9.80575025e-01 1.43969074e-01 -4.12372470e-01 -2.86797971e-01
-1.10256553e+00 7.05115139e-01 1.03022647e+00 2.84273446e-01
-3.57609093e-01 2.75404453e-01 1.83686286e-01 -3.11851621e-01
2.63786793e-01 1.64962467e-02 -2.48325214e-01 3.53987634e-01
-8.07186842e-01 -1.38851389e-01 6.76591992e-01 6.79101288e-01
6.09711945e-01 -1.34508520e-01 -5.45011282e-01 1.03080142e+00
6.53940380e-01 4.90637869e-01 4.90172446e-01 -8.23471308e-01
5.23699999e-01 8.21367145e-01 -6.34803832e-01 -4.40863699e-01
-4.81392860e-01 -6.16693377e-01 -1.22845817e+00 1.04377881e-01
4.24905598e-01 2.47166663e-01 -1.41106045e+00 9.17442262e-01
9.98948514e-01 2.66694754e-01 -4.86162841e-01 7.74627149e-01
1.26425087e+00 2.70426303e-01 6.20476529e-02 -2.06471086e-01
1.49175704e+00 -1.16207278e+00 -3.96588981e-01 9.97054949e-02
8.15515757e-01 -5.91385782e-01 9.13144171e-01 3.53448808e-01
-1.02685928e+00 -4.94519055e-01 -6.73982441e-01 -1.34450318e-02
1.33362085e-01 -1.19536862e-01 2.84879357e-01 6.90401375e-01
-7.68912375e-01 3.99577618e-01 -9.58280146e-01 5.13876937e-02
1.00000453e+00 5.78267932e-01 2.38426719e-02 -1.18599692e-02
-5.59029877e-01 2.86305368e-01 2.33471826e-01 5.24509959e-02
-8.80903006e-01 -7.43879616e-01 -6.30542815e-01 -4.68788296e-02
6.83858931e-01 -1.22002721e+00 1.27769756e+00 -2.15839148e-01
-1.21563828e+00 1.03352022e+00 -2.84417927e-01 -3.02949905e-01
4.81816858e-01 3.49982291e-01 4.78543043e-02 6.35215640e-01
9.34400335e-02 6.55820847e-01 1.07618344e+00 -1.36265421e+00
-9.25132930e-01 -6.86919928e-01 -3.75385165e-01 1.47792339e-01
-4.20943163e-02 -4.73053098e-01 -7.16383100e-01 -7.22594380e-01
3.61568242e-01 -8.66519928e-01 -6.17148876e-01 2.41165295e-01
-5.41469812e-01 -5.16628683e-01 9.20003057e-01 -6.63301289e-01
1.40195084e+00 -1.95868683e+00 8.98532569e-02 5.70418537e-01
7.62893975e-01 2.60871947e-01 3.08540612e-01 -3.06904227e-01
-2.02802345e-02 4.68818933e-01 -6.66128397e-01 -2.10468799e-01
-3.16116035e-01 5.24943709e-01 1.92180946e-01 4.00184751e-01
-5.81767820e-02 1.09172535e+00 -4.94780749e-01 -1.22259712e+00
4.88209754e-01 3.15246046e-01 -6.56762838e-01 2.91256458e-01
-4.82725561e-01 8.74999762e-01 -9.39078927e-01 7.44093895e-01
4.90514904e-01 -6.00580156e-01 -3.77550162e-02 -2.05834150e-01
1.79409191e-01 1.28321856e-01 -8.62290204e-01 1.32252491e+00
-4.53979969e-01 -1.60305932e-01 7.81819344e-01 -8.26514363e-01
5.55636644e-01 4.85486537e-01 9.29840744e-01 -1.70855835e-01
3.53753269e-01 3.53565425e-01 2.93473899e-01 -7.85037458e-01
-4.17709887e-01 -2.65713990e-01 3.93453091e-01 1.34334922e-01
-3.89988452e-01 -1.04508758e+00 -1.58369653e-02 -1.60997584e-01
1.08206987e+00 -2.22614795e-01 2.66594887e-01 -2.56107479e-01
8.59961212e-01 1.44414440e-01 3.69702846e-01 3.73011023e-01
-1.92596689e-01 7.26082742e-01 3.37852240e-01 -8.57983679e-02
-6.78867340e-01 -9.33594823e-01 -6.56524360e-01 5.29596746e-01
8.01980644e-02 -1.60927802e-01 -9.21797097e-01 -1.25482225e+00
8.25704560e-02 3.86801273e-01 -4.61649746e-01 3.54783982e-01
-1.05415809e+00 -9.87924933e-01 2.82715887e-01 5.75643599e-01
5.27455926e-01 -1.07300842e+00 -4.23211366e-01 1.51996911e-01
-2.10198611e-01 -9.55841839e-01 -3.53532523e-01 3.36645335e-01
-1.25156808e+00 -1.36962187e+00 -6.23162627e-01 -9.28622663e-01
7.18547583e-01 2.32524499e-01 1.05142319e+00 4.86569583e-01
-8.40445220e-01 3.58322263e-01 -7.86615685e-02 -2.04072431e-01
-4.97370303e-01 2.44633928e-01 -8.75551045e-01 -1.42116666e-01
-3.83650780e-01 -4.69684958e-01 -1.10874248e+00 6.96216762e-01
-8.59780908e-01 -9.28427875e-02 7.31058598e-01 9.40260231e-01
1.49885798e+00 4.62564915e-01 3.89582455e-01 -1.24134159e+00
1.44820392e-01 -5.80068767e-01 -4.08303499e-01 8.47535580e-02
-6.16029441e-01 -2.81188339e-01 6.20178998e-01 1.27552107e-01
-9.98778462e-01 -3.49177718e-02 -6.81297839e-01 -4.61095750e-01
-3.98865342e-01 8.92097317e-03 2.99604591e-02 -2.24376008e-01
4.76362646e-01 -2.44896244e-02 2.54820678e-02 -6.17932320e-01
2.92158902e-01 6.25490487e-01 2.64190018e-01 -4.78913158e-01
6.32475853e-01 7.37334847e-01 6.55749440e-01 -8.67836356e-01
-9.01390970e-01 -1.05508173e+00 -8.34494114e-01 -2.41800904e-01
1.30654764e+00 -4.53971058e-01 -5.86979687e-01 2.10236713e-01
-6.24121308e-01 -6.10554636e-01 -7.19041109e-01 2.64844358e-01
-5.40295660e-01 7.32983410e-01 -6.27530158e-01 -4.51402903e-01
-5.87334454e-01 -1.55882251e+00 1.37675190e+00 5.34121655e-02
-2.15577404e-03 -1.08948588e+00 -1.37934849e-01 1.09716558e+00
4.26809788e-02 3.14828932e-01 1.32762480e+00 -5.05051911e-01
-8.85039091e-01 1.08895063e-01 -3.09108496e-01 5.87479889e-01
1.78618133e-01 -1.38199236e-02 -7.91696012e-01 -1.74613521e-01
3.88325870e-01 -1.10714376e-01 1.12741435e+00 6.36166871e-01
2.03870130e+00 -1.30797490e-01 -7.88493097e-01 9.76591766e-01
1.24933529e+00 1.53174233e-02 1.81058690e-01 -2.68090308e-01
1.18679571e+00 8.21838081e-01 6.24346137e-01 1.34702876e-01
2.58855551e-01 4.50920492e-01 1.03855419e+00 -3.49001795e-01
-8.34266961e-01 1.88465044e-01 -3.95878226e-01 8.65898252e-01
-2.51433961e-02 -4.72330481e-01 -8.85720670e-01 5.31436920e-01
-1.44001138e+00 -4.68435168e-01 -9.44955587e-01 1.89429283e+00
6.96424723e-01 1.26722515e-01 5.05311452e-02 1.22846350e-01
5.64670742e-01 6.40112311e-02 -6.04094088e-01 -3.24619599e-02
5.11490941e-01 8.37204218e-01 3.82054001e-01 3.87947291e-01
-1.07326663e+00 5.62792242e-01 5.45348692e+00 1.46684706e+00
-9.92638767e-01 2.81051666e-01 9.10821438e-01 1.84894368e-01
-4.46888983e-01 -4.30517703e-01 -1.07442439e+00 3.04372072e-01
4.18761671e-01 5.31377494e-01 9.84446257e-02 7.25655615e-01
2.22840816e-01 -1.28841206e-01 -6.76467657e-01 6.82914138e-01
-2.09753007e-01 -1.04206443e+00 -3.49306613e-02 3.13151687e-01
8.53676915e-01 2.65981942e-01 -5.53758256e-02 -9.37825814e-02
1.18668161e-01 -1.15345967e+00 -3.98183838e-02 1.74968779e-01
1.02248824e+00 -3.57341886e-01 5.17120600e-01 6.03149056e-01
-1.47125971e+00 4.71198335e-02 -1.11405030e-01 8.19672883e-01
8.55006501e-02 7.51408279e-01 -1.50296044e+00 6.90008521e-01
7.58502662e-01 5.48498273e-01 -5.79999566e-01 1.16858745e+00
-3.06471080e-01 1.08302510e+00 -4.98488486e-01 5.40241562e-02
2.02072144e-01 -3.53484154e-01 6.25917494e-01 1.01322317e+00
2.62641817e-01 3.60525370e-01 4.34042990e-01 6.56938136e-01
-1.71367303e-01 5.24571598e-01 -2.81019717e-01 3.48746449e-01
2.57689469e-02 1.60620880e+00 -1.04213607e+00 -4.09792870e-01
-2.31369630e-01 4.53453809e-01 1.42168611e-01 1.41397957e-02
-8.45512748e-01 3.44281971e-01 6.98734894e-02 7.84592688e-01
5.73388934e-01 1.50013134e-01 -5.77579498e-01 -6.32233381e-01
-2.06090644e-01 -7.36063600e-01 7.40414679e-01 -3.08869123e-01
-1.27833116e+00 5.50080717e-01 1.50943145e-01 -8.86557639e-01
3.17703784e-02 -7.56191313e-01 -6.41124070e-01 6.85133219e-01
-1.84290123e+00 -1.19149125e+00 -6.60883784e-01 6.09943032e-01
9.10426617e-01 2.80705273e-01 3.93309802e-01 1.34731025e-01
-6.34694576e-01 3.47749501e-01 -6.64459616e-02 -2.42946565e-01
3.64624023e-01 -1.63159966e+00 -6.21772036e-02 2.98960596e-01
-1.43875495e-01 1.83444858e-01 -4.61412109e-02 -9.15082812e-01
-9.32560623e-01 -1.53412914e+00 1.93062916e-01 -4.97465551e-01
3.56577069e-01 1.60636470e-01 -9.46926653e-01 4.12679911e-01
-1.75695270e-02 3.23525608e-01 5.74676871e-01 -5.80616772e-01
2.93009818e-01 -1.64612129e-01 -1.38852799e+00 4.14543271e-01
1.05341721e+00 8.63494352e-02 -3.26525331e-01 6.77887738e-01
6.13640845e-01 -5.11975586e-01 -1.34320986e+00 1.14255321e+00
2.73592830e-01 -1.08575392e+00 1.22891915e+00 -5.01825102e-02
1.07794374e-01 -3.39840263e-01 1.93602681e-01 -6.57981753e-01
-3.58378977e-01 -2.40391821e-01 -1.93939909e-01 8.74833941e-01
2.36551568e-01 -6.40977383e-01 1.23355138e+00 1.24082446e-01
-6.18081748e-01 -1.38361597e+00 -1.10621536e+00 -2.59612918e-01
2.88152188e-01 -4.53692257e-01 3.09093446e-01 4.65815306e-01
-9.04100955e-01 1.66814610e-01 5.38995326e-01 6.07963391e-02
7.49594629e-01 3.71829361e-01 7.06709743e-01 -1.21451581e+00
-5.54121614e-01 -8.48355949e-01 3.40830870e-02 -1.38826025e+00
-1.31267890e-01 -1.30682266e+00 7.39713833e-02 -1.96465337e+00
1.79099709e-01 -8.32852185e-01 -2.69251436e-01 2.78497666e-01
-4.68042970e-01 3.66352975e-01 -3.55033100e-01 3.27056319e-01
-1.89741045e-01 2.17227593e-01 2.35149050e+00 -1.61928549e-01
5.27243689e-02 6.73726678e-01 -3.01749289e-01 9.09387529e-01
7.63252616e-01 -5.40558100e-01 -5.23502827e-01 1.78879462e-02
-3.45459193e-01 2.99504250e-01 5.89956701e-01 -8.24742854e-01
-4.45356313e-03 -1.37814909e-01 2.12320387e-01 -1.26254427e+00
3.14883828e-01 -1.15371418e+00 1.28017142e-02 7.72724807e-01
-6.91493079e-02 -3.71718079e-01 -8.86751339e-02 7.60529160e-01
-3.98972183e-02 -5.54726660e-01 1.12866783e+00 -5.31148374e-01
-9.70143527e-02 7.18170166e-01 -1.52262285e-01 1.99032173e-01
1.24411201e+00 -3.21591675e-01 -1.02599867e-01 1.56512484e-01
-8.53166699e-01 5.28107941e-01 2.79744506e-01 -3.36645812e-01
5.88366330e-01 -7.88339913e-01 -6.71379983e-01 3.40259373e-01
-9.45325345e-02 1.10260534e+00 4.70988512e-01 1.31148314e+00
-7.92799890e-01 3.93210083e-01 5.07101715e-01 -1.25163877e+00
-1.57991612e+00 3.34038705e-01 6.55463576e-01 -7.95579195e-01
-7.84629285e-01 1.14637876e+00 1.02733922e+00 -3.33382279e-01
1.44695491e-01 -8.93636227e-01 -3.36599439e-01 -2.28860810e-01
-2.65929490e-01 5.49772918e-01 2.10236102e-01 -7.31438577e-01
-1.38606671e-02 9.63646531e-01 1.93539690e-02 3.47627312e-01
8.53779376e-01 -7.26224557e-02 -3.29572022e-01 4.70936410e-02
1.06479621e+00 6.87811598e-02 -8.99112523e-01 -1.51242909e-03
-3.73976588e-01 -3.00473392e-01 2.23301172e-01 -7.81298637e-01
-1.32500219e+00 1.19210577e+00 5.88478625e-01 3.11735600e-01
1.04827821e+00 2.23760724e-01 1.19759631e+00 -8.74493346e-02
-8.05409998e-03 -6.45834148e-01 2.99263805e-01 -7.50698000e-02
8.34299445e-01 -1.23790181e+00 1.93149701e-01 -1.35169399e+00
-3.46859038e-01 1.06371617e+00 7.12342918e-01 4.73095812e-02
9.95405197e-01 -4.10376396e-03 -2.17633788e-02 -6.32319391e-01
-4.58678871e-01 -3.93299311e-01 7.53864408e-01 4.15901124e-01
2.46699408e-01 1.16436802e-01 -3.44309568e-01 3.27706397e-01
-5.10112196e-02 -4.47612941e-01 -3.89309168e-01 5.60659766e-01
-6.19196236e-01 -1.27098668e+00 -5.81815362e-01 1.00165451e+00
-7.15357780e-01 -8.21471401e-03 -3.06480408e-01 8.98860276e-01
4.37017828e-01 7.67128587e-01 -3.65299612e-01 7.35651404e-02
2.42371678e-01 -1.53065160e-01 5.53635418e-01 -9.96055782e-01
-1.02024531e+00 7.52414405e-01 4.73562256e-03 -4.02096927e-01
-2.63396263e-01 -6.55708015e-01 -1.73183501e+00 3.94306332e-01
-4.82535720e-01 1.86718795e-02 5.43630958e-01 7.33506739e-01
-8.57593939e-02 1.08631647e+00 9.22873139e-01 -4.58874881e-01
-5.37751496e-01 -7.97251880e-01 -4.67537612e-01 3.99621606e-01
1.90300778e-01 -4.25114602e-01 -5.16206741e-01 -1.58496290e-01] | [15.048200607299805, -2.160701036453247] |
9f0d8a61-2910-48b4-b2d7-e0e756ff0ea8 | cascading-convolutional-color-constancy | 1912.11180 | null | https://arxiv.org/abs/1912.11180v1 | https://arxiv.org/pdf/1912.11180v1.pdf | Cascading Convolutional Color Constancy | Regressing the illumination of a scene from the representations of object appearances is popularly adopted in computational color constancy. However, it's still challenging due to intrinsic appearance and label ambiguities caused by unknown illuminants, diverse reflection property of materials and extrinsic imaging factors (such as different camera sensors). In this paper, we introduce a novel algorithm by Cascading Convolutional Color Constancy (in short, C4) to improve robustness of regression learning and achieve stable generalization capability across datasets (different cameras and scenes) in a unique framework. The proposed C4 method ensembles a series of dependent illumination hypotheses from each cascade stage via introducing a weighted multiply-accumulate loss function, which can inherently capture different modes of illuminations and explicitly enforce coarse-to-fine network optimization. Experimental results on the public Color Checker and NUS 8-Camera benchmarks demonstrate superior performance of the proposed algorithm in comparison with the state-of-the-art methods, especially for more difficult scenes. | ['Zhao-Xiang Zhang', 'Yanlin Qian', 'Ke Chen', 'Kui Jia', 'Huanglin Yu', 'Kaiqi Wang'] | 2019-12-24 | null | null | null | null | ['color-constancy'] | ['computer-vision'] | [ 4.95452493e-01 -9.16994572e-01 9.62763578e-02 -5.47750711e-01
-2.76853174e-01 -6.20915949e-01 3.38667661e-01 -5.53277552e-01
-3.55674356e-01 6.61716223e-01 -3.00345063e-01 1.31420679e-02
1.00079417e-01 -1.96428910e-01 -8.39293599e-01 -9.77056384e-01
5.21215081e-01 -2.42002174e-01 5.48876636e-02 -7.79959857e-02
2.95669079e-01 3.45962763e-01 -1.58045828e+00 1.52598843e-01
1.08283818e+00 1.20169568e+00 1.45968944e-01 4.87251252e-01
-3.12441811e-02 1.01412404e+00 -3.29201043e-01 -4.86653626e-01
5.04448116e-01 -5.47966063e-01 -2.21461132e-01 4.33263630e-01
8.66020679e-01 -2.92247474e-01 -1.34457245e-01 1.43309271e+00
1.57305837e-01 2.13619292e-01 5.77305675e-01 -1.23826277e+00
-1.16263366e+00 5.77642471e-02 -1.08209157e+00 -6.60391301e-02
-1.02533758e-01 3.05125445e-01 8.44805181e-01 -8.86483610e-01
1.41787097e-01 1.17806995e+00 5.03516018e-01 5.82601726e-01
-1.34454131e+00 -1.04829907e+00 4.28205073e-01 2.76044130e-01
-1.27881539e+00 -4.75993752e-01 9.81363058e-01 -3.53591919e-01
3.71363968e-01 2.57947981e-01 3.83500695e-01 1.11953437e+00
1.04275256e-01 6.46750152e-01 1.92313302e+00 -3.00315708e-01
2.55309306e-02 1.62704006e-01 1.13917843e-01 8.26802373e-01
3.98273766e-01 9.08374414e-02 -4.52354938e-01 2.25446880e-01
1.07011652e+00 8.64723399e-02 -4.87066329e-01 -3.75761002e-01
-9.35412109e-01 3.59059066e-01 7.44350970e-01 -3.10549766e-01
-8.09156336e-03 2.56627202e-01 1.24531589e-01 2.78209716e-01
3.69315296e-01 2.66675681e-01 -6.12659991e-01 3.54055017e-01
-5.19787490e-01 -3.31506319e-02 3.48621160e-01 1.05591583e+00
8.88372898e-01 4.07265633e-01 -1.62377581e-01 1.03047168e+00
2.63190717e-01 6.61530674e-01 1.66657701e-01 -7.52613664e-01
4.59047735e-01 5.25855839e-01 2.85781622e-01 -9.67574477e-01
-3.18872660e-01 -6.12679124e-01 -1.18534791e+00 5.28411627e-01
5.36750674e-01 -7.11362660e-02 -1.15939033e+00 1.82567799e+00
2.50288099e-01 5.41144490e-01 -1.34952426e-01 1.31499732e+00
7.17003047e-01 4.06847030e-01 -2.53679324e-02 -1.56878829e-01
1.11385083e+00 -1.23768497e+00 -6.11850619e-01 -2.93917477e-01
-2.07721978e-01 -1.08163416e+00 1.10993743e+00 5.96219063e-01
-7.97747791e-01 -9.45487261e-01 -1.17822015e+00 -1.48139879e-01
-3.42886984e-01 4.59576100e-01 8.43650758e-01 8.05733442e-01
-8.48331809e-01 2.06233352e-01 -5.90219378e-01 6.69282377e-02
4.33418274e-01 3.09351563e-01 -1.75296798e-01 -3.82328391e-01
-8.43858123e-01 6.42492652e-01 1.43950790e-01 4.93687034e-01
-9.16001320e-01 -6.67235553e-01 -6.52445674e-01 -3.20245087e-01
3.89401197e-01 -6.71744227e-01 7.69063175e-01 -1.81535006e+00
-1.94149828e+00 7.00532854e-01 -3.68294492e-03 2.17232317e-01
6.27165139e-01 -4.05509591e-01 -5.47583342e-01 -3.23860317e-01
-4.14819777e-01 1.77125141e-01 1.35170817e+00 -1.63743687e+00
-5.32928467e-01 -3.62861067e-01 3.23850363e-01 2.05960304e-01
-1.85830399e-01 8.93123075e-02 -8.36402953e-01 -5.48257947e-01
1.79599389e-01 -1.01082277e+00 -9.01920125e-02 2.95752436e-01
-4.70325232e-01 2.24259198e-01 6.25965238e-01 -5.25202394e-01
8.82715583e-01 -2.05336761e+00 1.42850026e-01 1.00301608e-01
1.51563808e-01 2.57822812e-01 -3.38807881e-01 -2.78201103e-01
-1.96971327e-01 -3.13170731e-01 -1.64854333e-01 -4.01099026e-01
-1.91762120e-01 2.75709361e-01 7.14240298e-02 8.83488297e-01
5.17622888e-01 6.12980306e-01 -8.41988206e-01 -3.51100177e-01
4.38676387e-01 6.99118972e-01 -4.49974597e-01 3.40457559e-01
-2.33022124e-01 9.68047857e-01 -3.22825372e-01 8.75354052e-01
1.21945930e+00 -3.75574291e-01 -1.03392839e-01 -6.65424407e-01
-2.37292618e-01 -2.87701279e-01 -1.36425316e+00 1.66231513e+00
-5.80095947e-01 5.59150279e-01 1.78484693e-01 -7.90632546e-01
8.82227838e-01 -2.16847554e-01 1.98814780e-01 -6.95487559e-01
3.38584125e-01 1.20589852e-01 -1.82056669e-02 -4.70044523e-01
3.99128526e-01 8.72832760e-02 1.56511679e-01 3.44378389e-02
3.32672521e-02 1.06922828e-01 -1.43302992e-01 -4.18488026e-01
4.54601586e-01 5.96282303e-01 2.83987001e-02 -1.78173438e-01
8.80070567e-01 -4.44046795e-01 8.71025264e-01 7.20637202e-01
-2.44925529e-01 7.80607283e-01 9.07399878e-02 -3.88191342e-01
-9.73797202e-01 -1.02757871e+00 -2.69271851e-01 1.16495144e+00
6.07377172e-01 2.32381210e-01 -4.98931795e-01 -4.20895636e-01
1.82351097e-02 3.17249537e-01 -7.38376975e-01 -6.25936128e-03
-4.16695982e-01 -9.72833216e-01 2.51143068e-01 4.91687208e-01
7.83859015e-01 -5.58416069e-01 -2.88709700e-01 -1.04366690e-01
6.78043738e-02 -1.36648548e+00 -4.34881002e-01 2.10587800e-01
-3.93702865e-01 -1.22295165e+00 -6.21525884e-01 -6.68489575e-01
9.03181195e-01 6.20290995e-01 1.07875228e+00 -8.47665593e-02
-4.57286626e-01 2.90008545e-01 -2.64424890e-01 -2.22272143e-01
-1.50142357e-01 -3.37087572e-01 -7.61588812e-02 6.54181361e-01
1.16528332e-01 -2.36791268e-01 -9.63489890e-01 3.25056970e-01
-9.11670208e-01 2.46977970e-01 6.89139903e-01 1.10315418e+00
6.10268712e-01 1.01231262e-01 1.39759406e-01 -1.12227166e+00
2.09923849e-01 -3.04247141e-01 -1.11864865e+00 5.49085498e-01
-6.60871506e-01 -6.20524846e-02 8.21769774e-01 -4.15520579e-01
-1.63701916e+00 1.70946106e-01 3.89609814e-01 -6.66614354e-01
-4.87638563e-02 2.12793164e-02 -3.00954252e-01 -7.27114439e-01
4.76515710e-01 2.33947694e-01 -1.94271848e-01 -4.50233489e-01
5.64450324e-01 3.44759136e-01 7.89406002e-01 -7.97068655e-01
1.06989098e+00 4.54166651e-01 2.88322866e-01 -5.37459850e-01
-1.06127203e+00 -4.75608647e-01 -5.44046402e-01 -4.79017526e-01
7.08244979e-01 -1.15561461e+00 -8.26176465e-01 1.05847156e+00
-1.05546725e+00 -1.27294406e-01 3.11731666e-01 3.22044104e-01
-1.37212664e-01 2.67551184e-01 -5.52218795e-01 -8.21506381e-01
-1.54026017e-01 -1.28111589e+00 8.56286347e-01 8.17303956e-01
6.82508469e-01 -8.98048222e-01 -2.11746559e-01 3.12537998e-01
6.36786342e-01 5.89245260e-01 7.54046082e-01 2.62426376e-01
-8.14351141e-01 3.70761231e-02 -8.38532507e-01 8.41882169e-01
5.41914642e-01 3.33824724e-01 -1.26818919e+00 -3.13853800e-01
-1.47005185e-01 -4.12246794e-01 1.02184582e+00 2.57124692e-01
1.58166468e+00 -1.83471754e-01 2.52182156e-01 1.13412035e+00
2.15069604e+00 -1.65496513e-01 5.63219309e-01 3.32136422e-01
1.23183417e+00 3.55405539e-01 4.42338735e-01 5.37980914e-01
1.84994325e-01 5.31893969e-01 7.62105167e-01 -5.75589597e-01
-2.80138016e-01 1.03559904e-01 3.85296971e-01 7.66686201e-01
-4.08380538e-01 -5.10028638e-02 -2.60978729e-01 6.47203848e-02
-1.72013950e+00 -6.22970998e-01 -4.51852739e-01 2.32154942e+00
9.63242650e-01 -2.94576734e-02 -2.34857053e-01 -1.92148432e-01
7.91122675e-01 2.20747739e-01 -9.49287593e-01 -2.28147969e-01
-5.73544562e-01 4.07623589e-01 8.78997207e-01 2.30896726e-01
-1.24256730e+00 8.35910380e-01 5.66301632e+00 5.91385663e-01
-1.40749466e+00 1.01359971e-01 7.78781772e-01 1.12904899e-01
-1.21797621e-01 -2.63351817e-02 -5.79886138e-01 4.45880413e-01
1.63646415e-01 3.69483203e-01 9.52333272e-01 4.58669245e-01
-9.17997770e-03 8.97276998e-02 -9.39207911e-01 1.20310485e+00
4.41554815e-01 -8.71980608e-01 -7.62540251e-02 -5.51314294e-01
1.36570907e+00 3.51373814e-02 6.50816858e-01 5.07106259e-02
2.68403620e-01 -8.78576696e-01 7.02342927e-01 8.38899016e-01
9.71880317e-01 -4.87498641e-01 4.51471746e-01 -2.06020489e-01
-1.18951309e+00 -1.51467159e-01 -5.17931700e-01 8.02106857e-02
-3.25032353e-01 3.31034780e-01 -7.56890997e-02 6.73517823e-01
7.12575018e-01 9.23304379e-01 -8.37736130e-01 1.07743847e+00
-3.43725383e-01 4.06501353e-01 1.85750034e-02 7.03925639e-02
1.86349005e-01 -5.41262686e-01 1.91923499e-01 1.25034440e+00
-6.63459003e-02 -6.97033629e-02 1.40761554e-01 1.02652752e+00
-2.14665487e-01 -1.19732758e-02 -4.27657589e-02 4.11038965e-01
1.69354126e-01 1.59204316e+00 -3.46809804e-01 1.17659979e-01
-8.56774747e-01 1.21595383e+00 4.26685870e-01 8.60502422e-01
-1.13613045e+00 -2.01147169e-01 7.70108581e-01 -2.87942261e-01
2.30691209e-01 -2.49744743e-01 -2.10577697e-01 -1.39075267e+00
-6.21504337e-03 -1.03829324e+00 1.31010532e-01 -9.76540864e-01
-1.69161153e+00 4.02764231e-01 -4.68656719e-01 -1.46878099e+00
5.29342115e-01 -1.15987635e+00 -5.29310524e-01 9.80961382e-01
-2.19761872e+00 -1.64139986e+00 -8.60412240e-01 1.01548207e+00
4.69130516e-01 -5.04792258e-02 5.62205017e-01 4.26635444e-01
-8.42901528e-01 8.44395697e-01 5.14665306e-01 2.13294774e-02
1.20676577e+00 -1.23245466e+00 -6.35752603e-02 9.62592721e-01
-1.20840035e-01 5.93740702e-01 5.53928792e-01 -9.00238529e-02
-1.85547602e+00 -1.35596597e+00 -1.40506029e-01 -1.39887750e-01
6.34077907e-01 -2.55611658e-01 -7.71366119e-01 4.47486073e-01
2.58527607e-01 4.00266141e-01 5.70464313e-01 7.34182149e-02
-8.99354875e-01 -7.23710239e-01 -9.00959253e-01 5.10518849e-01
8.87318254e-01 -4.52359438e-01 4.79543209e-02 2.72015363e-01
3.59664917e-01 -7.06386507e-01 -6.01428568e-01 3.61714751e-01
7.46257663e-01 -1.04212368e+00 9.45915878e-01 -6.06365144e-01
4.49993759e-01 -7.35011280e-01 -3.45217317e-01 -1.02803469e+00
-5.98422050e-01 -6.05996072e-01 1.94435626e-01 1.42108297e+00
1.79754108e-01 -7.42490053e-01 3.85212153e-01 7.70845771e-01
-8.05278346e-02 -4.46725458e-01 -6.79320693e-01 -5.62470496e-01
-1.39921352e-01 -8.19835737e-02 4.77515697e-01 9.91620243e-01
-8.74108613e-01 1.30840600e-01 -9.68726933e-01 4.59890425e-01
1.11139023e+00 3.17999095e-01 9.55865443e-01 -1.08970296e+00
-4.21281457e-01 -4.50786442e-01 -3.64806980e-01 -1.00244677e+00
2.52338290e-01 -5.96530318e-01 1.59584939e-01 -9.12961721e-01
5.12304604e-01 -6.51719868e-01 -9.58206236e-01 3.11219811e-01
-6.05044544e-01 5.36978245e-01 1.34929091e-01 1.70355827e-01
-8.49643469e-01 5.22308648e-01 1.70528662e+00 -4.33362782e-01
4.85677272e-02 -1.08913101e-01 -7.23671854e-01 6.77776039e-01
6.20262802e-01 -9.79274213e-02 -3.86433184e-01 -8.61596346e-01
2.57270902e-01 -4.59142476e-01 5.65840542e-01 -9.17830050e-01
2.35010520e-01 -5.56107640e-01 9.38294590e-01 -1.89796522e-01
3.47007364e-01 -9.69946206e-01 2.52062440e-01 6.91628233e-02
-1.51662007e-01 -4.85249236e-02 2.05832273e-01 7.91857421e-01
-9.54942182e-02 1.13364749e-01 1.18766654e+00 -3.70425545e-02
-9.96840894e-01 4.23238218e-01 3.46280664e-01 -5.79168834e-03
7.24288881e-01 -1.33714110e-01 -6.18646622e-01 -6.22366592e-02
-1.42567843e-01 -8.72743502e-03 6.87521040e-01 4.98779267e-01
5.08805335e-01 -1.34549069e+00 -8.01032722e-01 3.52051258e-01
3.36910963e-01 -1.28118694e-01 3.60531837e-01 7.25477278e-01
-5.24352193e-01 -1.79678753e-01 -5.01701474e-01 -6.96304262e-01
-1.10579240e+00 4.65410739e-01 5.56687891e-01 2.16253594e-01
-2.21330494e-01 1.04449046e+00 5.41706979e-01 -1.67614952e-01
1.42076537e-01 -2.98929662e-01 -5.40656447e-02 -4.97740299e-01
3.07696819e-01 2.05337599e-01 -6.96846694e-02 -7.77172863e-01
-2.48912081e-01 9.97783542e-01 -1.06598020e-01 4.82086599e-01
1.16439664e+00 -3.22444767e-01 -3.38208258e-01 4.74029899e-01
1.20582783e+00 -8.99628848e-02 -1.79528284e+00 -4.46882218e-01
-5.17137647e-01 -9.22189951e-01 1.26927748e-01 -8.96980345e-01
-1.60693395e+00 6.17470264e-01 8.88938248e-01 -2.31485605e-01
1.56296349e+00 -5.02762675e-01 3.99268478e-01 1.42174914e-01
3.11408043e-01 -1.18023479e+00 1.58159807e-01 2.42944509e-01
7.24872112e-01 -1.59029543e+00 1.93347141e-01 -4.11842614e-01
-6.35640979e-01 1.16972280e+00 1.05698967e+00 -3.38528991e-01
4.87167090e-01 -7.07666995e-03 3.38421226e-01 2.46573061e-01
-4.55340087e-01 -1.55933514e-01 5.76494038e-01 5.00944138e-01
5.54262757e-01 6.21746480e-02 -2.50489973e-02 4.96342897e-01
3.95012319e-01 -2.26180404e-01 3.47678721e-01 3.97801965e-01
-3.19456272e-02 -1.02214611e+00 -3.85309607e-01 2.92581767e-01
-4.83320713e-01 -1.23316400e-01 -1.93221584e-01 6.62492633e-01
4.74337727e-01 1.10363233e+00 -1.42910868e-01 -2.03873441e-01
1.76936194e-01 -3.90398055e-01 8.41172814e-01 -1.19211644e-01
-4.86997485e-01 1.62098020e-01 -3.21594238e-01 -7.32838750e-01
-8.59269977e-01 -6.16491020e-01 -6.39777958e-01 -8.16124976e-02
-6.42510712e-01 -4.87382948e-01 8.05460989e-01 6.29451036e-01
-1.92213058e-03 6.41983449e-01 1.16638720e+00 -8.34491372e-01
-5.37543058e-01 -7.50235081e-01 -7.18193889e-01 7.88346291e-01
6.55102491e-01 -7.81450927e-01 -3.99829328e-01 4.08692569e-01] | [10.516283988952637, -2.5699214935302734] |
67cc21a4-13ff-49a4-9701-bd8f40e7f99f | brain-effective-connectome-based-on-fmri-and | 2302.05451 | null | https://arxiv.org/abs/2302.05451v2 | https://arxiv.org/pdf/2302.05451v2.pdf | Brain Effective Connectome based on fMRI and DTI Data: Bayesian Causal Learning and Assessment | Neuroscientific studies aim to find an accurate and reliable brain Effective Connectome (EC). Although current EC discovery methods have contributed to our understanding of brain organization, their performances are severely constrained by the short sample size and poor temporal resolution of fMRI data, and high dimensionality of the brain connectome. By leveraging the DTI data as prior knowledge, we introduce two Bayesian causal discovery frameworks -the Bayesian GOLEM (BGOLEM) and Bayesian FGES (BFGES) methods- that offer significantly more accurate and reliable ECs and address the shortcomings of the existing causal discovery methods in discovering ECs based on only fMRI data. Through a series of simulation studies on synthetic and hybrid (DTI of the Human Connectome Project (HCP) subjects and synthetic fMRI) data, we demonstrate the effectiveness of the proposed methods in discovering EC. To numerically assess the improvement in the accuracy of ECs with our method on empirical data, we first introduce the Pseudo False Discovery Rate (PFDR) as a new computational accuracy metric for causal discovery in the brain. We show that our Bayesian methods achieve higher accuracy than traditional methods on HCP data. Additionally, we measure the reliability of discovered ECs using the Rogers-Tanimoto index for test-retest data and show that our Bayesian methods provide significantly more reproducible ECs than traditional methods. Overall, our study's numerical and graphical results highlight the potential for these frameworks to advance our understanding of brain function and organization significantly. | ['Babak Nadjar Araabi', 'Alireza Akhondi-Asl', 'Yamin Bagheri', 'Mahdi Dehshiri', 'Abdolmahdi Bagheri'] | 2023-02-10 | null | null | null | null | ['causal-discovery'] | ['knowledge-base'] | [-4.75028269e-02 -4.87891212e-02 -2.04694644e-01 -2.97335476e-01
-1.57777533e-01 -2.59993553e-01 6.63186729e-01 -2.62076229e-01
-2.79150486e-01 1.20687556e+00 4.19535637e-01 -3.38557094e-01
-9.39489841e-01 -5.49565434e-01 -4.41121429e-01 -5.53446054e-01
-9.18832064e-01 2.31441796e-01 2.16303959e-01 2.31464118e-01
3.46899092e-01 3.65819454e-01 -9.76455331e-01 -8.34093019e-02
1.19429278e+00 8.58009338e-01 1.16602607e-01 1.39572889e-01
5.00462294e-01 2.80362070e-01 -1.58804059e-01 -4.68354046e-01
1.90903574e-01 -4.64141846e-01 -9.42034006e-01 -4.19480056e-01
7.13595015e-04 -3.41371924e-01 -5.45685053e-01 1.07365787e+00
4.54194903e-01 5.64474836e-02 7.84770370e-01 -1.21136081e+00
-5.90907574e-01 9.81390357e-01 -7.86901474e-01 8.40184629e-01
1.11225128e-01 1.38613269e-01 7.79975593e-01 -8.43267262e-01
6.67531908e-01 1.37025797e+00 6.68737113e-01 1.81388140e-01
-1.54209435e+00 -1.04321873e+00 1.18681736e-01 4.70907420e-01
-1.59727120e+00 -4.34135437e-01 5.88125348e-01 -6.98051333e-01
6.18515491e-01 -1.43055022e-01 8.23841870e-01 1.39339519e+00
7.00372994e-01 2.76277840e-01 1.65283763e+00 -3.94295231e-02
4.90269989e-01 -4.01192784e-01 3.28986466e-01 5.61102390e-01
5.82500041e-01 5.83853900e-01 -7.21584976e-01 -4.98488903e-01
1.16529429e+00 -3.50559771e-01 -2.97236949e-01 -7.17499256e-02
-1.39468479e+00 8.31656337e-01 4.39044744e-01 4.21573639e-01
-7.09090352e-01 4.72100914e-01 2.54081964e-01 -8.05035383e-02
3.98309708e-01 1.49218112e-01 -3.06355208e-01 1.41829893e-01
-1.17803264e+00 1.83468789e-01 5.58474004e-01 5.50509632e-01
1.99307781e-03 5.82703911e-02 -2.54144400e-01 5.71710765e-01
3.10096294e-01 3.04846078e-01 2.90665627e-01 -1.01638234e+00
-7.24014044e-02 -6.35967553e-02 3.78169268e-02 -1.23932028e+00
-5.27101994e-01 -7.32376039e-01 -1.18255508e+00 -2.91032970e-01
2.50804842e-01 -5.48044592e-02 -4.27482069e-01 2.00839448e+00
1.42865971e-01 3.19549292e-01 -6.33387804e-01 8.76882613e-01
2.39965335e-01 6.05885349e-02 3.97224903e-01 -6.85321867e-01
1.13122833e+00 -7.94129223e-02 -7.61979401e-01 9.85007435e-02
4.92282445e-03 -1.29183188e-01 5.50617754e-01 5.00646293e-01
-9.51400101e-01 -3.37274671e-01 -8.50556076e-01 5.32526433e-01
3.91085893e-02 -8.60775933e-02 1.10926807e+00 6.71133518e-01
-1.02687681e+00 5.52586079e-01 -9.04826880e-01 -3.52818221e-01
8.30540419e-01 2.40416691e-01 -3.34125429e-01 -1.85974941e-01
-1.34940135e+00 7.43717432e-01 4.10854369e-01 2.15923369e-01
-1.52327943e+00 -1.06264436e+00 -1.93128631e-01 2.35221028e-01
2.47008279e-01 -7.96175063e-01 6.72915757e-01 -5.80280840e-01
-1.03224027e+00 1.83818668e-01 -3.46383005e-02 -4.92554605e-01
3.01070422e-01 1.50968045e-01 -2.76060849e-01 4.99365956e-01
3.24551761e-01 7.73292124e-01 5.38388491e-01 -1.02061701e+00
8.04354846e-02 -5.17545879e-01 -3.39212239e-01 -3.87739152e-01
-1.68702349e-01 -6.70627691e-03 2.88135320e-01 -7.10524499e-01
3.48023295e-01 -5.82489669e-01 -1.93711162e-01 6.03033826e-02
-4.21663880e-01 -1.82608664e-01 1.10933796e-01 -7.49940336e-01
1.00183690e+00 -1.94946122e+00 -2.46612187e-02 4.07572091e-01
8.03938925e-01 -2.55997688e-01 -2.08159551e-01 1.85836330e-01
-4.30781364e-01 4.42599058e-01 -3.70338559e-01 3.83428186e-01
-2.42813006e-01 6.63314713e-03 -1.12197153e-01 8.16942751e-01
1.29270554e-01 9.10990179e-01 -1.15553474e+00 -5.21293104e-01
-2.06416383e-01 4.88630742e-01 -5.72248757e-01 -1.83678493e-01
3.19945753e-01 7.06110120e-01 -4.53614533e-01 2.72422910e-01
5.93870997e-01 -2.54486918e-01 5.86228073e-01 -3.01257402e-01
-1.70341104e-01 1.41658351e-01 -8.61883163e-01 1.38407290e+00
1.55809581e-01 4.90776449e-01 5.91844204e-04 -1.23595560e+00
7.31491983e-01 4.25596237e-01 6.64147556e-01 -7.05147207e-01
5.38627431e-02 5.03188781e-02 6.81853592e-01 -3.86814922e-01
-3.35568577e-01 -2.73207247e-01 3.69979590e-01 4.60652053e-01
2.95157194e-01 3.22857887e-01 1.89278796e-01 4.68629301e-01
1.47012091e+00 -2.29200572e-01 3.92754585e-01 -1.04791713e+00
-6.90076798e-02 -2.22496584e-01 8.20874333e-01 7.91335940e-01
-5.77914238e-01 -8.34945738e-02 8.46986830e-01 -6.33228570e-02
-1.02087450e+00 -1.50004339e+00 -7.34015822e-01 3.59955341e-01
-2.26467907e-01 -9.42690149e-02 -6.71982825e-01 -4.00658935e-01
1.12722784e-01 6.68884754e-01 -8.61505687e-01 -2.33580232e-01
-1.53080761e-01 -1.48138714e+00 6.91840649e-01 4.88469750e-01
6.34091198e-01 -5.57416558e-01 -4.82287496e-01 2.44156912e-01
-4.02057528e-01 -9.60367024e-01 -8.59779790e-02 -1.94853932e-01
-1.25574613e+00 -1.31701529e+00 -4.11093026e-01 -4.60869744e-02
6.09072804e-01 1.33216575e-01 7.67813563e-01 -5.56205548e-02
-6.39281392e-01 2.49083191e-01 -1.64883927e-01 9.20195580e-02
6.23520557e-03 -4.27515656e-01 5.94538450e-01 -1.68675825e-01
4.43484858e-02 -1.07935798e+00 -9.79680121e-01 3.73873830e-01
-6.76514149e-01 -2.08362564e-02 6.93574250e-01 9.75757003e-01
2.34598398e-01 3.18497241e-01 1.15521407e+00 -5.55872440e-01
8.50736499e-01 -1.04593086e+00 -6.04401469e-01 -4.30402011e-02
-1.13571393e+00 -4.40935530e-02 -4.09374088e-02 -5.39583325e-01
-1.33593285e+00 -3.86587352e-01 2.84147471e-01 -1.11393720e-01
1.68651521e-01 9.76679981e-01 2.64726877e-01 -7.36873373e-02
7.15386689e-01 -1.35024697e-01 -1.34650633e-01 -3.20918351e-01
2.77216285e-01 1.26913637e-01 4.64528084e-01 -8.51615787e-01
1.86406210e-01 4.77890223e-01 3.10018897e-01 -5.36508858e-01
-4.91126001e-01 -4.60100248e-02 -9.83441830e-01 -4.31829304e-01
5.81989586e-01 -7.84190118e-01 -9.87124920e-01 -7.66387507e-02
-1.02957582e+00 -2.48009145e-01 4.47397560e-01 9.43251133e-01
-4.42421287e-01 4.02437866e-01 -7.10524917e-01 -1.05974603e+00
-1.33648440e-01 -8.79730105e-01 3.98548037e-01 -1.78970158e-01
-3.00623983e-01 -9.66017604e-01 1.01909481e-01 1.70863345e-01
4.30836529e-01 5.21210313e-01 1.33449697e+00 -2.87556350e-01
-3.88475239e-01 4.12829295e-02 -5.92469931e-01 -1.11678109e-01
-1.86995924e-01 1.23018324e-01 -6.68327272e-01 -1.31714791e-01
9.28245634e-02 4.51969467e-02 8.69885504e-01 8.93748283e-01
1.11898482e+00 -3.04195166e-01 -6.14933074e-01 9.69501287e-02
1.37431514e+00 9.94970948e-02 7.67864764e-01 -3.61290485e-01
2.28619978e-01 8.76307487e-01 2.09859580e-01 5.52821755e-01
2.46810496e-01 4.14527059e-01 4.27937329e-01 2.46260121e-01
-1.50850147e-01 -1.65613964e-01 1.60244346e-01 9.92607594e-01
-4.44190890e-01 3.48927565e-02 -1.05069923e+00 7.85014689e-01
-1.87455785e+00 -1.10925448e+00 -5.77125788e-01 2.23139405e+00
9.88331676e-01 2.58943792e-02 1.07780881e-01 -1.04625240e-01
7.47920990e-01 -5.54576576e-01 -5.50360024e-01 2.74534971e-01
-3.60886529e-02 2.70045847e-01 4.02498424e-01 2.13515297e-01
-4.15390015e-01 4.98026848e-01 7.79315233e+00 6.61808729e-01
-5.42286813e-01 6.60699069e-01 7.84766018e-01 -2.39118025e-01
-1.20209843e-01 1.17147475e-01 -3.35418284e-01 4.82411504e-01
1.21417201e+00 -4.04620379e-01 7.35711396e-01 3.03243369e-01
7.54787087e-01 -4.61141467e-01 -9.99495804e-01 7.21947134e-01
-3.93105894e-01 -1.23006940e+00 -3.42416704e-01 3.81462127e-01
8.56600404e-01 8.89843628e-02 -1.95966795e-01 -1.79214418e-01
5.42935729e-01 -1.04644191e+00 5.86993575e-01 1.07550621e+00
7.43824899e-01 -4.82178003e-01 6.38873577e-01 1.27357200e-01
-7.11586773e-01 -1.73967034e-01 -5.94970584e-01 -1.60513833e-01
7.64788240e-02 1.47930157e+00 -6.35496318e-01 4.04400975e-01
8.84084463e-01 5.92548609e-01 -3.45239788e-01 1.29918742e+00
-3.54895562e-01 9.86198068e-01 -2.51149416e-01 1.17348611e-01
-2.78838634e-01 5.55709284e-03 6.40691221e-01 8.77721190e-01
2.43050903e-01 5.31623840e-01 -2.22189993e-01 1.87370908e+00
1.06647082e-01 -2.56849408e-01 -2.81849772e-01 -2.29068503e-01
8.42452407e-01 1.33201277e+00 -1.01758039e+00 -2.35195100e-01
2.52093934e-02 3.86994213e-01 3.31101000e-01 4.37189996e-01
-7.09628522e-01 4.46020588e-02 4.29978192e-01 9.63271260e-02
4.99990918e-02 -6.77644789e-01 -4.76463765e-01 -1.04633105e+00
-3.35139126e-01 -4.93173510e-01 2.42355451e-01 -8.09255719e-01
-1.76207149e+00 2.64716685e-01 6.96310222e-01 -3.55730832e-01
-2.86297384e-03 -5.21553040e-01 -4.82695907e-01 9.21152830e-01
-1.00355220e+00 -6.16874695e-01 -1.00207083e-01 5.08433521e-01
7.00273812e-02 3.09596509e-01 4.09664750e-01 3.60093921e-01
-7.66661286e-01 1.22356743e-01 3.07600740e-02 -7.32937455e-02
5.36425114e-01 -8.17053616e-01 8.20902437e-02 9.39968348e-01
-1.80888772e-01 1.15996516e+00 6.21053398e-01 -1.25320923e+00
-1.04516089e+00 -6.82211995e-01 3.70950639e-01 -2.49811172e-01
1.02504528e+00 -4.43215847e-01 -6.37906373e-01 5.27075410e-01
-7.87258223e-02 -1.49102360e-02 5.76567352e-01 3.59749079e-01
-2.53678322e-01 4.71784398e-02 -1.22539949e+00 4.77515042e-01
1.45964301e+00 -2.12676138e-01 -6.58742130e-01 3.55859637e-01
4.00916338e-01 6.25000775e-01 -1.44863522e+00 5.42150736e-01
8.25527191e-01 -8.99415970e-01 8.60046148e-01 -5.47617197e-01
3.41360718e-01 -9.41865295e-02 7.42481798e-02 -1.39019227e+00
-8.02563190e-01 -2.01971203e-01 1.01911299e-01 1.09464681e+00
1.36061147e-01 -7.97300339e-01 1.86568454e-01 7.19437718e-01
1.29298747e-01 -5.12998521e-01 -1.25029588e+00 -9.30927277e-01
1.73271537e-01 -4.64767098e-01 3.68615419e-01 1.21017587e+00
3.49372655e-01 1.03628188e-01 -9.56793353e-02 2.05880553e-02
1.27724934e+00 -3.77061784e-01 4.30149138e-02 -1.69789648e+00
-1.62806809e-01 -4.88349110e-01 -1.77920669e-01 -2.49527395e-01
4.48427834e-02 -8.56352925e-01 -4.26937379e-02 -1.16200674e+00
8.70258152e-01 -5.06168962e-01 -3.19860935e-01 5.07939458e-01
-3.94599028e-02 9.98094454e-02 -2.66080648e-01 3.58329952e-01
-3.54376473e-02 7.01657772e-01 1.01458454e+00 2.25463182e-01
2.65231222e-01 -6.37392521e-01 -6.38037682e-01 5.35332203e-01
5.75826347e-01 -7.75280535e-01 -4.99118149e-01 -1.25161350e-01
4.20564532e-01 3.26246023e-01 1.02858317e+00 -6.89969480e-01
1.88876837e-01 -1.28652796e-01 7.29818106e-01 -2.06513181e-01
-1.33234650e-01 -3.11032921e-01 4.33229685e-01 7.13669717e-01
-2.89447755e-01 2.96427272e-02 1.04970157e-01 7.99393117e-01
3.10275078e-01 -5.31486645e-02 6.93190336e-01 -1.25856534e-01
-2.47433066e-01 2.87792683e-01 -5.21699965e-01 -1.00064054e-01
5.94804168e-01 1.26023725e-01 -5.83611608e-01 -2.02830851e-01
-7.24823475e-01 -6.84214616e-03 -3.13640147e-01 3.23011912e-02
6.91317081e-01 -1.29815781e+00 -8.21651220e-01 -1.28642976e-01
-3.53203207e-01 -9.45021689e-01 3.09578925e-01 1.70305657e+00
9.99466404e-02 6.48731291e-01 -6.27968252e-01 -4.28243220e-01
-5.29527783e-01 5.86302757e-01 2.07314581e-01 -3.31793725e-02
-4.05122817e-01 6.11758769e-01 3.80719543e-01 5.85697219e-03
-2.96264321e-01 -1.16322808e-01 4.57333699e-02 -8.66912231e-02
4.89130706e-01 7.73565352e-01 -2.41292372e-01 -2.01005310e-01
-4.85518247e-01 -1.37550876e-01 1.81126997e-01 -3.29607069e-01
1.44462216e+00 -2.82806873e-01 -7.02161133e-01 3.27629864e-01
6.17668092e-01 -1.53529957e-01 -1.12167966e+00 1.32580340e-01
6.08505420e-02 -4.42220539e-01 5.16656280e-01 -1.12991786e+00
-9.35698509e-01 6.84984326e-01 7.58428395e-01 8.72125253e-02
8.42033505e-01 -6.04098216e-02 1.66154265e-01 -7.46862665e-02
8.01446736e-01 -7.42094457e-01 -4.09806892e-02 -3.26885357e-02
9.78417873e-01 -8.38776886e-01 2.98147142e-01 -6.22422159e-01
-1.69445962e-01 9.49625015e-01 4.09559071e-01 -2.02936471e-01
8.64512563e-01 4.99555394e-02 -9.00588334e-01 -6.27568603e-01
-9.25993621e-01 5.11283949e-02 3.35824072e-01 6.14131570e-01
4.88933116e-01 3.11915845e-01 -9.86614764e-01 9.71764624e-01
-4.98476438e-02 2.55442888e-01 5.37843585e-01 2.84522444e-01
-2.03251109e-01 -6.47593081e-01 -2.13524133e-01 8.29127967e-01
-3.96508604e-01 -4.52164680e-01 -2.63710350e-01 8.60512316e-01
-8.62562433e-02 1.12376320e+00 3.29803899e-02 -1.06873073e-01
-2.59834200e-01 -1.00516239e-02 7.68478334e-01 -3.37490529e-01
-1.75360050e-02 1.15993790e-01 5.09764291e-02 -7.79938400e-01
-6.15518272e-01 -9.14885938e-01 -1.09445953e+00 -5.30027926e-01
-4.43290412e-01 8.82801414e-02 6.24358058e-01 1.16593599e+00
5.28104365e-01 5.84528029e-01 3.13760668e-01 -5.05697370e-01
-3.83391857e-01 -1.18104804e+00 -7.60709703e-01 -1.97689086e-02
-2.40246013e-01 -1.35336590e+00 -3.66323262e-01 8.57096631e-03] | [12.37670612335205, 3.4296979904174805] |
0a61c8cf-27fb-4d2e-a83c-0d7c8f7526e0 | gaitfi-robust-device-free-human | 2208.14326 | null | https://arxiv.org/abs/2208.14326v1 | https://arxiv.org/pdf/2208.14326v1.pdf | GaitFi: Robust Device-Free Human Identification via WiFi and Vision Multimodal Learning | As an important biomarker for human identification, human gait can be collected at a distance by passive sensors without subject cooperation, which plays an essential role in crime prevention, security detection and other human identification applications. At present, most research works are based on cameras and computer vision techniques to perform gait recognition. However, vision-based methods are not reliable when confronting poor illuminations, leading to degrading performances. In this paper, we propose a novel multimodal gait recognition method, namely GaitFi, which leverages WiFi signals and videos for human identification. In GaitFi, Channel State Information (CSI) that reflects the multi-path propagation of WiFi is collected to capture human gaits, while videos are captured by cameras. To learn robust gait information, we propose a Lightweight Residual Convolution Network (LRCN) as the backbone network, and further propose the two-stream GaitFi by integrating WiFi and vision features for the gait retrieval task. The GaitFi is trained by the triplet loss and classification loss on different levels of features. Extensive experiments are conducted in the real world, which demonstrates that the GaitFi outperforms state-of-the-art gait recognition methods based on single WiFi or camera, achieving 94.2% for human identification tasks of 12 subjects. | ['Lihua Xie', 'Chris Xiaoxuan Lu', 'Han Zou', 'Shenghai Yuan', 'Jianfei Yang', 'Lang Deng'] | 2022-08-30 | null | null | null | null | ['gait-recognition'] | ['computer-vision'] | [ 2.30255559e-01 -1.01788402e+00 -1.72611594e-01 -1.25573978e-01
-5.32427013e-01 -2.63453394e-01 2.21380934e-01 -5.00243545e-01
-5.16497076e-01 4.85945046e-01 7.28796124e-02 2.27543011e-01
-8.62563103e-02 -6.85921729e-01 -4.61931258e-01 -1.04642248e+00
-2.90047169e-01 -1.93983749e-01 -1.90166887e-02 2.99128264e-01
-5.63223362e-02 4.82673645e-02 -1.40400529e+00 -1.35256210e-02
4.86420780e-01 1.42601085e+00 -7.90760666e-02 5.95679164e-01
3.15721303e-01 5.78699589e-01 -5.65940320e-01 -5.31766117e-01
1.80356026e-01 -9.73043516e-02 1.08605456e-02 -2.82925427e-01
3.86601001e-01 -6.19169891e-01 -1.23070848e+00 1.01243913e+00
7.50020504e-01 8.50071833e-02 3.99759293e-01 -1.46757221e+00
-6.41980410e-01 4.01321165e-02 -7.00837672e-01 1.76372483e-01
7.33154893e-01 4.80805635e-01 4.53384697e-01 -7.99220502e-01
-1.33886084e-01 1.27482009e+00 1.12433231e+00 6.56689644e-01
-7.33368695e-01 -1.12204027e+00 -2.16516227e-01 7.94932187e-01
-1.60446799e+00 -5.82575262e-01 6.71077907e-01 -2.55884409e-01
7.56184757e-01 -6.32056501e-03 6.17988169e-01 1.58030963e+00
-2.43654270e-02 7.05231071e-01 7.19721794e-01 1.69218406e-02
-1.76936910e-01 -5.49679577e-01 1.31566972e-01 8.07923675e-01
7.77432263e-01 2.85560310e-01 -9.13090706e-01 -2.12706491e-01
7.46300638e-01 3.14292014e-01 -5.52573383e-01 7.81539977e-02
-1.36437774e+00 3.42644364e-01 3.63633007e-01 4.23160717e-02
-4.04299319e-01 5.23862422e-01 5.42464077e-01 2.60007262e-01
-7.94283524e-02 -5.52389443e-01 2.60626644e-01 -4.41183150e-01
-9.92497623e-01 -2.01023202e-02 5.53833604e-01 5.58172882e-01
5.07967293e-01 5.62167615e-02 -3.97862524e-01 7.51402974e-01
8.34370136e-01 1.49772263e+00 4.60860491e-01 -8.19837213e-01
9.53427196e-01 2.51942039e-01 1.19158663e-01 -1.52553666e+00
-2.48471543e-01 -2.79315174e-01 -1.25967228e+00 -5.70421338e-01
3.20662856e-01 -2.30310813e-01 -6.06115460e-01 1.64974272e+00
1.90841053e-02 1.12708998e+00 -1.24579184e-01 1.09691286e+00
8.24217021e-01 4.05751854e-01 5.36981318e-03 -1.84997380e-01
1.27504456e+00 -6.46362185e-01 -5.63417971e-01 -3.19569677e-01
3.02539170e-01 -5.78842461e-01 6.07033253e-01 5.49810827e-01
-5.14343083e-01 -7.22162843e-01 -1.08414924e+00 6.56197965e-01
4.88173543e-03 5.01445115e-01 5.35847247e-01 1.24044740e+00
-8.75476360e-01 4.41583127e-01 -9.39063430e-01 -4.85835135e-01
4.92395341e-01 5.68478465e-01 -5.27915359e-01 -6.45892441e-01
-1.44347823e+00 2.39602983e-01 7.73510486e-02 7.25594819e-01
-6.01649165e-01 -1.93425402e-01 -8.93039525e-01 4.84733731e-02
2.12561176e-03 -7.66039610e-01 6.49508536e-01 -3.97817045e-01
-1.33203030e+00 3.92160773e-01 -3.09184700e-01 -4.29941982e-01
3.39033276e-01 -1.72509298e-01 -9.18374717e-01 4.30208474e-01
3.04348230e-01 2.92620901e-02 1.14258814e+00 -6.94290578e-01
-4.07542616e-01 -5.20311952e-01 -3.90815407e-01 -1.62595212e-01
-7.15280175e-01 1.08650196e-02 -8.45168531e-01 -5.36933422e-01
-1.74039677e-01 -8.96791160e-01 2.06862703e-01 -2.41293088e-01
-4.21417296e-01 1.57613292e-01 1.09643364e+00 -8.71609628e-01
1.50486457e+00 -2.18081546e+00 -4.18977827e-01 4.84588742e-01
1.58920690e-01 6.00691855e-01 -2.15438604e-01 2.07925364e-01
2.62454033e-01 -3.77484620e-01 -2.36984715e-01 -5.66604614e-01
2.06841454e-01 2.85844225e-02 -6.65907636e-02 7.10764945e-01
-9.95451286e-02 8.51487458e-01 -8.00733328e-01 -4.93809462e-01
3.81987274e-01 7.88638532e-01 -3.21293682e-01 1.49315760e-01
8.23018372e-01 5.67486942e-01 -6.66400433e-01 1.01337802e+00
1.01920080e+00 -1.87723085e-01 -2.50655971e-02 -5.57931125e-01
2.28621989e-01 -4.15105134e-01 -1.20658660e+00 1.76656532e+00
-2.16106609e-01 3.51578176e-01 3.84155959e-02 -1.27298033e+00
7.23853946e-01 4.72059011e-01 8.29247296e-01 -8.97856057e-01
1.25813127e-01 2.30314687e-01 -2.81484425e-01 -6.85572386e-01
-3.66469137e-02 4.34074491e-01 -2.94870198e-01 3.46762538e-01
4.85464334e-02 1.07261407e+00 2.07072750e-01 -2.73769978e-03
1.69217408e+00 -1.88963804e-02 -2.42173702e-01 5.24149060e-01
8.69705677e-01 -5.54907203e-01 7.89578378e-01 9.77733433e-01
-7.11836636e-01 4.92170304e-01 -2.85649151e-01 -2.15068892e-01
-3.45741481e-01 -1.37887657e+00 7.14451298e-02 5.10436177e-01
2.96086162e-01 -4.38621461e-01 -6.60961151e-01 -5.32150686e-01
7.38756061e-02 -3.57844204e-01 -3.80685896e-01 -4.89407122e-01
-8.03486586e-01 -1.08985758e+00 1.27113271e+00 6.42571688e-01
1.37609494e+00 -6.08581066e-01 -5.97144961e-01 3.04079413e-01
-8.37769032e-01 -1.52056670e+00 -7.19616950e-01 -5.23852587e-01
-3.14088255e-01 -1.24760735e+00 -1.09551561e+00 -4.46882337e-01
3.01695734e-01 7.69403815e-01 4.78728831e-01 1.58742011e-01
-4.92157221e-01 9.87994850e-01 -3.24150980e-01 2.17210755e-01
5.60309231e-01 -2.49348447e-01 5.84880471e-01 7.13766932e-01
6.31630957e-01 -5.75269461e-01 -9.63406622e-01 3.43102634e-01
-4.25417274e-01 -7.14659750e-01 6.12661839e-01 1.05358136e+00
1.99834153e-01 1.83053493e-01 2.41259024e-01 -7.95312151e-02
4.16824549e-01 -6.60723686e-01 -1.02240227e-01 2.74087548e-01
-2.12978542e-01 -4.07709986e-01 6.25045359e-01 -3.14828634e-01
-1.01841378e+00 1.52388707e-01 -1.47717416e-01 -7.94006586e-01
-2.81504452e-01 5.09482682e-01 -3.97656679e-01 -5.61559439e-01
1.10256881e-01 5.36853254e-01 -1.44296959e-01 -3.36416245e-01
-7.10146651e-02 8.55681241e-01 9.58431363e-01 -4.61712241e-01
1.06644177e+00 5.35297275e-01 2.59028941e-01 -1.07040632e+00
-2.59778470e-01 -8.86543036e-01 -4.03784811e-01 -6.24706745e-01
6.87941492e-01 -1.14510393e+00 -1.30189347e+00 1.07737362e+00
-1.06388164e+00 1.02480195e-01 5.71807861e-01 8.57678294e-01
-3.72472703e-01 1.01926851e+00 -7.46884227e-01 -9.29941475e-01
-4.89511609e-01 -9.14072156e-01 1.30322385e+00 3.73539299e-01
1.75996274e-01 -7.26861358e-01 8.02281406e-03 6.57913625e-01
4.84392434e-01 1.23095348e-01 1.97462112e-01 -5.76862227e-03
-5.42770505e-01 -5.19338071e-01 -3.88453156e-01 2.77827475e-02
2.56366760e-01 -3.67276698e-01 -1.26286745e+00 -5.79122007e-01
-2.27307439e-01 -1.70963123e-01 1.07469976e+00 4.47746426e-01
8.92302215e-01 -2.87648886e-01 -7.07519233e-01 9.91177320e-01
1.29449046e+00 2.39097357e-01 8.87889266e-01 2.35124916e-01
1.09482312e+00 1.54510796e-01 4.45812941e-01 6.80992007e-01
5.79756558e-01 8.27649355e-01 1.57746062e-01 2.74926633e-01
-8.04397017e-02 -2.09771261e-01 8.47469449e-01 8.80676448e-01
-2.98127741e-01 -2.60062516e-01 -8.54912996e-01 8.87612328e-02
-2.15771294e+00 -1.42903292e+00 -1.88673556e-01 2.43128800e+00
-3.71051691e-02 -1.24860525e-01 4.33239937e-01 4.21922177e-01
9.85282004e-01 4.74094376e-02 -4.39572394e-01 4.71262246e-01
-1.21061578e-01 2.44867206e-01 7.32961595e-01 -1.35241136e-01
-1.51427031e+00 4.84069765e-01 5.38181686e+00 7.95054257e-01
-1.21360719e+00 1.54845521e-01 5.79389445e-02 -4.74324487e-02
5.08534789e-01 -4.95590866e-01 -5.95493376e-01 1.03179836e+00
1.05400002e+00 9.66434553e-02 4.20852661e-01 4.24600720e-01
4.89202827e-01 1.30974501e-01 -5.81891954e-01 1.85938358e+00
3.49214405e-01 -8.52697134e-01 -1.42958194e-01 1.74708039e-01
-3.98381315e-02 -1.53608680e-01 2.84043431e-01 2.46138856e-01
-1.86833322e-01 -9.60728109e-01 2.26071298e-01 8.47004533e-01
9.40587282e-01 -7.65989542e-01 7.97422886e-01 -3.49399000e-02
-2.00024486e+00 -4.24331844e-01 -2.07400486e-01 -2.82965810e-03
2.33116984e-01 5.96614659e-01 -6.25603124e-02 8.15219760e-01
1.08860373e+00 1.22388268e+00 -4.67020482e-01 1.51830053e+00
1.79248616e-01 1.04247427e+00 -3.49678427e-01 1.01684816e-01
-1.95333809e-02 -1.69463232e-01 4.49498653e-01 1.46195900e+00
7.45211482e-01 -7.31641948e-02 4.38725740e-01 5.89006007e-01
2.53023673e-02 -3.25893521e-01 -6.89850390e-01 1.26803011e-01
6.45403087e-01 1.15968525e+00 -4.56883520e-01 3.58237512e-03
-6.41172111e-01 1.25162458e+00 -2.55321145e-01 5.59959710e-01
-9.89151299e-01 -7.02046275e-01 8.98488045e-01 -3.22214901e-01
2.69923627e-01 -4.24350679e-01 2.85245687e-01 -1.61437035e+00
2.93722153e-01 -5.23076057e-01 3.59995753e-01 -2.56136417e-01
-1.48943496e+00 -1.89300312e-03 -3.68989617e-01 -1.61057389e+00
4.91083367e-03 -7.07375109e-01 -8.96005332e-01 6.09719336e-01
-1.31211841e+00 -1.30160761e+00 -6.65125310e-01 1.16429210e+00
-8.51563737e-02 -3.43337059e-01 6.22786462e-01 1.23652506e+00
-1.08520186e+00 1.17916226e+00 1.86803132e-01 7.48837650e-01
8.62743139e-01 -5.89380443e-01 4.80438292e-01 1.14302921e+00
-3.75612788e-02 7.97720969e-01 1.76494882e-01 -7.22387910e-01
-2.06653619e+00 -1.25890434e+00 5.05917668e-01 2.36715954e-02
4.07263279e-01 -1.52188659e-01 -6.18276596e-01 2.20243990e-01
-2.25144416e-01 3.42896312e-01 7.99046695e-01 -4.04968947e-01
-4.21373159e-01 -3.82760644e-01 -1.09514892e+00 1.45797580e-01
1.37698424e+00 -6.42978132e-01 -1.18941829e-01 -8.89613256e-02
4.81073260e-02 1.26759678e-01 -7.84539104e-01 3.38535339e-01
9.63741124e-01 -7.43796527e-01 1.46166670e+00 -7.25716650e-02
-2.91585565e-01 -5.42299569e-01 -3.11118513e-01 -1.06976855e+00
-4.96123940e-01 -4.69938785e-01 -4.93877888e-01 1.34845734e+00
-4.68745172e-01 -6.90345347e-01 9.50694561e-01 2.24482477e-01
2.10760355e-01 -6.65254295e-02 -1.25985682e+00 -1.11891770e+00
-5.28216541e-01 -6.65362000e-01 5.77540219e-01 6.85962439e-01
-3.59306484e-02 -1.39991567e-02 -8.83480012e-01 2.93236852e-01
1.42403460e+00 -3.28155398e-01 6.55645192e-01 -1.21750629e+00
-3.49284798e-01 -2.25853339e-01 -1.08430994e+00 -9.96005237e-01
2.29077563e-01 -5.88108242e-01 3.27772759e-02 -1.20786142e+00
1.81651875e-01 -1.27438933e-01 -6.04205728e-01 3.27943206e-01
-7.73572102e-02 6.33449674e-01 1.12924367e-01 3.85296822e-01
-8.11616302e-01 6.00829065e-01 6.39349282e-01 -6.48790717e-01
3.26220393e-01 -1.06451577e-02 -2.38647446e-01 6.62528098e-01
5.65120757e-01 -3.48788872e-02 -1.87913924e-01 -5.01051545e-01
-3.01110327e-01 1.53188422e-01 9.15116251e-01 -1.84170544e+00
6.22789264e-01 1.22671403e-01 8.58100176e-01 -2.99888670e-01
6.75376832e-01 -7.33191252e-01 1.78002462e-01 6.48389697e-01
2.88839757e-01 3.35594639e-02 -8.61938521e-02 9.54748273e-01
-2.30341777e-01 3.43014479e-01 2.74175078e-01 6.18147030e-02
-9.63437140e-01 7.23276436e-01 -4.75644648e-01 -1.00084737e-01
6.08856440e-01 -4.67806995e-01 -4.93993193e-01 -3.10751855e-01
-4.37137365e-01 1.22650996e-01 1.04249984e-01 3.12063158e-01
1.03800476e+00 -1.83713996e+00 -5.55661619e-01 3.83287907e-01
2.07812220e-01 -9.31271911e-01 5.39522350e-01 1.08861101e+00
-1.29295290e-01 5.53566337e-01 -3.23504150e-01 -6.90584540e-01
-1.18981934e+00 1.77107006e-01 3.01445156e-01 -3.78770567e-03
-5.13027132e-01 5.98437786e-01 -2.56859988e-01 -1.22756161e-01
4.90715563e-01 3.19306701e-01 -2.05459490e-01 -8.08289871e-02
8.74217093e-01 7.74265468e-01 1.32972360e-01 -1.08964515e+00
-7.53765225e-01 1.00650883e+00 3.11590970e-01 2.33102068e-02
8.43065917e-01 -4.81943935e-01 2.69705504e-01 -3.03915478e-02
1.27165806e+00 -4.22769994e-01 -1.10199368e+00 -3.03032666e-01
-2.35998556e-01 -8.12958717e-01 -1.80790454e-01 -4.02560949e-01
-1.36795545e+00 1.02650917e+00 1.19240952e+00 -3.40893388e-01
1.14859390e+00 -8.06128860e-01 1.48553240e+00 7.36102223e-01
1.03226304e+00 -8.89029086e-01 1.85357645e-01 4.59667563e-01
6.49582446e-02 -1.15679383e+00 -4.69238579e-01 -2.70672798e-01
-2.22791210e-01 1.10677743e+00 5.23835957e-01 1.66927148e-02
6.49038196e-01 1.45746693e-01 -1.19819805e-01 1.79935828e-01
-2.70850748e-01 -3.48822176e-01 8.79005939e-02 1.10779417e+00
1.56950980e-01 6.12507761e-02 1.95245445e-01 8.79707396e-01
2.10301176e-01 3.71830136e-01 6.38711452e-02 8.59322309e-01
-2.61939019e-01 -9.51998353e-01 -8.13651741e-01 7.80752599e-01
-3.55115414e-01 3.46237011e-02 -1.70489967e-01 1.24330789e-01
2.90544599e-01 1.44487166e+00 -3.53771091e-01 -1.07003987e+00
2.49375999e-01 -1.35910898e-01 5.72977066e-01 1.14399083e-02
-2.17926115e-01 -2.14852959e-01 -8.07727128e-02 -9.24664497e-01
-5.83378673e-01 -7.34102428e-01 -9.12723184e-01 -6.61753595e-01
-4.58747568e-03 3.16129178e-02 1.63312569e-01 1.01510274e+00
3.06550294e-01 1.46934688e-01 7.80312777e-01 -1.00556982e+00
-2.75166512e-01 -3.94629866e-01 -7.57370770e-01 4.42738920e-01
4.02816594e-01 -1.11930597e+00 -1.87124282e-01 4.76129912e-02] | [14.252493858337402, 1.460525631904602] |
707c2383-90ce-4279-86fa-52583b6cf785 | learning-to-factorize-and-relight-a-city | 2008.02796 | null | https://arxiv.org/abs/2008.02796v1 | https://arxiv.org/pdf/2008.02796v1.pdf | Learning to Factorize and Relight a City | We propose a learning-based framework for disentangling outdoor scenes into temporally-varying illumination and permanent scene factors. Inspired by the classic intrinsic image decomposition, our learning signal builds upon two insights: 1) combining the disentangled factors should reconstruct the original image, and 2) the permanent factors should stay constant across multiple temporal samples of the same scene. To facilitate training, we assemble a city-scale dataset of outdoor timelapse imagery from Google Street View, where the same locations are captured repeatedly through time. This data represents an unprecedented scale of spatio-temporal outdoor imagery. We show that our learned disentangled factors can be used to manipulate novel images in realistic ways, such as changing lighting effects and scene geometry. Please visit factorize-a-city.github.io for animated results. | ['Tinghui Zhou', 'Alexei A. Efros', 'Andrew Liu', 'Shiry Ginosar', 'Noah Snavely'] | 2020-08-06 | null | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/2473_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123490528.pdf | eccv-2020-8 | ['intrinsic-image-decomposition'] | ['computer-vision'] | [ 1.90157339e-01 -5.09342670e-01 -3.87327932e-02 -1.53541937e-01
-6.57857120e-01 -1.18676376e+00 5.44692099e-01 -6.14831030e-01
-1.17308728e-01 6.05862021e-01 4.94839907e-01 -1.91241220e-01
-3.59037906e-01 -5.62074780e-01 -8.93171430e-01 -8.75843048e-01
-3.22438449e-01 -3.21426541e-01 -1.73307076e-01 -2.80745663e-02
-1.58897445e-01 5.49581647e-01 -1.53707635e+00 2.79550135e-01
6.23275220e-01 3.83782238e-01 3.74096841e-01 1.14246440e+00
6.75801218e-01 6.91925883e-01 -2.69269943e-01 -9.12304036e-03
7.41793633e-01 -3.19266409e-01 -2.24110916e-01 4.74627733e-01
8.15707982e-01 -6.03875279e-01 -1.11762106e+00 6.97074533e-01
8.59809071e-02 2.50899076e-01 1.48808882e-01 -1.21496511e+00
-8.87072802e-01 -9.12626833e-03 -6.36221588e-01 2.43946031e-01
5.05489409e-01 5.53470075e-01 8.60896707e-01 -6.57571137e-01
5.94673038e-01 1.05054069e+00 3.23048979e-01 1.07094564e-01
-1.83662629e+00 -7.86658704e-01 4.85927761e-01 2.45763231e-02
-1.30933821e+00 -6.68799818e-01 7.07514584e-01 -5.65744877e-01
5.99027336e-01 5.80372930e-01 9.24197674e-01 1.57772422e+00
1.01726659e-01 6.29112959e-01 1.47643685e+00 -1.08370349e-01
-1.00350767e-01 -9.40765291e-02 -4.02258277e-01 5.58509946e-01
3.16192180e-01 4.60039496e-01 -7.64186323e-01 1.04021681e-02
9.69369709e-01 2.77797937e-01 -4.75793391e-01 -4.98699456e-01
-1.73351347e+00 5.42996287e-01 5.14245987e-01 2.99768057e-02
-7.97469094e-02 3.93544257e-01 -1.46857515e-01 2.14239761e-01
3.17785859e-01 5.02887726e-01 -6.68539464e-01 2.47110631e-02
-7.55941331e-01 3.32663268e-01 3.26507628e-01 8.98483276e-01
9.00624216e-01 1.77095920e-01 2.46438101e-01 3.54921520e-01
9.99851376e-02 1.15138030e+00 5.19666336e-02 -1.40967679e+00
3.81704926e-01 2.88926922e-02 3.69203955e-01 -1.26095724e+00
-1.89251095e-01 -1.72504857e-01 -8.34174037e-01 1.87028855e-01
5.80238998e-01 -2.03080043e-01 -7.95710623e-01 2.00881505e+00
1.71212643e-01 6.87951744e-01 -2.56150901e-01 7.34974682e-01
5.51478505e-01 6.55904233e-01 -4.30310071e-01 -2.05008239e-02
1.19634044e+00 -7.69551694e-01 -7.33933747e-01 -3.50029886e-01
7.99193382e-02 -5.89453161e-01 1.17781961e+00 4.89425033e-01
-7.69056439e-01 -5.98392010e-01 -9.82544124e-01 -1.78687111e-01
-4.19754207e-01 2.02558130e-01 9.34647143e-01 3.80350173e-01
-9.85902131e-01 2.18740419e-01 -9.58828330e-01 -3.97653908e-01
2.80448139e-01 1.37440842e-02 -7.29879916e-01 -2.81287342e-01
-8.84539664e-01 3.69547695e-01 -1.39877722e-01 3.02208103e-02
-1.31854153e+00 -9.58988667e-01 -8.76988471e-01 -7.14440197e-02
3.84150863e-01 -9.12335098e-01 7.82813132e-01 -6.87153161e-01
-1.25193763e+00 8.90861154e-01 -3.64973009e-01 -7.61629269e-03
3.96471560e-01 -4.58488107e-01 -6.06586099e-01 2.37064913e-01
3.14818561e-01 3.91180545e-01 1.19141185e+00 -1.61046243e+00
-1.64333180e-01 -4.99644339e-01 4.22477365e-01 1.53843135e-01
-3.50189991e-02 -4.01728392e-01 -3.41726482e-01 -7.90220559e-01
2.96816915e-01 -1.11520863e+00 -3.11737746e-01 3.77042502e-01
-4.00290817e-01 9.12329376e-01 7.92540073e-01 -7.09715068e-01
9.23582554e-01 -2.50482392e+00 4.46221769e-01 -1.75641149e-01
6.32559836e-01 -3.50556701e-01 -2.67532527e-01 4.90689427e-01
-4.98504102e-01 2.26799190e-01 2.65023652e-02 -4.82310355e-01
-1.57631099e-01 2.71985292e-01 -6.65552258e-01 7.87912250e-01
-8.60761702e-02 9.70649421e-01 -1.17827773e+00 9.74996015e-03
4.71085399e-01 3.98371845e-01 -6.77624345e-01 2.30405197e-01
4.30776458e-03 1.19505179e+00 -2.92234600e-01 3.71618688e-01
9.02178884e-01 -2.86198765e-01 2.02719510e-01 -3.02536458e-01
-2.14194432e-01 1.19516961e-01 -1.04844701e+00 2.15685344e+00
-5.98454356e-01 1.02312493e+00 1.64446592e-01 -4.58539456e-01
4.43288177e-01 9.09762010e-02 6.31892085e-01 -6.66320920e-01
-2.07943708e-01 -2.99483538e-01 -3.71769637e-01 -7.45016575e-01
4.57025528e-01 -1.00604162e-01 -2.02119961e-01 5.60019016e-01
-1.91260371e-02 -4.55325276e-01 -7.88911209e-02 5.21037996e-01
1.07012081e+00 3.35911274e-01 1.30977839e-01 -1.52910054e-01
7.47713000e-02 -2.63960034e-01 5.06308317e-01 7.28627026e-01
-3.38872999e-01 6.87170982e-01 3.59582096e-01 -7.18436539e-01
-1.04042947e+00 -1.67751026e+00 -2.41190363e-02 8.37487340e-01
1.64748698e-01 -5.16020298e-01 -2.71148145e-01 -3.20321143e-01
-2.41447054e-02 5.44471443e-01 -9.17194843e-01 3.64772417e-02
-3.12505126e-01 -5.78606963e-01 4.56012726e-01 9.51603204e-02
6.32496357e-01 -2.11009249e-01 -5.12084484e-01 -3.74272823e-01
-5.53684413e-01 -1.43624592e+00 -5.46681404e-01 -3.59090827e-02
-6.42079949e-01 -1.02941835e+00 -3.37994456e-01 -1.54882744e-01
7.13245869e-01 1.22863376e+00 1.19844115e+00 -1.54065445e-01
-3.57537836e-01 6.73140943e-01 -1.98472813e-01 4.91529517e-02
2.07082823e-01 -3.21051359e-01 3.11394274e-01 3.18590760e-01
2.68317410e-03 -1.31888497e+00 -7.47287095e-01 3.58386040e-01
-1.00210929e+00 5.22742748e-01 4.40897718e-02 6.14034534e-01
4.46095645e-01 1.35534182e-01 -2.28595778e-01 -5.50857425e-01
1.69488177e-01 -5.15368760e-01 -7.59279907e-01 1.30840465e-01
1.24531090e-01 -8.81267041e-02 5.56619465e-01 -5.59786916e-01
-1.06737006e+00 7.94444233e-02 5.21137536e-01 -6.43115699e-01
-3.41661453e-01 1.48928404e-01 -4.47673708e-01 1.07490811e-02
7.80197263e-01 2.52473563e-01 -4.29110765e-01 -3.41977566e-01
8.66432905e-01 1.78253174e-01 5.93426406e-01 -8.11554492e-01
1.29461992e+00 1.28310275e+00 -7.32494295e-02 -7.60305345e-01
-1.01486945e+00 -2.65575469e-01 -8.77544403e-01 -2.53469646e-01
9.95042443e-01 -1.46619773e+00 -7.84324646e-01 4.04123127e-01
-7.96535969e-01 -7.23213732e-01 -3.93764079e-01 5.37493289e-01
-6.75272167e-01 9.19411331e-02 -2.67514050e-01 -3.49914610e-01
7.29880631e-01 -1.01828170e+00 1.34084702e+00 2.67895967e-01
-5.59962243e-02 -9.50352073e-01 3.96729708e-01 4.33357775e-01
9.82683972e-02 6.79064333e-01 4.63552207e-01 4.28530753e-01
-1.12654972e+00 4.39205170e-02 -1.98868394e-01 6.07698373e-02
5.96646249e-01 1.88131496e-01 -1.26216972e+00 -4.21239495e-01
2.29096279e-01 -2.66039044e-01 8.16842735e-01 3.21514130e-01
1.10652614e+00 -4.30079967e-01 -2.11965397e-01 1.39957464e+00
1.51300931e+00 -2.24545360e-01 7.03256965e-01 2.79983521e-01
9.90823388e-01 3.53560388e-01 1.53009966e-01 5.75845540e-01
5.52507699e-01 6.42617881e-01 2.90302962e-01 -2.29907483e-01
-1.56285807e-01 -6.60745323e-01 3.91371191e-01 7.55346954e-01
-1.57707393e-01 -2.92531997e-01 -6.50030315e-01 5.72032690e-01
-1.72459197e+00 -1.32134652e+00 -4.15741988e-02 2.28840303e+00
3.27426553e-01 -2.03222841e-01 -1.62574217e-01 -1.68808371e-01
2.01920435e-01 8.81670475e-01 -8.66006017e-01 1.73544496e-01
-6.26189351e-01 -1.41809911e-01 6.94693804e-01 7.44188964e-01
-1.07157660e+00 7.98516750e-01 6.89661598e+00 3.65148365e-01
-1.14357758e+00 2.21846789e-01 4.55238879e-01 -6.96319044e-01
-7.70724237e-01 3.91098380e-01 -1.80120736e-01 3.56689215e-01
5.79166174e-01 -1.81313992e-01 1.17339623e+00 3.06939662e-01
6.94013119e-01 -2.06105113e-01 -9.36593294e-01 1.13818884e+00
-8.11268911e-02 -1.17669058e+00 -1.37378704e-02 2.98726082e-01
1.05114043e+00 8.87999684e-02 5.43524742e-01 -6.77027106e-02
6.53536618e-01 -9.94333148e-01 6.56976163e-01 8.01339626e-01
9.31868434e-01 -3.21266413e-01 -3.44574511e-01 3.54880691e-01
-1.23147333e+00 -6.82660192e-02 -4.77152504e-03 -3.84511322e-01
2.89106637e-01 5.90146363e-01 3.01000327e-02 5.76216400e-01
8.75479817e-01 1.28656292e+00 -7.65359402e-01 4.48824644e-01
-6.19545877e-01 4.07768399e-01 -3.38548928e-01 6.87700093e-01
-1.26443192e-01 -5.38317978e-01 7.77393222e-01 8.58070374e-01
1.54824778e-01 4.11247671e-01 1.33186008e-03 9.72845614e-01
1.08304046e-01 -7.44139433e-01 -1.16858840e+00 -4.50865328e-02
2.49605820e-01 1.25904083e+00 -4.59042192e-01 -1.90459326e-01
-4.69307959e-01 1.31966853e+00 2.12752864e-01 1.08131111e+00
-1.08242047e+00 2.66272277e-01 1.42791688e+00 4.78699319e-02
3.68351817e-01 -1.08938694e+00 -2.59455770e-01 -2.00585127e+00
1.61807630e-02 -9.53084588e-01 4.31179581e-03 -1.32867086e+00
-1.05728865e+00 3.37549180e-01 2.34936073e-01 -1.48480809e+00
2.75149405e-01 -5.52291691e-01 -3.25039625e-01 6.90908551e-01
-1.25084436e+00 -1.36287570e+00 -6.70714140e-01 9.93944347e-01
4.77811009e-01 2.16629207e-01 9.31884408e-01 2.04829857e-01
-7.12905169e-01 2.04211101e-01 2.58891702e-01 -7.66547471e-02
7.53774524e-01 -1.08995759e+00 5.37097692e-01 1.38283944e+00
6.12763643e-01 8.78748596e-01 7.71684766e-01 -3.14267159e-01
-1.68767226e+00 -8.01549554e-01 3.05493534e-01 -1.03175008e+00
9.15620685e-01 -8.53312552e-01 -3.78951997e-01 1.10854626e+00
2.69018114e-01 3.85326028e-01 9.30713296e-01 2.19614133e-02
-9.57648218e-01 -2.12172866e-01 -8.95527244e-01 9.77941811e-01
1.42998409e+00 -9.74051178e-01 -1.36009946e-01 4.90937740e-01
1.07755065e+00 -4.86405015e-01 -6.48778796e-01 2.15274468e-01
8.95595014e-01 -1.32138324e+00 1.26710534e+00 -7.23149598e-01
4.87410396e-01 -5.57597458e-01 -7.23959267e-01 -1.41490948e+00
-7.09385037e-01 -8.66110504e-01 -3.02359134e-01 6.55273974e-01
1.24534309e-01 -8.45341802e-01 4.25661415e-01 6.71468973e-01
3.32656175e-01 -2.92316198e-01 -6.53404117e-01 -7.44415820e-01
-2.07235545e-01 -5.30734539e-01 7.22374618e-01 1.11104262e+00
-4.71905380e-01 1.75084844e-01 -8.03665340e-01 7.44629681e-01
7.53348410e-01 3.67437571e-01 1.16899931e+00 -6.94692492e-01
-7.84479499e-01 -1.60968192e-02 -2.88771302e-01 -1.39071631e+00
-6.00869358e-02 -4.28288221e-01 -2.75570601e-01 -1.13573837e+00
2.57902771e-01 -2.67368913e-01 -1.10041879e-01 3.52059960e-01
-2.49253780e-01 3.71922642e-01 4.16997552e-01 2.44880840e-01
-4.17471290e-01 7.46240258e-01 1.53263760e+00 -2.98299044e-02
-4.88854460e-02 -3.61753345e-01 -8.73907745e-01 5.36402285e-01
6.06288731e-01 -4.90675151e-01 -6.58648372e-01 -9.73010123e-01
5.02015233e-01 7.85243958e-02 6.68258131e-01 -8.10056388e-01
-6.29110187e-02 -6.43950582e-01 4.40178096e-01 -2.10373223e-01
6.02367043e-01 -1.00983906e+00 6.37964785e-01 7.22756460e-02
-2.59628473e-03 1.39715120e-01 4.93460894e-01 7.84059823e-01
-1.15919979e-02 6.11675620e-01 3.73841792e-01 -3.40913385e-01
-5.41477621e-01 4.70216036e-01 -4.00379449e-01 -8.89445245e-02
9.15761650e-01 -3.28208238e-01 -4.77959394e-01 -6.60824358e-01
-7.99311936e-01 2.24759094e-02 8.96420598e-01 5.60334325e-01
4.16696280e-01 -1.29452205e+00 -5.75039744e-01 4.47016567e-01
1.73314527e-01 -7.06409588e-02 7.27245390e-01 7.95782208e-01
-5.60131192e-01 1.44354269e-01 -1.89548850e-01 -6.79498792e-01
-9.86394703e-01 7.71842420e-01 2.84458518e-01 -1.41437888e-01
-5.09156346e-01 7.40402400e-01 6.80923939e-01 -5.90658188e-01
-3.97617608e-01 -3.10615122e-01 4.93388355e-01 -1.61667347e-01
6.54606044e-01 1.70839444e-01 -4.93670404e-01 -6.88069165e-01
-2.12570012e-01 7.74205148e-01 4.77489114e-01 -4.82953221e-01
1.44332504e+00 -7.02912271e-01 -7.33581334e-02 8.18522036e-01
1.33764100e+00 6.41283870e-01 -1.85429668e+00 -1.88501999e-01
-7.80365646e-01 -1.18766499e+00 -8.01930875e-02 -6.23464584e-01
-1.09048951e+00 6.99936390e-01 5.05508125e-01 1.34256527e-01
1.48912704e+00 -1.68609962e-01 3.45341295e-01 1.48672268e-01
6.71861529e-01 -2.76192218e-01 2.79956877e-01 2.58877903e-01
9.68623936e-01 -1.23008013e+00 3.44716102e-01 -3.60819817e-01
-4.17003900e-01 7.91552067e-01 3.14446598e-01 -4.17061180e-01
8.49500179e-01 3.98374915e-01 2.32538804e-02 -3.01571071e-01
-7.64238179e-01 -1.89419195e-01 2.57468849e-01 7.01510966e-01
-9.61560756e-02 3.87230366e-01 4.97574955e-01 1.49742007e-01
-3.82983208e-01 -1.91146627e-01 5.83586931e-01 6.70168936e-01
2.37549558e-01 -7.79728472e-01 -4.48670447e-01 6.61424547e-02
1.05610192e-01 1.02742538e-02 -2.33559266e-01 7.10333765e-01
3.89113843e-01 9.24490988e-01 -1.22605823e-01 -6.06762409e-01
1.79970622e-01 -4.32242721e-01 7.96459854e-01 -5.13872445e-01
1.73562393e-01 -7.55956098e-02 -1.07992426e-01 -1.13035715e+00
-6.92570269e-01 -7.71188617e-01 -4.36921179e-01 -3.91885042e-01
9.55316126e-02 -3.05340856e-01 5.20474553e-01 7.06684589e-01
5.14038503e-01 5.31069636e-01 9.03912842e-01 -1.28084469e+00
3.61594468e-01 -6.41752064e-01 -6.56927407e-01 4.82703358e-01
1.01475036e+00 -6.18178844e-01 -7.98744380e-01 5.62239885e-01] | [9.343363761901855, -3.052455186843872] |
9eddd23c-73ac-462e-b427-2b6345dde52e | rapid-randomized-restarts-for-multi-agent | 1706.02794 | null | http://arxiv.org/abs/1706.02794v1 | http://arxiv.org/pdf/1706.02794v1.pdf | Rapid Randomized Restarts for Multi-Agent Path Finding Solvers | Multi-Agent Path Finding (MAPF) is an NP-hard problem well studied in
artificial intelligence and robotics. It has many real-world applications for
which existing MAPF solvers use various heuristics. However, these solvers are
deterministic and perform poorly on "hard" instances typically characterized by
many agents interfering with each other in a small region. In this paper, we
enhance MAPF solvers with randomization and observe that they exhibit
heavy-tailed distributions of runtimes on hard instances. This leads us to
develop simple rapid randomized restart (RRR) strategies with the intuition
that, given a hard instance, multiple short runs have a better chance of
solving it compared to one long run. We validate this intuition through
experiments and show that our RRR strategies indeed boost the performance of
state-of-the-art MAPF solvers such as iECBS and M*. | ['Glenn Wagner', 'Sven Koenig', 'Liron Cohen', 'T. K. Satish Kumar', 'Howie Choset'] | 2017-06-08 | null | null | null | null | ['multi-agent-path-finding'] | ['playing-games'] | [-1.47146344e-01 4.84596163e-01 -2.17532635e-01 -1.79106556e-02
-5.33990800e-01 -9.61546779e-01 4.99596655e-01 2.84178823e-01
-3.59963328e-01 1.29145181e+00 -2.45791391e-01 -6.33078098e-01
-7.61229694e-01 -1.13642609e+00 -1.17113912e+00 -6.13883913e-01
-6.43487692e-01 1.28073168e+00 5.61812758e-01 -4.40401495e-01
2.19088525e-01 1.45585552e-01 -1.16668713e+00 -1.12762406e-01
8.11826766e-01 3.20052177e-01 2.55438626e-01 5.62744915e-01
8.65347758e-02 5.76703668e-01 -5.90773046e-01 -1.03720330e-01
5.20184457e-01 -3.20363671e-01 -1.15612757e+00 -1.56381384e-01
-3.17744732e-01 -5.68416752e-02 -3.77632499e-01 1.07184422e+00
1.10554464e-01 3.47976238e-01 2.57291347e-01 -1.98530793e+00
-1.36408582e-01 1.20725501e+00 -9.26282942e-01 4.27083299e-02
6.44662380e-01 1.88688949e-01 9.87948239e-01 3.42285372e-02
9.21816051e-01 1.30077302e+00 3.73760581e-01 3.74027610e-01
-1.11278880e+00 -3.71888250e-01 5.10876536e-01 4.82756525e-01
-1.25321817e+00 8.12666640e-02 2.36218244e-01 8.01938772e-02
1.22395957e+00 4.62356180e-01 6.60960674e-01 6.57589138e-01
1.77224159e-01 7.16300368e-01 1.42516828e+00 -2.15535492e-01
5.67744136e-01 -1.78984687e-01 1.22052528e-01 5.10488868e-01
6.53871715e-01 3.70912462e-01 -2.48161122e-01 -1.78481549e-01
4.94923621e-01 -4.15992349e-01 -2.82133728e-01 -3.78047585e-01
-1.23003054e+00 1.13556838e+00 3.55021328e-01 -4.33038771e-02
-2.73502052e-01 3.68698865e-01 2.58876503e-01 3.48810822e-01
-1.38848260e-01 7.28627920e-01 -4.48094577e-01 -3.05824250e-01
-2.94782132e-01 8.51145029e-01 1.22486866e+00 1.04399002e+00
7.21261919e-01 -6.31022513e-01 2.37716243e-01 3.74322981e-01
-8.61132219e-02 3.58089626e-01 -2.24882632e-01 -1.22594130e+00
6.47645175e-01 3.98118645e-01 5.43544471e-01 -8.51139426e-01
-8.56339276e-01 -2.30272606e-01 -3.35746646e-01 4.77097034e-01
6.36456072e-01 -2.68685639e-01 -6.57907546e-01 1.83087397e+00
5.12098849e-01 2.64721990e-01 1.94722682e-01 1.03088105e+00
2.25228235e-01 1.03957033e+00 -4.13649380e-01 -4.05947000e-01
1.14440060e+00 -1.41007531e+00 -4.15932536e-01 -6.11563921e-01
5.82753718e-01 -3.86023730e-01 6.17147565e-01 5.68487644e-01
-1.25871301e+00 3.66961151e-01 -1.12191606e+00 3.24571341e-01
-3.82351846e-01 -7.92337239e-01 1.10473490e+00 5.10146022e-01
-1.00047028e+00 4.56638664e-01 -9.74308670e-01 -4.48094338e-01
2.13668361e-01 4.86004114e-01 -3.35880160e-01 -5.82895100e-01
-7.92628765e-01 1.17705572e+00 3.73562008e-01 -1.52108282e-01
-9.73862469e-01 -4.91080105e-01 -5.37991941e-01 -9.44994390e-03
1.26639473e+00 -7.78801858e-01 1.41267538e+00 -5.11684299e-01
-1.56893349e+00 5.42057872e-01 -2.67345637e-01 -7.06234038e-01
7.14746773e-01 1.53496534e-01 8.24977010e-02 2.24105064e-02
3.58620137e-01 5.13980865e-01 2.31837288e-01 -1.26332021e+00
-8.35992098e-01 -2.61202514e-01 7.59326637e-01 2.08370388e-01
3.36272240e-01 -5.97335119e-03 -2.37092480e-01 1.30981252e-01
4.07786109e-02 -1.25440276e+00 -9.95799482e-01 -4.86287266e-01
-5.61196566e-01 -2.85738617e-01 3.57683033e-01 1.91516295e-01
9.35784221e-01 -1.52640069e+00 3.78622711e-01 6.47193611e-01
1.34938762e-01 -1.46809861e-01 -5.69283426e-01 7.85665810e-01
1.78295150e-01 2.01209798e-01 -5.07357456e-02 1.74777940e-01
4.91716564e-01 7.58571267e-01 -1.31541034e-02 6.61769211e-01
-2.28837460e-01 8.42038214e-01 -1.16946244e+00 -1.85998753e-01
2.90165786e-02 -3.40139478e-01 -7.20376611e-01 -6.73297793e-02
-6.64515615e-01 1.49324164e-01 -4.36823815e-01 3.44036937e-01
8.95435870e-01 -3.24286878e-01 5.39124608e-01 5.51924706e-01
-3.58043373e-01 2.86026210e-01 -1.47972059e+00 1.44624114e+00
-7.86565915e-02 2.77578473e-01 2.62614876e-01 -8.92021596e-01
2.92148888e-01 -1.18563622e-01 5.24306774e-01 -9.03458834e-01
1.28859475e-01 2.09289610e-01 2.44663417e-01 -2.77615756e-01
4.81669962e-01 6.96108043e-02 -1.73665985e-01 7.53604650e-01
-5.88042319e-01 -1.78565741e-01 8.70751143e-01 2.30208084e-01
1.86794960e+00 -1.73588768e-01 1.31625816e-01 -3.01006258e-01
2.04024568e-01 6.06066108e-01 7.59457290e-01 1.22462809e+00
-1.40739977e-01 1.47126615e-01 8.37177575e-01 -6.08308136e-01
-8.74096692e-01 -8.37289512e-01 2.20652774e-01 9.03157115e-01
8.18365157e-01 -6.62960172e-01 -6.96501791e-01 -5.09647071e-01
5.05208150e-02 6.45453215e-01 -6.55178308e-01 1.00307889e-01
-6.95805013e-01 -1.02425444e+00 2.60893375e-01 2.10245386e-01
1.78621709e-01 -9.02002454e-01 -8.66213739e-01 5.77617168e-01
-2.49085218e-01 -1.32096195e+00 1.56387538e-02 4.52529997e-01
-3.71211886e-01 -1.41272831e+00 -3.22981030e-01 -6.45382166e-01
8.17620337e-01 7.39728034e-01 1.15179801e+00 1.65365562e-01
-1.81689993e-01 1.31104486e-02 -5.90054333e-01 -4.44319725e-01
-3.05593550e-01 2.58191258e-01 -1.02027893e-01 -8.39420855e-01
-6.38813302e-02 -5.35798967e-01 -3.53411138e-01 6.18431687e-01
-6.80516005e-01 -1.38074355e-02 4.11011308e-01 6.30394995e-01
5.85803688e-01 7.42437482e-01 4.54906106e-01 -7.66762376e-01
8.11229229e-01 -7.36184239e-01 -1.20684540e+00 2.80189455e-01
-5.18692970e-01 -5.52939810e-02 6.17823243e-01 -3.36891860e-01
-4.73924905e-01 -4.05944213e-02 2.66771466e-01 4.04357091e-02
8.55225325e-02 7.89423287e-01 1.66726679e-01 -2.19329491e-01
4.46126282e-01 -1.57339782e-01 -2.76009142e-02 1.88436404e-01
3.13073903e-01 -1.93028953e-02 4.79403943e-01 -1.11771238e+00
8.86757970e-01 3.28421414e-01 3.59396070e-01 -2.36552998e-01
-7.90113688e-01 -2.96669126e-01 3.16887736e-01 -1.56825379e-01
4.95361328e-01 -5.31542718e-01 -1.34892368e+00 1.58977628e-01
-9.88564968e-01 -8.09749484e-01 -9.89561826e-02 9.15109068e-02
-9.22304153e-01 5.69908805e-02 -4.10148144e-01 -9.94282484e-01
2.27819383e-01 -1.31092060e+00 6.20795131e-01 5.37912309e-01
-9.65610817e-02 -5.75198948e-01 4.57014829e-01 1.73517331e-01
2.89197028e-01 3.54557335e-01 8.22702229e-01 -4.92911458e-01
-8.84821415e-01 1.20598502e-01 -1.76032364e-01 -7.27429211e-01
-2.91810870e-01 -3.35868448e-02 -2.82705128e-01 -4.41444188e-01
-5.70560813e-01 -1.36077255e-01 4.08995271e-01 5.80199122e-01
8.24983895e-01 -5.89084566e-01 -7.83005834e-01 2.83526838e-01
1.67714918e+00 2.65457749e-01 7.91587770e-01 1.20091736e+00
-3.83173898e-02 5.65363228e-01 1.03271103e+00 5.87066591e-01
8.46553683e-01 6.43384933e-01 9.26183879e-01 1.55867130e-01
5.46174049e-01 1.95087805e-01 2.41157398e-01 -2.34886333e-02
-2.07790792e-01 -6.09179080e-01 -1.07426119e+00 7.65229344e-01
-2.57582879e+00 -8.86566103e-01 -2.74874061e-01 2.05695796e+00
6.74753070e-01 3.92211735e-01 5.43036640e-01 1.46457523e-01
7.49226093e-01 -2.71535635e-01 -4.74955440e-01 -6.48738742e-01
-2.59021968e-01 3.12611550e-01 1.02129602e+00 6.27896190e-01
-9.32866454e-01 1.05420327e+00 6.53688383e+00 5.22699296e-01
-5.49019754e-01 -9.24804062e-02 1.95100531e-01 -2.44779050e-01
-1.41117364e-01 2.21915528e-01 -4.87651527e-01 3.39292556e-01
9.48503613e-01 -6.48320079e-01 1.20772326e+00 8.23755920e-01
2.42961451e-01 -5.61404347e-01 -1.15371454e+00 5.19544423e-01
-4.67725903e-01 -1.51977885e+00 -5.69913208e-01 3.96577060e-01
1.02150798e+00 2.93021023e-01 -2.56615371e-01 2.18853369e-01
1.22525179e+00 -1.16869676e+00 7.31316864e-01 -1.66959092e-01
-2.08213463e-01 -1.03782368e+00 8.13690960e-01 5.26883304e-01
-9.57397461e-01 -4.78251964e-01 -4.71723199e-01 -4.18162793e-01
5.64456403e-01 4.18287188e-01 -8.24477792e-01 7.94769287e-01
7.90963471e-01 5.94279878e-02 -1.09661758e-01 1.69269133e+00
-3.77708644e-01 1.86495274e-01 -8.11706185e-01 -1.86218247e-01
6.98891401e-01 -3.87870997e-01 8.29789340e-01 7.06717312e-01
2.06719860e-01 3.15199494e-01 5.05607247e-01 7.65936434e-01
3.70884925e-01 -2.82092810e-01 -4.90320474e-01 -5.09915873e-02
5.94845653e-01 1.10663593e+00 -1.04617012e+00 -4.60696518e-02
-1.03502393e-01 4.66333717e-01 4.26788241e-01 2.08300173e-01
-1.35346937e+00 -2.39094302e-01 8.30436826e-01 -4.73613068e-02
3.39992464e-01 -3.96336585e-01 -4.55395103e-01 -7.07310438e-01
1.12442635e-01 -9.18432534e-01 4.72260058e-01 -6.58638597e-01
-1.00181985e+00 4.62090194e-01 1.74030159e-02 -8.38615835e-01
-2.36085117e-01 -4.08481896e-01 -6.82705581e-01 2.60763019e-01
-1.79118967e+00 -8.09087634e-01 -3.06043863e-01 4.90959048e-01
3.01065594e-01 3.12374324e-01 7.52383173e-01 9.90637988e-02
-8.51024508e-01 3.63855034e-01 -3.12545747e-02 -4.55015093e-01
1.83861822e-01 -1.32564330e+00 4.29724246e-01 9.19423819e-01
-2.70091891e-01 4.51211810e-01 1.17644227e+00 -5.10029733e-01
-2.02387881e+00 -8.70541990e-01 3.23891580e-01 -8.66137147e-02
8.74666989e-01 2.25218553e-02 -2.71792501e-01 9.78210628e-01
2.22846195e-01 -1.07311599e-01 4.13318053e-02 1.95094362e-01
-1.57603219e-01 2.17276365e-01 -1.22930753e+00 7.50299275e-01
1.17986608e+00 2.34155670e-01 -2.33329773e-01 6.52620971e-01
6.58170342e-01 -6.33252382e-01 -5.27816772e-01 3.76781881e-01
2.62847781e-01 -9.53150630e-01 8.67186606e-01 -6.07988477e-01
3.98675829e-01 -5.22242606e-01 -5.89402653e-02 -1.57886827e+00
-3.77500832e-01 -1.05802822e+00 -7.85541981e-02 7.49681234e-01
6.15400195e-01 -1.05857217e+00 9.20460582e-01 5.78403175e-01
-1.67525887e-01 -7.34690964e-01 -1.01143157e+00 -1.33640754e+00
1.74087375e-01 -1.75616071e-01 8.27526689e-01 8.13687980e-01
5.59579670e-01 1.29438326e-01 -9.01562646e-02 6.25216246e-01
6.67641342e-01 4.71959054e-01 1.04367363e+00 -1.01898086e+00
-3.84088129e-01 -6.65500998e-01 -1.05165713e-01 -7.66466916e-01
2.27777824e-01 -4.78395730e-01 3.15555930e-01 -1.81316721e+00
3.51684242e-01 -8.63634109e-01 1.45550951e-01 6.76345110e-01
7.29412511e-02 -1.07320525e-01 1.80960000e-01 -2.10151404e-01
-1.15479898e+00 8.18996206e-02 1.26259804e+00 -2.50351638e-01
-2.48628795e-01 -4.71442565e-02 -5.93202412e-01 6.10119104e-01
8.34686697e-01 -6.59056067e-01 -3.31315339e-01 -4.79438901e-01
8.00781846e-01 3.47550124e-01 1.28575787e-01 -9.29093182e-01
3.79033118e-01 -9.67205048e-01 -4.69497502e-01 -3.50696355e-01
1.93047449e-01 -8.87515724e-01 4.86526877e-01 7.59107769e-01
-7.06439419e-03 3.39620113e-01 1.52517483e-01 3.56119215e-01
4.58927155e-02 -4.00098383e-01 5.19626260e-01 -3.89067650e-01
-5.31786382e-01 1.97935879e-01 -6.29260778e-01 1.26276806e-01
1.61996186e+00 -2.24294692e-01 -1.02850878e+00 -6.16179645e-01
-4.92809713e-01 9.06170666e-01 6.39657736e-01 9.76351798e-02
3.27150941e-01 -8.30340743e-01 -7.08568871e-01 -4.30929124e-01
-2.26503634e-03 2.96812236e-01 -6.88900501e-02 1.04526746e+00
-7.29336500e-01 4.21369195e-01 -3.35608870e-01 -2.01742381e-01
-9.70918834e-01 8.06254447e-01 1.94746315e-01 -5.22006810e-01
-6.89704299e-01 6.58161342e-01 3.83350812e-02 -4.23964918e-01
2.84131110e-01 -2.65126258e-01 2.32408956e-01 -3.35841715e-01
6.15281701e-01 7.35345483e-01 -1.04821883e-02 2.25725211e-02
-6.68869555e-01 3.32208723e-01 -1.41607493e-01 -1.94801226e-01
1.78536642e+00 -8.07266980e-02 -2.76099473e-01 -4.29185361e-01
4.94006008e-01 -7.43322372e-02 -8.26733768e-01 1.87753379e-01
5.35032563e-02 -4.40896839e-01 -1.83998436e-01 -1.00317919e+00
-1.00368667e+00 8.48282501e-02 -1.64179146e-01 7.18159378e-01
9.51800704e-01 2.57224172e-01 8.18682313e-01 6.61098301e-01
1.16981411e+00 -1.16643035e+00 -2.77484268e-01 8.25236380e-01
6.43858790e-01 -8.07354808e-01 1.61888465e-01 -9.26921904e-01
-4.08843398e-01 8.09722722e-01 7.83443928e-01 -3.50474805e-01
-4.31620376e-03 6.52749121e-01 -3.33092183e-01 -2.21975058e-01
-1.05022693e+00 -5.75715840e-01 -6.66161656e-01 6.21246576e-01
-6.10800266e-01 2.96438068e-01 -5.26141763e-01 5.05903006e-01
-5.55401325e-01 -1.22942571e-02 1.09228563e+00 1.26221311e+00
-5.84430873e-01 -1.26895154e+00 -5.00634968e-01 2.43586767e-02
-1.59566805e-01 3.13646883e-01 -4.93712783e-01 9.37392056e-01
-1.88211098e-01 1.21962225e+00 -1.84822023e-01 -1.72081172e-01
1.76435977e-01 -6.06891394e-01 9.04193401e-01 -2.76294738e-01
-5.72247386e-01 -2.03065425e-01 6.16696894e-01 -9.72486079e-01
-2.39893839e-01 -5.49691141e-01 -1.60127616e+00 -7.93188810e-01
-2.71309257e-01 3.84468436e-01 6.73131466e-01 1.11225414e+00
1.06307589e-01 5.00585139e-01 5.85827529e-01 -7.97382355e-01
-4.66389686e-01 -2.17130363e-01 -3.30501109e-01 -1.50159612e-01
-2.58632954e-02 -7.87472010e-01 -2.96756774e-01 -7.14749873e-01] | [4.95452356338501, 1.9091202020645142] |
dcaa0656-9000-49cf-a6aa-0dcec2cc84c8 | guided-exploration-of-data-summaries | 2205.13956 | null | https://arxiv.org/abs/2205.13956v1 | https://arxiv.org/pdf/2205.13956v1.pdf | Guided Exploration of Data Summaries | Data summarization is the process of producing interpretable and representative subsets of an input dataset. It is usually performed following a one-shot process with the purpose of finding the best summary. A useful summary contains k individually uniform sets that are collectively diverse to be representative. Uniformity addresses interpretability and diversity addresses representativity. Finding such as summary is a difficult task when data is highly diverse and large. We examine the applicability of Exploratory Data Analysis (EDA) to data summarization and formalize Eda4Sum, the problem of guided exploration of data summaries that seeks to sequentially produce connected summaries with the goal of maximizing their cumulative utility. EdA4Sum generalizes one-shot summarization. We propose to solve it with one of two approaches: (i) Top1Sum which chooses the most useful summary at each step; (ii) RLSum which trains a policy with Deep Reinforcement Learning that rewards an agent for finding a diverse and new collection of uniform sets at each step. We compare these approaches with one-shot summarization and top-performing EDA solutions. We run extensive experiments on three large datasets. Our results demonstrate the superiority of our approaches for summarizing very large data, and the need to provide guidance to domain experts. | ['Aurélien Personnaz', 'Sihem Amer-Yahia', 'Brit Youngmann'] | 2022-05-27 | null | null | null | null | ['data-summarization'] | ['miscellaneous'] | [ 3.83862466e-01 4.94644105e-01 -3.64264578e-01 -3.07341814e-01
-1.34791160e+00 -4.98590320e-01 4.74229604e-01 8.00956190e-01
-1.61492378e-01 1.01505291e+00 1.01354682e+00 -6.60842583e-02
-4.43838328e-01 -6.59444273e-01 -6.55789316e-01 -5.14289677e-01
-2.27941096e-01 9.57863271e-01 -1.20820299e-01 1.21684775e-01
7.55467892e-01 3.23391289e-01 -1.63549662e+00 4.40014482e-01
1.45240140e+00 8.30553949e-01 2.90323913e-01 9.53292787e-01
-2.42546335e-01 7.75355220e-01 -1.14680910e+00 -9.77574587e-02
1.51095763e-01 -6.24291480e-01 -1.21530473e+00 4.54992235e-01
2.33766839e-01 -4.67754275e-01 3.08334917e-01 7.87819624e-01
6.18755460e-01 5.14928818e-01 7.04324961e-01 -1.28857791e+00
-6.96603954e-01 1.12127268e+00 -6.89988375e-01 3.41152191e-01
5.54537356e-01 2.89898634e-01 1.29501784e+00 -5.96629500e-01
7.56996095e-01 1.29380846e+00 3.96956593e-01 4.25381541e-01
-1.26565361e+00 -7.76043208e-03 4.03853029e-01 -2.10341528e-01
-8.48330498e-01 -5.86633742e-01 6.23732686e-01 -1.96187586e-01
1.15564179e+00 6.17217422e-01 6.35260880e-01 7.64013171e-01
1.25905916e-01 1.22190106e+00 3.63521665e-01 -2.24262878e-01
9.58006680e-01 -2.42152527e-01 5.93828797e-01 2.03404054e-01
8.30031991e-01 -7.34065056e-01 -6.92573428e-01 -7.01820254e-01
1.68029629e-02 7.00608119e-02 -7.55026788e-02 -2.31179416e-01
-1.26351190e+00 1.00110090e+00 2.84536183e-01 -3.43225189e-02
-9.71104860e-01 2.07350224e-01 6.07892752e-01 2.77589351e-01
5.15645206e-01 1.28275490e+00 1.48043074e-02 -4.19858396e-02
-1.09081149e+00 6.87899232e-01 9.18875515e-01 1.06050038e+00
6.38069093e-01 1.13849699e-01 -6.06739759e-01 6.01568222e-01
-1.70264706e-01 9.58907008e-02 7.39191234e-01 -1.43837512e+00
6.46207392e-01 8.88756156e-01 3.60607415e-01 -5.90650082e-01
-3.38807374e-01 -1.94275111e-01 -8.37360919e-01 -9.25831422e-02
-1.64067835e-01 -5.37486970e-01 -8.09260607e-01 1.47643018e+00
1.44730017e-01 -4.04404908e-01 5.50727665e-01 5.57389498e-01
1.04791629e+00 9.54189599e-01 3.14854272e-02 -7.72028327e-01
9.36250508e-01 -9.49648678e-01 -7.17617750e-01 -2.29164809e-01
4.92636591e-01 -1.45905614e-01 9.54483807e-01 3.92101526e-01
-1.60347188e+00 -2.91008800e-01 -1.03846800e+00 -1.85254782e-01
-2.07113504e-01 4.42916676e-02 3.40205133e-01 1.73500106e-01
-1.22824311e+00 7.97639549e-01 -6.52978003e-01 -5.34212172e-01
6.92165971e-01 3.79834384e-01 -5.65008298e-02 2.59409726e-01
-6.96474254e-01 5.72574198e-01 7.85386980e-01 -4.57853079e-01
-7.33966768e-01 -7.40697026e-01 -6.80103481e-01 4.54923332e-01
8.24954450e-01 -1.19424856e+00 1.53743982e+00 -7.14778662e-01
-1.07403195e+00 4.18094426e-01 -4.48278695e-01 -7.43934095e-01
4.38743770e-01 -3.63322407e-01 1.54028282e-01 5.28494641e-02
5.55778146e-01 6.04394794e-01 3.99348021e-01 -1.42147589e+00
-8.38410914e-01 -4.54986274e-01 -2.75677055e-01 5.05388618e-01
-2.31144384e-01 -8.33591744e-02 -2.59836037e-02 -5.18577695e-01
-2.04472527e-01 -3.49923790e-01 -5.54422259e-01 -6.39904320e-01
-1.01956022e+00 -6.69562817e-01 5.31523466e-01 -6.23805761e-01
1.75538135e+00 -1.59345675e+00 3.21447909e-01 -1.00763300e-02
4.21983808e-01 7.74374008e-02 -1.36963993e-01 9.08442080e-01
1.38719320e-01 5.13285697e-01 -3.95873338e-01 -5.15805423e-01
-7.08601177e-02 3.47485729e-02 -5.57486951e-01 -1.52363092e-01
3.23856443e-01 9.09901679e-01 -1.19895387e+00 -4.25466686e-01
-2.66508132e-01 -4.07903194e-01 -5.14610291e-01 4.34559673e-01
-6.81499779e-01 -5.33171147e-02 -6.36681199e-01 5.48873425e-01
3.73891920e-01 -4.90848750e-01 1.55454233e-01 3.60683762e-02
-3.36245030e-01 3.37967217e-01 -1.15070367e+00 1.58304942e+00
3.32676843e-02 5.12834132e-01 -4.47378129e-01 -9.21711683e-01
9.56118941e-01 -7.29536861e-02 3.96587759e-01 -2.42976531e-01
9.70818326e-02 2.58667290e-01 -2.84983516e-01 -6.02896512e-01
1.32261527e+00 2.00607389e-01 -4.06687260e-01 1.01935077e+00
-1.47678494e-01 -1.98711097e-01 7.28441298e-01 6.90988302e-01
1.35395801e+00 -4.41270024e-01 9.69378889e-01 -3.74284923e-01
-2.72593796e-02 4.12873954e-01 4.85369384e-01 1.29747093e+00
2.47621819e-01 7.42969871e-01 1.05629599e+00 -4.20645028e-01
-1.05375016e+00 -8.92914653e-01 6.41659319e-01 1.02407086e+00
2.22416781e-03 -5.10957420e-01 -6.81503415e-01 -5.96126616e-01
1.45914495e-01 1.37450874e+00 -7.43039668e-01 -2.07322836e-01
-4.00854796e-01 -5.57767451e-01 -2.00762935e-02 4.98958379e-01
3.54670823e-01 -1.36493945e+00 -1.19953978e+00 2.32490882e-01
-2.81635582e-01 -3.70162606e-01 -6.41413689e-01 3.61652046e-01
-9.11142230e-01 -9.40346301e-01 -6.68825805e-01 -5.95154345e-01
7.35829651e-01 4.35293287e-01 1.14111328e+00 -2.63201088e-01
5.95966019e-02 3.19226146e-01 -4.74995852e-01 -8.30247343e-01
-6.59430683e-01 4.37236696e-01 -7.87412450e-02 -1.36360258e-01
1.86286941e-01 -3.98482472e-01 -4.96054143e-01 -2.87895769e-01
-9.66631234e-01 6.75402656e-02 5.12370110e-01 5.39363921e-01
7.62268603e-01 3.03023518e-03 1.15538669e+00 -1.13734961e+00
1.68310916e+00 -8.19379330e-01 3.60798910e-02 7.36320496e-01
-4.67343539e-01 3.32219362e-01 9.56566870e-01 -1.59411535e-01
-8.85121703e-01 -1.51350126e-01 3.92270148e-01 -3.24017078e-01
7.04448894e-02 6.28738642e-01 -1.02934703e-01 9.56135511e-01
8.12293708e-01 4.82247680e-01 5.94706871e-02 -3.05881172e-01
4.38545316e-01 8.38604808e-01 7.85796762e-01 -4.54572082e-01
-3.17461751e-02 2.59979963e-01 -4.81338501e-01 -8.32035542e-01
-7.40650535e-01 -5.01280248e-01 -3.73282194e-01 -4.42889333e-02
5.06513953e-01 -6.86153054e-01 -6.27292573e-01 4.80830967e-02
-1.15308595e+00 -1.87666222e-01 -1.04398286e+00 -1.45286739e-01
-8.86282265e-01 3.47890466e-01 7.11940601e-02 -8.49046290e-01
-1.13909960e+00 -7.56836057e-01 1.09840822e+00 5.28113723e-01
-8.80689561e-01 -4.83932018e-01 2.51291871e-01 1.05149169e-02
2.05253631e-01 6.75125122e-01 8.91784668e-01 -1.35979342e+00
-4.62253600e-01 -9.74119604e-02 1.95211247e-01 -6.65634423e-02
4.22272027e-01 1.82898074e-01 -5.87924302e-01 -3.76408607e-01
-3.06927919e-01 -4.57844347e-01 1.11061311e+00 7.33833194e-01
1.45660782e+00 -9.29905593e-01 -2.84334779e-01 1.62659213e-01
1.12397194e+00 4.57584947e-01 2.03200623e-01 3.22998345e-01
2.84484386e-01 5.51699460e-01 7.74038255e-01 1.00935531e+00
4.35676634e-01 7.24174501e-03 3.28749657e-01 2.12913245e-01
6.54412806e-02 -3.69090468e-01 -2.76741255e-02 4.53407764e-01
1.36240989e-01 -9.42426383e-01 -7.25799978e-01 1.03119397e+00
-2.29067564e+00 -1.18888474e+00 2.80850649e-01 2.08889389e+00
6.84979856e-01 1.47673890e-01 6.60730243e-01 -1.88905299e-02
6.54676318e-01 3.06558698e-01 -1.15937304e+00 -9.18240845e-01
-1.45378157e-01 -2.43894666e-01 -1.53241295e-03 2.46445984e-01
-7.50198424e-01 6.14436626e-01 6.24697113e+00 5.85876822e-01
-5.83216667e-01 -6.32319093e-01 9.58363593e-01 -5.89573622e-01
-8.16557884e-01 -2.21358791e-01 -5.27297914e-01 5.90752184e-01
8.78227711e-01 -9.30234253e-01 2.71806300e-01 8.17549586e-01
3.92276615e-01 -5.67686081e-01 -1.31472313e+00 5.89034200e-01
3.61910276e-02 -1.90568542e+00 6.34984612e-01 -1.57439411e-01
1.21463311e+00 -1.37590304e-01 -1.83403805e-01 -5.43102250e-03
9.96676028e-01 -7.69262195e-01 6.09278679e-01 7.05030859e-01
5.49493790e-01 -1.12777269e+00 3.74931812e-01 5.40639520e-01
-6.47451520e-01 -3.69563580e-01 -4.02271211e-01 1.87751338e-01
1.94829673e-01 5.51815450e-01 -1.01698136e+00 6.78410769e-01
5.26137769e-01 7.72029042e-01 -3.88742000e-01 1.01571858e+00
1.12646759e-01 2.86737859e-01 -1.76889837e-01 -5.14875472e-01
3.02402377e-01 -5.17937914e-02 8.88824224e-01 1.16997695e+00
4.56235766e-01 1.14751607e-01 2.70179272e-01 8.02993059e-01
-3.76920909e-01 -8.06336999e-02 -5.92047930e-01 -1.65532485e-01
8.77422452e-01 9.01550770e-01 -7.95136988e-01 -7.79341519e-01
2.15429068e-01 7.49333739e-01 4.55623478e-01 1.98440179e-01
-1.47093743e-01 -6.59059465e-01 2.74061233e-01 -3.18383537e-02
3.43435675e-01 2.14070812e-01 -7.09088027e-01 -7.90760159e-01
-6.08376302e-02 -9.51799750e-01 9.77971256e-01 -8.64486217e-01
-1.18755901e+00 6.39198244e-01 2.61789232e-01 -1.03860962e+00
-4.86574918e-01 2.68445551e-01 -1.22106278e+00 5.98654687e-01
-1.02825904e+00 -5.30799329e-01 -4.26700473e-01 7.08555104e-03
1.26396537e+00 -2.28319123e-01 5.62622547e-01 -7.06439614e-01
-7.96313465e-01 1.84127197e-01 4.38036174e-01 -4.75986630e-01
3.79672796e-01 -1.66571486e+00 8.76266241e-01 9.20438230e-01
-4.80001390e-01 6.33623779e-01 9.72901404e-01 -9.61563408e-01
-1.26810765e+00 -1.12704074e+00 9.69212532e-01 -1.83448792e-01
3.51376176e-01 2.13477723e-02 -9.94020164e-01 6.30502999e-01
5.86288214e-01 -6.39654219e-01 6.77978396e-01 -7.53538087e-02
3.15748394e-01 3.41198407e-02 -1.10981989e+00 6.66900635e-01
9.52131569e-01 3.10029060e-01 -9.28257108e-01 2.74214715e-01
8.65190923e-01 -1.07784919e-01 -5.76424599e-01 -2.22869869e-03
1.46479651e-01 -9.46441233e-01 5.96953630e-01 -8.98189187e-01
9.52664614e-01 -6.15558997e-02 9.66919884e-02 -1.89197433e+00
-3.74813169e-01 -1.06060660e+00 -3.85413706e-01 1.20322585e+00
3.72871280e-01 -3.83312255e-01 6.28496826e-01 7.36231208e-01
-2.94366360e-01 -9.73835647e-01 -4.17404413e-01 -5.47762394e-01
-1.58959344e-01 3.13163936e-01 1.07719696e+00 5.63315809e-01
2.66912192e-01 6.21091247e-01 -2.56521285e-01 -1.75754458e-01
6.50345922e-01 6.67680323e-01 1.08861232e+00 -1.22964108e+00
1.00815795e-01 -7.54730582e-01 2.82310039e-01 -9.71733510e-01
-2.46179968e-01 -7.27107406e-01 1.98956877e-01 -2.32108593e+00
4.98203188e-01 -3.84160056e-04 1.61327451e-01 3.50691676e-01
-4.94038194e-01 -6.85391486e-01 3.93756367e-02 3.20133060e-01
-1.26017797e+00 6.10822201e-01 1.00214720e+00 -1.05856396e-01
-9.14056540e-01 2.05590919e-01 -1.61060822e+00 3.83975953e-01
9.34789777e-01 -3.64776820e-01 -6.52933776e-01 -2.53768623e-01
2.39910275e-01 2.88997620e-01 -2.13293195e-01 -7.19590187e-01
4.75468129e-01 -3.60162348e-01 3.64027470e-01 -1.19672513e+00
-1.96525231e-01 -1.53702423e-01 7.27574304e-02 5.36545038e-01
-1.09260213e+00 1.89947248e-01 1.00986570e-01 7.46796250e-01
-4.74844947e-02 -3.16532642e-01 4.61846769e-01 -4.11009580e-01
-7.47407794e-01 7.90455490e-02 -4.54555959e-01 3.95480037e-01
1.08835363e+00 -4.79435682e-01 -5.94025731e-01 -4.80852753e-01
-4.87445563e-01 9.86379981e-01 2.71467000e-01 2.30588526e-01
6.45994246e-01 -1.08948648e+00 -1.08111918e+00 -7.28405938e-02
1.66529238e-01 6.56201482e-01 1.34202570e-01 2.54609406e-01
-3.95920455e-01 2.90448487e-01 -2.00024873e-01 -2.39891529e-01
-1.15324879e+00 6.01341426e-01 -6.98896125e-02 -4.74585384e-01
-6.47635996e-01 6.30356312e-01 -2.75432430e-02 -3.20076719e-02
2.45061710e-01 -5.56960344e-01 -3.74158978e-01 5.04607916e-01
8.02525997e-01 1.04992414e+00 -1.19688138e-01 4.75234389e-02
-1.49459153e-01 8.42892658e-03 -4.41342592e-01 2.25271031e-01
1.69302642e+00 -2.17945859e-01 -6.64713830e-02 5.25980294e-01
9.59268689e-01 -2.23581061e-01 -1.14192402e+00 -2.13873506e-01
1.98664337e-01 -2.97516525e-01 -2.51374483e-01 -8.15621912e-01
-4.46138293e-01 2.94601947e-01 -4.21471775e-01 9.03220773e-01
1.17289352e+00 1.78961977e-01 5.94416499e-01 5.64486682e-01
-1.34942025e-01 -1.18697810e+00 4.48840886e-01 9.65244621e-02
1.43105400e+00 -1.24526787e+00 3.84862185e-01 1.17238693e-01
-1.22158456e+00 1.10688829e+00 6.43948078e-01 -2.43870944e-01
3.65226679e-02 -6.04485534e-02 -4.93653923e-01 -4.12949026e-01
-1.11496544e+00 -1.28366038e-01 1.46361262e-01 3.31309885e-01
-1.06828324e-01 1.76953763e-01 -4.16730255e-01 6.61228299e-01
-4.16160405e-01 -3.20092961e-02 8.84695292e-01 1.04657888e+00
-1.03309000e+00 -4.64950740e-01 -2.82979727e-01 1.18543553e+00
-1.43535018e-01 3.76414597e-01 -9.25567031e-01 5.44795632e-01
-4.66284782e-01 9.70827162e-01 3.54900390e-01 -1.56152010e-01
4.49110746e-01 -7.97548369e-02 -9.58370715e-02 -8.27198863e-01
-6.21610701e-01 -6.84907809e-02 1.56609222e-01 -2.51753509e-01
-1.68467596e-01 -1.01456070e+00 -1.36330795e+00 -3.93270344e-01
-4.14146036e-02 4.29576218e-01 3.04991603e-01 6.41451478e-01
7.77773082e-01 7.71107197e-01 8.18702996e-01 -6.92607939e-01
-9.08490241e-01 -7.74595618e-01 -4.43118721e-01 2.29637086e-01
6.73521161e-01 -3.29924095e-03 -1.38505638e-01 -1.00903332e-01] | [12.511327743530273, 9.441153526306152] |
6cc357ab-8676-40ad-862c-2806b26ba6b5 | molecule-design-by-latent-space-energy-based | 2306.14902 | null | https://arxiv.org/abs/2306.14902v1 | https://arxiv.org/pdf/2306.14902v1.pdf | Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting | Generation of molecules with desired chemical and biological properties such as high drug-likeness, high binding affinity to target proteins, is critical for drug discovery. In this paper, we propose a probabilistic generative model to capture the joint distribution of molecules and their properties. Our model assumes an energy-based model (EBM) in the latent space. Conditional on the latent vector, the molecule and its properties are modeled by a molecule generation model and a property regression model respectively. To search for molecules with desired properties, we propose a sampling with gradual distribution shifting (SGDS) algorithm, so that after learning the model initially on the training data of existing molecules and their properties, the proposed algorithm gradually shifts the model distribution towards the region supported by molecules with desired values of properties. Our experiments show that our method achieves very strong performances on various molecule design tasks. | ['Ying Nian Wu', 'Tian Han', 'Bo Pang', 'Deqian Kong'] | 2023-06-09 | null | null | null | null | ['drug-discovery'] | ['medical'] | [ 4.78726119e-01 -1.16037294e-01 -6.76935196e-01 -1.76251143e-01
-5.59767902e-01 -4.61552441e-01 7.76553750e-01 4.22132671e-01
1.67132188e-02 1.37326539e+00 1.55960947e-01 -6.74070120e-02
-1.41851798e-01 -1.07648754e+00 -7.20234215e-01 -1.15088546e+00
1.18617497e-01 7.21273661e-01 2.34181628e-01 5.77004068e-02
5.45510471e-01 7.64743745e-01 -1.16617119e+00 4.29198965e-02
1.14063656e+00 4.26045835e-01 4.54512388e-01 3.25501829e-01
-1.52209736e-02 6.06266439e-01 -2.67897934e-01 6.99871182e-02
-2.08484367e-01 -6.51631474e-01 -6.30291104e-01 -1.91161737e-01
-1.85328051e-02 8.24484006e-02 -9.15180743e-02 9.04411793e-01
4.53320324e-01 5.05128086e-01 1.48467040e+00 -6.79599166e-01
-6.15006208e-01 2.60576785e-01 -2.96560556e-01 -4.69785899e-01
4.30875719e-01 1.32014096e-01 1.00012028e+00 -1.04843283e+00
7.67506897e-01 1.04834175e+00 1.34203598e-01 8.19242418e-01
-1.63319767e+00 -5.70526898e-01 9.54788253e-02 2.78572626e-02
-1.40029526e+00 -5.00731707e-01 8.77398551e-01 -4.36786413e-01
1.10419834e+00 2.02624783e-01 7.09015131e-01 9.94914114e-01
4.06477183e-01 6.79373860e-01 6.57763660e-01 -3.10196191e-01
9.05605555e-01 2.39381805e-01 -2.80568004e-01 5.89404643e-01
2.62272179e-01 -9.38557386e-02 -7.52013087e-01 -8.25074911e-01
4.32487696e-01 6.88087642e-02 -2.22182915e-01 -9.38966274e-01
-8.38651597e-01 9.20490265e-01 3.03091019e-01 2.21511066e-01
-9.24538791e-01 6.15175590e-02 -2.56262451e-01 -4.36736792e-01
3.35506678e-01 8.51638854e-01 -5.99259615e-01 1.44221216e-01
-9.43000317e-01 4.98956472e-01 6.53123438e-01 7.85319746e-01
8.91523778e-01 -2.40626693e-01 -2.67641932e-01 6.84965611e-01
7.53562510e-01 2.85710961e-01 2.30951965e-01 -2.53881007e-01
-1.18369564e-01 5.93976736e-01 4.67236042e-01 -4.65816021e-01
-1.64813653e-01 -4.03168380e-01 -6.69090152e-01 -1.30828902e-01
-9.43646356e-02 2.83102319e-02 -1.12657714e+00 1.77485967e+00
6.00794375e-01 4.17971835e-02 2.49596000e-01 2.62295604e-01
6.07486725e-01 1.18020880e+00 6.15195751e-01 -8.11373353e-01
9.19561744e-01 -6.39776289e-01 -5.68774641e-01 1.86959863e-01
6.24508679e-01 -7.17674673e-01 6.22459412e-01 4.65740055e-01
-1.04588306e+00 -4.16573852e-01 -9.01661396e-01 2.90475816e-01
-2.46065333e-01 6.17816225e-02 7.52446771e-01 5.38430393e-01
-5.63013256e-01 1.03216517e+00 -7.71975517e-01 -5.85574424e-03
5.89783072e-01 5.51439524e-01 -2.84697801e-01 -2.16027021e-01
-1.00026560e+00 5.81280291e-01 6.60033226e-01 -2.64265686e-01
-1.43942785e+00 -6.71630263e-01 -6.22437298e-01 -5.33130998e-03
9.86936912e-02 -1.01299155e+00 6.91046178e-01 -5.09652674e-01
-1.85322201e+00 2.04952240e-01 -5.79625964e-01 -2.60641634e-01
5.63131459e-03 -4.56492789e-02 -9.66125950e-02 -4.28335890e-02
-1.37501001e-01 8.35523903e-01 9.20369804e-01 -1.21488214e+00
-3.81276369e-01 -1.47918284e-01 -3.95212978e-01 2.08872899e-01
-2.34466195e-01 -2.98663706e-01 -1.12181135e-01 -2.58375347e-01
5.63779585e-02 -8.78592968e-01 -5.40109873e-01 -5.02737284e-01
-7.68128872e-01 -5.10929108e-01 2.47666448e-01 -2.29347497e-01
1.19943857e+00 -1.79705918e+00 7.47338653e-01 6.75528169e-01
2.10415035e-01 1.24127403e-01 -8.26715380e-02 8.89290988e-01
-2.51041442e-01 1.80515051e-01 -3.13284725e-01 2.59410560e-01
-4.16799635e-01 -1.80820122e-01 -1.81566805e-01 3.78011525e-01
2.09366247e-01 7.65639901e-01 -1.11949468e+00 -1.77171230e-01
-3.62662375e-02 6.09075010e-01 -7.32258737e-01 3.52590919e-01
-8.89185309e-01 5.45031726e-01 -1.07385552e+00 6.36027932e-01
7.65113890e-01 -4.23614770e-01 5.07755399e-01 -2.14013234e-01
-1.29905671e-01 2.59455621e-01 -7.61804760e-01 1.30934191e+00
-1.79310087e-02 -2.99418032e-01 -7.30422199e-01 -6.05671167e-01
1.17016160e+00 4.27173048e-01 6.86516941e-01 -1.53863430e-01
-1.99948445e-01 3.20321828e-01 2.53331423e-01 -2.20487088e-01
1.93423241e-01 -5.41995943e-01 3.86794955e-01 1.72373950e-01
7.52460435e-02 -6.73532635e-02 1.48834929e-01 1.61621422e-01
8.77487361e-01 4.67574626e-01 4.13235456e-01 -1.60229981e-01
5.27227640e-01 -1.04953378e-01 4.07250345e-01 4.22230780e-01
3.95385116e-01 1.33206591e-01 4.72260058e-01 -2.77159095e-01
-1.18678725e+00 -8.77163649e-01 -2.39786521e-01 8.18568826e-01
-9.40832198e-02 -5.60877442e-01 -5.36891758e-01 -6.34048879e-01
-2.80236840e-01 8.28802645e-01 -6.10884011e-01 -6.00432038e-01
-2.24312142e-01 -1.10134029e+00 -1.39695659e-01 -6.32670149e-02
5.72817400e-02 -1.17007339e+00 3.66295129e-02 6.53723180e-01
2.93172807e-01 -3.13843220e-01 -2.92229682e-01 3.75573665e-01
-9.33133841e-01 -8.50513637e-01 -9.42794800e-01 -7.65419245e-01
9.64497864e-01 -1.26525596e-01 5.69048107e-01 -3.69540662e-01
-5.84153086e-02 -3.80930930e-01 -2.99793631e-01 -3.41056108e-01
-5.26485980e-01 1.46732613e-01 3.24306823e-02 1.75826818e-01
4.87028882e-02 -6.74610913e-01 -7.63767540e-01 -8.97794962e-03
-7.44459748e-01 1.40793890e-01 7.19846785e-01 8.25587749e-01
1.15253830e+00 2.69635439e-01 6.66356444e-01 -9.64795589e-01
6.12654865e-01 -6.19261563e-01 -5.33971608e-01 2.56720692e-01
-7.74437189e-01 5.53162575e-01 5.17679155e-01 -7.00950205e-01
-9.99702692e-01 5.07472277e-01 -2.68254340e-01 1.65162515e-02
-1.68027952e-01 5.52342832e-01 -6.86647296e-01 1.31206140e-01
6.38635218e-01 6.70107901e-01 -2.19355449e-01 -6.25286460e-01
3.06621253e-01 2.29082793e-01 -1.23348661e-01 -8.46810699e-01
6.11553073e-01 1.52783260e-01 2.88824975e-01 -7.13883221e-01
-5.56284964e-01 -3.33381116e-01 -4.09683675e-01 2.25479454e-01
7.89635479e-01 -6.92074537e-01 -6.37238026e-01 2.87124813e-01
-9.23668385e-01 -2.20500678e-01 -1.55214384e-01 7.36188769e-01
-6.69441938e-01 2.14353904e-01 -1.41992897e-01 -9.52556610e-01
-4.04212475e-01 -1.21859825e+00 8.97941351e-01 3.11392665e-01
-3.50134075e-01 -9.28491950e-01 5.42004049e-01 -3.45842764e-02
1.78335384e-01 3.12831849e-01 1.47694457e+00 -7.50924110e-01
-9.63162601e-01 -3.66742909e-01 2.64124662e-01 -1.95619389e-02
5.49288452e-01 1.28553778e-01 -6.53860450e-01 -3.00236136e-01
-3.82057071e-01 -2.61434376e-01 9.36944246e-01 8.60949516e-01
1.17320371e+00 -2.40968496e-01 -9.12721217e-01 5.21357417e-01
1.29505658e+00 8.38324726e-01 7.82564461e-01 -5.33217825e-02
6.54959261e-01 3.06630224e-01 7.06761122e-01 6.19274318e-01
-2.56054461e-01 6.32170498e-01 3.03749889e-01 -8.79381895e-02
2.97171801e-01 -7.81944573e-01 3.51082921e-01 8.13996717e-02
-5.85293472e-02 -6.24896824e-01 -4.68413949e-01 3.19675028e-01
-1.75561154e+00 -8.81851971e-01 -1.09884711e-02 2.36130118e+00
1.32098615e+00 2.51349211e-01 3.84678811e-01 -3.72001290e-01
5.50003648e-01 -1.41583025e-01 -1.03341246e+00 -1.23494916e-01
7.48873036e-03 4.94889915e-01 4.04420376e-01 6.74493015e-01
-6.93622530e-01 1.15666151e+00 6.86797619e+00 1.32284880e+00
-8.45920861e-01 -4.45672899e-01 8.96458864e-01 1.64832965e-01
-7.90110707e-01 3.65746170e-01 -1.21782470e+00 3.72328877e-01
7.65812039e-01 -2.42288426e-01 2.14590102e-01 6.31455362e-01
4.51350480e-01 -6.30428866e-02 -1.20193470e+00 6.50541067e-01
-3.42481613e-01 -1.69009626e+00 5.00553131e-01 4.14468676e-01
8.18838000e-01 -4.72315013e-01 1.29531711e-01 -1.63662285e-01
1.95216283e-01 -1.14948237e+00 3.91142339e-01 7.99193561e-01
6.90799236e-01 -9.92033482e-01 3.33647728e-01 4.99320626e-01
-7.56196380e-01 4.10378486e-01 -4.64868605e-01 3.88959736e-01
-1.71190090e-02 5.88669181e-01 -1.22516251e+00 3.67629170e-01
-2.89790243e-01 7.04659760e-01 -1.04074612e-01 1.08824253e+00
-3.22949737e-01 5.85679233e-01 -1.64555192e-01 -6.16154075e-01
1.15569279e-01 -5.70688188e-01 3.20231378e-01 7.94212937e-01
2.73749232e-01 4.64575738e-03 2.14223891e-01 9.95331168e-01
-1.80097014e-01 4.94768023e-01 -5.88966131e-01 -4.02397424e-01
5.54065526e-01 9.66754317e-01 -6.70922518e-01 -5.02086639e-01
1.11742072e-01 8.55090141e-01 3.46272923e-02 6.00494564e-01
-7.62527406e-01 -1.69425324e-01 3.91299725e-01 1.67241275e-01
2.72790521e-01 -3.79118994e-02 1.85701028e-01 -7.76717365e-01
-3.82676959e-01 -7.41995037e-01 5.93333729e-02 -6.00423396e-01
-1.08498359e+00 4.10381794e-01 8.81691501e-02 -8.27450037e-01
1.78811520e-01 -3.48322690e-01 -5.58516681e-01 1.13360071e+00
-1.39503849e+00 -8.64214420e-01 4.22031254e-01 3.58071357e-01
4.59604502e-01 -3.94159943e-01 9.17435110e-01 -1.32128388e-01
-3.81092459e-01 2.00876579e-01 3.85969996e-01 -8.02695811e-01
6.68964744e-01 -1.15341926e+00 2.46497467e-01 3.13491747e-02
6.14129603e-02 9.41886604e-01 9.55088675e-01 -1.05333209e+00
-1.24081266e+00 -8.92359972e-01 8.57866585e-01 -4.03693080e-01
3.18510085e-01 -2.87216127e-01 -8.02187979e-01 2.91009303e-02
-2.49646232e-01 -5.54076374e-01 1.04093969e+00 8.14178959e-02
7.90632069e-02 3.04965019e-01 -1.17616844e+00 5.79127073e-01
8.42299640e-01 -7.71814659e-02 -5.26403785e-02 9.06820178e-01
6.09707415e-01 -1.43622849e-02 -8.53441715e-01 3.59541327e-01
5.77732384e-01 -4.82033879e-01 1.08420455e+00 -9.49595392e-01
1.11471787e-01 -5.39179683e-01 -1.41932487e-01 -1.29691982e+00
-7.70111263e-01 -7.25204349e-01 -3.15793455e-01 8.73842120e-01
9.20814455e-01 -3.67034882e-01 1.05677164e+00 5.33013523e-01
2.74650306e-01 -1.14566231e+00 -6.02750123e-01 -6.43777549e-01
3.41996527e-03 9.88114774e-02 6.99866951e-01 6.51113570e-01
-1.14501566e-01 9.41566169e-01 -6.40239894e-01 8.06221962e-02
3.95034224e-01 2.82025963e-01 6.08352721e-01 -1.10353518e+00
-4.49980170e-01 -2.49225333e-01 -7.22734183e-02 -1.31758702e+00
-1.08957455e-01 -8.18452358e-01 -3.72668922e-01 -1.63778841e+00
7.17811346e-01 -4.57147300e-01 -3.20171416e-01 2.51109689e-01
-1.16751164e-01 -3.62525791e-01 -3.91005397e-01 2.61923194e-01
-4.96502072e-01 1.01931262e+00 1.28590417e+00 -2.08668515e-01
-7.82448411e-01 4.77917761e-01 -6.90866232e-01 4.21877980e-01
7.17006743e-01 -6.08881354e-01 -6.06900394e-01 5.75238466e-01
4.66736853e-01 1.07185774e-01 -2.70108014e-01 -6.50778711e-01
-2.63221711e-01 -7.15162337e-01 6.14880502e-01 -6.50843918e-01
5.73080003e-01 -5.00477135e-01 5.05154848e-01 8.00093710e-01
-4.44804907e-01 -6.98508680e-01 -1.60610795e-01 7.82279670e-01
4.27555962e-04 -3.94268960e-01 8.63419533e-01 3.73910926e-02
-2.28970237e-02 8.62632632e-01 -4.57105845e-01 -5.73008597e-01
9.50307727e-01 -2.92114615e-01 3.02457243e-01 -1.79837659e-01
-1.00309014e+00 1.84608921e-02 5.91992378e-01 1.26155857e-02
9.64985430e-01 -1.33248675e+00 -5.76714337e-01 1.76103905e-01
3.13049108e-01 -1.16950448e-03 -4.08978313e-02 3.90472859e-01
-3.26702327e-01 4.96585071e-01 2.09626317e-01 -2.94049382e-01
-1.16940188e+00 8.12538624e-01 3.51624072e-01 -3.91920209e-01
6.50922135e-02 9.04128790e-01 5.74937820e-01 -6.07416816e-02
-1.50943711e-01 3.58967409e-02 -2.46862218e-01 -7.66398087e-02
3.37335765e-01 1.26549110e-01 -9.28263813e-02 -3.55502486e-01
-4.17416394e-01 4.96619105e-01 -4.49587554e-01 1.00920916e-01
1.60570109e+00 5.38308203e-01 1.47482846e-02 1.39474139e-01
1.01619506e+00 2.46634990e-01 -1.30289030e+00 -5.42197526e-02
-1.24501567e-02 -4.17415917e-01 4.25079279e-02 -8.49549472e-01
-2.13891059e-01 4.79779422e-01 4.78251129e-01 -1.34442210e-01
7.51375318e-01 2.60367364e-01 5.83528817e-01 3.21599513e-01
2.97859311e-01 -8.72367442e-01 3.02977949e-01 3.09622854e-01
6.39663339e-01 -8.49114299e-01 3.72566670e-01 -3.71731400e-01
-4.35867310e-01 9.67417777e-01 2.92307884e-01 7.12721497e-02
6.06496334e-01 -3.83597612e-01 -7.83424079e-01 -4.69596416e-01
-1.02355754e+00 -5.53416088e-02 4.47401077e-01 6.72170281e-01
6.70517266e-01 1.67056486e-01 -3.38756293e-01 2.08979696e-02
2.94273913e-01 -1.00674212e-01 -3.49548608e-02 8.16448748e-01
-8.83061111e-01 -1.81769276e+00 -1.19153008e-01 2.56669015e-01
-2.20104888e-01 -4.14837569e-01 -7.85529613e-01 2.17632785e-01
2.28532463e-01 5.67617059e-01 -4.03039753e-01 -9.24881473e-02
1.04170412e-01 2.49143258e-01 7.56255686e-01 -8.96688342e-01
8.74464810e-02 6.56065762e-01 -5.21093654e-03 5.17992266e-05
-1.28184691e-01 -6.87738240e-01 -1.29257119e+00 9.66922268e-02
-7.63720572e-01 6.64560914e-01 5.93923450e-01 7.58664429e-01
6.10439181e-01 4.08989787e-01 1.02573705e+00 -5.00232279e-01
-2.32877538e-01 -8.26013923e-01 -6.85307741e-01 -4.21906076e-03
1.33759990e-01 -6.24154627e-01 2.62931347e-01 1.84017628e-01] | [4.975209712982178, 5.711024284362793] |
4cbe2213-95e1-4728-9a5d-f48ba2e183ee | correcting-the-misuse-a-method-for-the | null | null | https://aclanthology.org/2020.deelio-1.1 | https://aclanthology.org/2020.deelio-1.1.pdf | Correcting the Misuse: A Method for the Chinese Idiom Cloze Test | The cloze test for Chinese idioms is a new challenge in machine reading comprehension: given a sentence with a blank, choosing a candidate Chinese idiom which matches the context. Chinese idiom is a type of Chinese idiomatic expression. The common misuse of Chinese idioms leads to error in corpus and causes error in the learned semantic representation of Chinese idioms. In this paper, we introduce the definition written by Chinese experts to correct the misuse. We propose a model for the Chinese idiom cloze test integrating various information effectively. We propose an attention mechanism called Attribute Attention to balance the weight of different attributes among different descriptions of the Chinese idiom. Besides the given candidates of every blank, we also try to choose the answer from all Chinese idioms that appear in the dataset as the extra loss due to the uniqueness and specificity of Chinese idioms. In experiments, our model outperforms the state-of-the-art model. | ['Hongbo Wang', 'Tan Yang', 'Hongsheng Zhao', 'Xinyu Wang'] | null | null | null | null | emnlp-deelio-2020-11 | ['cloze-test'] | ['natural-language-processing'] | [ 5.17745987e-02 -1.15867361e-01 -2.79847980e-01 -5.12387812e-01
-7.07119942e-01 -6.43875539e-01 1.41612262e-01 -1.96748048e-01
-3.45913410e-01 5.03190994e-01 7.35865891e-01 -3.82905275e-01
2.30264310e-02 -7.47397423e-01 -2.12035328e-01 -2.40077138e-01
6.87719762e-01 1.11059475e+00 1.19200289e-01 -5.22104084e-01
5.99203467e-01 -2.39786997e-01 -8.78404677e-01 1.01542521e+00
1.38388181e+00 7.87695289e-01 5.10785401e-01 6.73119575e-02
-3.99671912e-01 1.17609847e+00 -9.01658714e-01 -9.04926538e-01
-4.91214776e-03 -1.11506641e+00 -1.40683866e+00 -6.90341592e-02
1.50030077e-01 -2.80677319e-01 2.06756711e-01 1.48908317e+00
5.10508895e-01 -6.97451979e-02 5.72420955e-01 -8.40593278e-01
-1.33425152e+00 1.20079827e+00 -3.65493238e-01 3.55867088e-01
5.87559581e-01 -4.04412776e-01 1.33888149e+00 -9.90114987e-01
9.21456933e-01 1.26039314e+00 1.45304069e-01 9.52657521e-01
-5.03818870e-01 -8.01547170e-01 4.55743581e-01 1.05347359e+00
-1.27574635e+00 -4.00668420e-02 1.15607023e+00 -1.36980504e-01
1.04534101e+00 4.64400023e-01 2.29750782e-01 1.05603015e+00
3.50241400e-02 9.01585817e-01 1.09630954e+00 -6.22196853e-01
-1.48153871e-01 1.90665573e-01 4.41912442e-01 2.47835159e-01
-2.36950889e-01 -3.04046780e-01 -2.70877659e-01 1.80914387e-01
1.97424829e-01 -2.07480311e-01 -3.96830410e-01 2.49536693e-01
-8.79036009e-01 1.00720835e+00 4.70725268e-01 3.71272951e-01
8.21432024e-02 -3.86696070e-01 5.03841758e-01 6.64221406e-01
1.43078258e-02 7.86700308e-01 -9.05444443e-01 -1.21406943e-01
-1.42213374e-01 4.87369448e-01 7.29240716e-01 1.35698259e+00
3.14811945e-01 -3.99347514e-01 1.46045059e-01 1.08669806e+00
-1.10271029e-01 3.04027140e-01 9.79010344e-01 -6.91863179e-01
8.43400359e-01 9.67218101e-01 -1.10463865e-01 -1.19424784e+00
-2.67475963e-01 -3.49160403e-01 -6.18930519e-01 -4.59013015e-01
3.81401360e-01 2.82800347e-02 -1.61231503e-01 1.78577363e+00
-4.92151640e-02 -3.11128855e-01 1.94497511e-01 1.23768795e+00
9.54369247e-01 6.19069338e-01 -9.88340974e-02 -1.49072394e-01
1.70339775e+00 -1.31641448e+00 -9.17508066e-01 -5.21394670e-01
5.51685810e-01 -8.94327998e-01 1.50669372e+00 4.51739132e-01
-9.63883817e-01 -4.15712565e-01 -9.52462375e-01 -4.45206583e-01
-3.50593805e-01 6.68868273e-02 1.94747820e-01 3.71782988e-01
-2.43476212e-01 8.16215649e-02 -2.60042161e-01 7.70944124e-03
-2.53666565e-02 -1.01993335e-02 -1.11336671e-01 -3.17011356e-01
-1.55417192e+00 1.30347860e+00 6.81411445e-01 -1.10839278e-01
-3.74825001e-01 -5.67559600e-01 -8.95267427e-01 1.48977309e-01
5.87047756e-01 -3.49871606e-01 1.11433840e+00 -1.61240375e+00
-1.29324532e+00 1.18879879e+00 -2.74132460e-01 -1.58906519e-01
3.25211495e-01 -4.61625963e-01 -6.28375947e-01 -1.47748023e-01
5.44294715e-01 3.70154917e-01 4.06824321e-01 -9.28179502e-01
-4.59164828e-01 -2.42032945e-01 6.58023581e-02 4.68974590e-01
1.32463530e-01 7.79643774e-01 -2.75087953e-01 -6.76909566e-01
5.62642097e-01 -6.92657769e-01 2.08737999e-01 -8.00735414e-01
-2.81436533e-01 -3.71024996e-01 7.87230611e-01 -8.75775456e-01
1.60798585e+00 -2.06043959e+00 3.07094574e-01 -1.95974633e-01
-7.14459270e-02 -8.15818831e-02 -2.92012133e-02 3.46761256e-01
-3.84750627e-02 3.41422707e-01 -2.12629944e-01 2.14061171e-01
-6.83137402e-02 1.72801286e-01 -4.81494665e-01 -4.03089710e-02
4.34659600e-01 1.02596164e+00 -1.07160091e+00 -2.81936228e-01
-4.51176822e-01 -1.99109599e-01 -9.05236781e-01 3.20634007e-01
-5.33767164e-01 6.12815797e-01 -2.78348893e-01 5.89565992e-01
9.97877300e-01 -2.34720215e-01 5.70620775e-01 1.75637588e-01
2.07932174e-01 1.27979445e+00 -8.42210650e-01 1.51900387e+00
-4.17789489e-01 1.69711798e-01 -4.78787243e-01 -8.83532524e-01
9.75769877e-01 3.06086391e-01 -2.80923337e-01 -1.07449877e+00
3.02238137e-01 6.38403475e-01 5.99648833e-01 -7.83224642e-01
3.01088065e-01 -3.59690398e-01 -4.57501769e-01 6.77329540e-01
-1.35573953e-01 7.68666640e-02 8.89869332e-02 2.63915267e-02
7.46695757e-01 -2.59413812e-02 6.61618650e-01 -6.06145382e-01
9.69884574e-01 2.43831966e-02 9.83887792e-01 5.65942705e-01
-9.35800839e-03 6.54926717e-01 7.15576470e-01 -8.09736550e-01
-8.37471068e-01 -9.59722579e-01 -1.26908451e-01 1.21819830e+00
4.15748358e-01 -6.57767415e-01 -8.91909480e-01 -1.08125937e+00
-6.44940317e-01 8.23034823e-01 -4.64012712e-01 -5.00811376e-02
-1.15766108e+00 -7.44381845e-01 4.58168924e-01 7.25429118e-01
9.66677427e-01 -1.63193512e+00 -8.67308259e-01 2.45869204e-01
-8.12857449e-01 -1.20886004e+00 -7.20936239e-01 1.91861130e-02
-3.51512223e-01 -1.21649444e+00 -4.31105271e-02 -1.31281030e+00
8.06327522e-01 -1.67677253e-01 1.48447001e+00 7.04618871e-01
3.10427845e-01 -6.38184607e-01 -8.78156066e-01 -4.12060350e-01
-4.52471823e-01 1.62607044e-01 -3.47667605e-01 -3.24873358e-01
1.17349696e+00 -1.50626764e-01 -2.07883507e-01 2.75940627e-01
-6.69611990e-01 3.68731797e-01 6.66817725e-02 1.25772858e+00
2.12202400e-01 7.79926702e-02 6.18501186e-01 -1.44016528e+00
8.39483142e-01 -5.06866693e-01 -4.47031796e-01 2.82213688e-01
-5.38773179e-01 6.05912469e-02 9.16576564e-01 -6.02188408e-01
-1.25489700e+00 -4.66567695e-01 -1.89748481e-01 2.83564478e-01
-1.08621821e-01 9.52453136e-01 -7.97061205e-01 5.35366714e-01
5.43767452e-01 6.44879863e-02 -3.11505854e-01 -7.58274496e-01
2.37014443e-01 7.76584387e-01 4.40274954e-01 -9.55967367e-01
2.50193417e-01 -1.44885346e-01 -6.65792465e-01 -3.01788121e-01
-1.41843402e+00 -2.99648821e-01 -6.30390406e-01 4.25137937e-01
9.76502299e-01 -6.99423194e-01 -6.01451337e-01 4.48127657e-01
-1.79853404e+00 6.88068122e-02 5.34485877e-01 1.05087468e-02
-4.35028821e-01 2.50085443e-01 -1.00369143e+00 -4.10820693e-01
-4.25723135e-01 -1.26177454e+00 7.01704860e-01 1.85235497e-02
-6.51893318e-01 -8.35823774e-01 -7.48058781e-02 4.69070196e-01
3.42248380e-01 -1.82275549e-01 1.69149554e+00 -1.00857508e+00
-4.95336860e-01 1.73161849e-01 -4.64506686e-01 2.58221805e-01
2.30386361e-01 -6.90481126e-01 -7.64935017e-01 1.28216539e-02
6.58869982e-01 -3.20473373e-01 6.88193083e-01 -1.45649523e-01
9.69419658e-01 -9.89909410e-01 1.56586468e-01 6.00538254e-01
1.49556768e+00 6.03939354e-01 7.78406262e-01 6.02655590e-01
6.37283087e-01 7.68415749e-01 6.03134453e-01 -6.73254579e-02
6.01566911e-01 7.24034071e-01 9.10166204e-02 4.04241204e-01
8.83684233e-02 -4.66707200e-01 2.63123184e-01 1.28081858e+00
2.05892444e-01 -8.48903880e-02 -9.96076226e-01 5.55532098e-01
-1.76397562e+00 -9.94348705e-01 -1.54445395e-01 1.72721469e+00
1.28558815e+00 1.25646278e-01 -3.69822145e-01 2.66503748e-02
5.09072900e-01 -2.00605631e-01 4.52440940e-02 -6.86360776e-01
-5.50857484e-01 4.25366104e-01 -1.24967173e-01 9.70374405e-01
-1.13212502e+00 1.52469325e+00 5.31268835e+00 5.89452863e-01
-1.03289831e+00 4.51430589e-01 3.16191077e-01 6.37082875e-01
-5.61966717e-01 2.70025939e-01 -8.36697519e-01 5.86967289e-01
3.86377692e-01 -1.66116700e-01 5.83594203e-01 8.15039754e-01
-3.16462100e-01 4.18031886e-02 -1.14087260e+00 7.01221049e-01
7.51062572e-01 -1.07988429e+00 3.99720013e-01 -5.58972657e-01
9.31358278e-01 -3.18580240e-01 -1.25765786e-01 2.29258135e-01
-1.22561172e-01 -1.04492128e+00 7.38840520e-01 -6.84503019e-02
5.65204442e-01 -8.38417709e-01 1.22036445e+00 5.13867497e-01
-7.74592757e-01 -2.32593805e-01 -6.97571278e-01 -6.12285852e-01
2.55410168e-02 -2.12744206e-01 -6.36978626e-01 3.80319476e-01
5.21607339e-01 5.86742222e-01 -7.54742861e-01 5.70546269e-01
-8.82788301e-01 3.15165251e-01 2.43732333e-01 -2.03034848e-01
2.94531405e-01 -2.68942416e-01 4.46476281e-01 1.20719612e+00
1.18638404e-01 3.55779856e-01 1.73247218e-01 1.24511266e+00
-8.09619054e-02 4.98995155e-01 -4.45056498e-01 3.88341129e-01
5.40864348e-01 7.21563637e-01 -3.70955616e-01 -3.96661401e-01
-3.98836553e-01 1.31550193e+00 6.36972845e-01 1.20328821e-01
-6.92761302e-01 -2.74518907e-01 4.85512108e-01 -1.08188801e-01
1.24066599e-01 2.64292657e-01 -8.16377044e-01 -1.38811314e+00
1.69954598e-01 -1.47038722e+00 7.82805264e-01 -7.53142178e-01
-1.72393858e+00 8.30078185e-01 -3.44693437e-02 -1.26681507e+00
-2.24432722e-01 -8.45611632e-01 -8.52328181e-01 9.73112226e-01
-1.35420680e+00 -1.09852159e+00 -1.71977878e-01 3.81850213e-01
1.14574373e+00 -2.11867258e-01 1.12832212e+00 3.96067590e-01
-2.17127502e-01 6.88826144e-01 -5.99524856e-01 6.35214388e-01
6.26281917e-01 -1.28387415e+00 3.90881330e-01 9.51071560e-01
9.85800996e-02 9.76388752e-01 4.94601756e-01 -7.82099485e-01
-5.10979831e-01 -5.65851808e-01 1.79800761e+00 -9.02942896e-01
5.55074513e-01 -1.56678200e-01 -1.19736242e+00 8.68858993e-01
6.05393529e-01 -7.72969484e-01 7.19517469e-01 1.21974923e-01
-6.80328488e-01 1.41084820e-01 -7.61643291e-01 7.31749594e-01
9.29198384e-01 -5.26287794e-01 -1.20687294e+00 1.77360013e-01
8.86411130e-01 -7.09889829e-01 -1.46618187e-01 4.34950441e-01
2.46479839e-01 -6.98503196e-01 4.99104232e-01 -1.29120147e+00
1.01356745e+00 -5.39014697e-01 -2.02643663e-01 -1.31018531e+00
-2.90634364e-01 -3.63029897e-01 3.81150097e-01 1.11545277e+00
7.85913587e-01 -1.81073204e-01 3.87454629e-01 5.06081820e-01
-1.94929644e-01 -4.32932109e-01 -9.08843517e-01 -5.31749129e-01
5.11894226e-01 -2.84535587e-01 8.42125773e-01 1.30058551e+00
7.02069879e-01 1.01422036e+00 -3.57143968e-01 -1.15749925e-01
6.42847642e-02 3.42227370e-01 3.39814216e-01 -9.11787868e-01
-3.33244532e-01 -6.20494604e-01 -1.01156764e-01 -1.18547142e+00
5.78248560e-01 -1.15417695e+00 -5.30317985e-02 -8.39715004e-01
4.54298764e-01 -4.62006211e-01 -1.02281511e-01 2.25367442e-01
-6.04388535e-01 -1.62284318e-02 4.03597891e-01 -3.87909599e-02
-5.38854539e-01 2.06942409e-01 1.25269568e+00 -1.84974939e-01
-5.06292768e-02 -2.06617638e-01 -9.68258619e-01 7.77041495e-01
8.68748307e-01 -5.90774179e-01 -2.67412990e-01 -9.34555471e-01
6.16292119e-01 -7.35602304e-02 -3.25030473e-04 -3.38928699e-01
2.30313912e-01 -4.07461613e-01 1.62926376e-01 -4.61714119e-01
-1.47724897e-01 -8.88052106e-01 -7.01289400e-02 3.99217397e-01
-5.01800716e-01 9.02162135e-01 -2.15437621e-01 -1.45192310e-01
-3.13512355e-01 -6.60471261e-01 7.58518279e-01 -6.60166025e-01
-7.57520616e-01 -3.45308542e-01 -7.08889589e-02 7.30395079e-01
4.05722827e-01 1.89986572e-01 -6.78709447e-01 -3.42803478e-01
-3.37364107e-01 1.80462435e-01 3.51185501e-01 8.28120112e-01
8.71634722e-01 -1.38212907e+00 -8.08122694e-01 5.09660125e-01
3.48792791e-01 -1.78206101e-01 2.01138165e-02 7.82698929e-01
-8.49410355e-01 2.55060285e-01 -5.08310199e-01 2.63889413e-02
-1.06501281e+00 9.28206265e-01 5.11598945e-01 -3.36444885e-01
-5.69371581e-01 8.14875007e-01 3.05960000e-01 -6.32978320e-01
3.76914889e-02 -1.19735658e-01 -5.09852946e-01 -2.01791808e-01
9.74624157e-01 -4.02329266e-02 1.22013070e-01 -6.82309806e-01
-5.38991034e-01 5.79697967e-01 -3.36625725e-01 -4.82344814e-02
8.23909998e-01 -2.88746744e-01 -8.81759584e-01 3.45814884e-01
9.56486404e-01 4.94050235e-01 -3.11911374e-01 -1.90758705e-01
5.88994622e-01 -6.03263378e-01 -8.00897300e-01 -1.25884414e+00
-7.49360502e-01 8.78519237e-01 -1.24140404e-01 -2.16095477e-01
1.12030911e+00 2.13144064e-01 9.76771593e-01 3.47822189e-01
3.63228321e-01 -1.16048574e+00 1.88408270e-02 1.23120117e+00
1.00734901e+00 -1.26756692e+00 -4.86427784e-01 -6.83789194e-01
-1.26709759e+00 1.13434076e+00 1.31641173e+00 -3.06722552e-01
4.54926074e-01 1.79381758e-01 7.65213490e-01 -2.20577762e-01
-9.24130440e-01 9.63724852e-02 3.28321993e-01 5.73420525e-01
7.87559211e-01 2.25072116e-01 -1.22813046e+00 1.33940506e+00
-7.46926904e-01 -5.90076506e-01 5.88089943e-01 4.06887531e-01
-2.61076331e-01 -1.27809191e+00 7.27128610e-02 5.37830219e-02
-6.99118078e-01 -6.11261010e-01 -8.35271657e-01 5.26999414e-01
3.16335410e-01 8.47877800e-01 8.41539353e-02 -3.30287457e-01
1.51943147e-01 3.31163853e-01 3.63238871e-01 -7.38996327e-01
-8.22190881e-01 -8.37511122e-02 1.96526229e-01 -2.99786866e-01
-1.18373364e-01 -3.44977349e-01 -1.35597539e+00 -1.79252669e-01
-3.56595665e-01 2.62398750e-01 -7.94117972e-02 1.28105891e+00
-9.34794173e-02 1.23880915e-01 4.75298524e-01 2.40705535e-01
-5.15911758e-01 -1.24251616e+00 -1.99266359e-01 1.06574476e+00
5.21552050e-03 -4.75606829e-01 -1.21051446e-01 -3.19787860e-02] | [10.885123252868652, 9.202057838439941] |
dfc1b04b-cc51-4c55-a4a8-bbabd7d2e887 | ynu-hpcc-at-semeval-2021-task-5-using-a | null | null | https://aclanthology.org/2021.semeval-1.112 | https://aclanthology.org/2021.semeval-1.112.pdf | YNU-HPCC at SemEval-2021 Task 5: Using a Transformer-based Model with Auxiliary Information for Toxic Span Detection | Toxic span detection requires the detection of spans that make a text toxic instead of simply classifying the text. In this paper, a transformer-based model with auxiliary information is proposed for SemEval-2021 Task 5. The proposed model was implemented based on the BERT-CRF architecture. It consists of three parts: a transformer-based model that can obtain the token representation, an auxiliary information module that combines features from different layers, and an output layer used for the classification. Various BERT-based models, such as BERT, ALBERT, RoBERTa, and XLNET, were used to learn contextual representations. The predictions of these models were assembled to improve the sequence labeling tasks by using a voting strategy. Experimental results showed that the introduced auxiliary information can improve the performance of toxic spans detection. The proposed model ranked 5th of 91 in the competition. The code of this study is available at https://github.com/Chenrj233/semeval2021{\_}task5 | ['Xuejie Zhang', 'Jin Wang', 'Ruijun Chen'] | 2021-08-01 | null | null | null | semeval-2021 | ['toxic-spans-detection'] | ['natural-language-processing'] | [ 1.67992979e-01 8.58792961e-02 -9.64134783e-02 -4.36128765e-01
-8.39576900e-01 -3.51518720e-01 5.76423287e-01 3.03149998e-01
-5.71840107e-01 9.55465078e-01 3.60258073e-01 -2.71139860e-01
4.13529754e-01 -6.62683845e-01 -6.09372735e-01 -5.67911625e-01
2.54482418e-01 3.94412369e-01 5.17624676e-01 -6.33397549e-02
6.14747643e-01 3.27633798e-01 -1.25659239e+00 8.53029191e-01
1.11479521e+00 1.03030479e+00 4.96810377e-01 5.95619559e-01
-2.48308823e-01 1.02856612e+00 -7.14898944e-01 -2.02522337e-01
-1.35442361e-01 -4.54950303e-01 -1.00611663e+00 -3.60780448e-01
-4.24607173e-02 1.34166833e-02 -1.74210995e-01 7.35519469e-01
5.34294486e-01 2.49631241e-01 6.62208080e-01 -1.16872418e+00
-5.18066227e-01 1.24245501e+00 -3.82475615e-01 2.62281537e-01
2.47404590e-01 -3.49873565e-02 1.16913652e+00 -1.05963409e+00
3.85058612e-01 1.27922249e+00 6.26468301e-01 4.34250265e-01
-7.32968330e-01 -7.74983883e-01 2.47618318e-01 6.77179754e-01
-1.25486565e+00 -2.97787309e-01 5.54133236e-01 -4.67434704e-01
1.20375705e+00 1.63373724e-01 4.91076946e-01 1.27620232e+00
2.90841073e-01 1.25017464e+00 1.28440201e+00 -5.87544143e-01
4.46801931e-02 -4.42325361e-02 7.74191439e-01 6.52216434e-01
-1.81769282e-02 -1.42902017e-01 -6.70361221e-01 2.93939840e-03
2.47072242e-02 -1.19084187e-01 -1.14473902e-01 4.19083834e-01
-9.35244560e-01 6.87021017e-01 5.15239358e-01 4.48486567e-01
-2.16532275e-01 -1.25728669e-02 5.66026986e-01 -7.04949424e-02
7.04976082e-01 2.47598648e-01 -5.85761368e-01 -8.50384459e-02
-1.02999699e+00 1.58499449e-01 5.65804303e-01 1.03561640e+00
4.11808431e-01 -1.44367591e-01 -7.92504847e-01 7.88443983e-01
4.81909126e-01 1.98481053e-01 5.21347702e-01 -2.50013351e-01
7.51547515e-01 6.85034513e-01 2.75320164e-03 -3.18256497e-01
-7.74890840e-01 -3.49308550e-01 -5.81125855e-01 -1.64277881e-01
3.16176534e-01 -1.70144245e-01 -1.25169730e+00 1.65320933e+00
5.08294255e-02 2.42567271e-01 -3.02828938e-01 5.67665279e-01
1.03579986e+00 5.80846429e-01 4.42215204e-01 -2.32482851e-02
1.49509096e+00 -1.32386565e+00 -7.94267237e-01 -2.56312601e-02
8.36626112e-01 -1.01049972e+00 1.02315485e+00 4.39124942e-01
-7.72489488e-01 -5.32243669e-01 -1.13222015e+00 -3.78215373e-01
-6.03062630e-01 4.59834009e-01 1.68649957e-01 5.15261352e-01
-9.00185823e-01 6.73661470e-01 -6.92493439e-01 -3.07144552e-01
2.89430380e-01 -6.37581050e-02 -5.39291045e-03 6.43005595e-02
-1.64013660e+00 1.07387364e+00 8.40110540e-01 -1.68598170e-04
-9.94528651e-01 -3.88329893e-01 -7.76830733e-01 1.57159731e-01
1.80345237e-01 -3.50785285e-01 1.33847117e+00 -3.97565305e-01
-1.29737282e+00 6.73429132e-01 -1.90770105e-01 -4.60010678e-01
5.85558057e-01 -6.28000617e-01 -3.99586946e-01 -4.06001508e-02
1.48754880e-01 5.02617538e-01 4.92921710e-01 -8.38756502e-01
-6.86304271e-01 -3.82341415e-01 -1.61008120e-01 1.36147454e-01
-3.31347510e-02 2.00757921e-01 -5.58258116e-01 -6.98855102e-01
-3.33079308e-01 -9.04726386e-01 -1.36100724e-01 -7.78265119e-01
-8.85630071e-01 -7.19747663e-01 6.50513887e-01 -1.05866873e+00
1.49455893e+00 -1.88860095e+00 -2.16307729e-01 4.80270199e-02
-7.60380700e-02 2.41184369e-01 -1.72688052e-01 7.06050098e-01
-1.08253621e-01 3.38859648e-01 -1.58798963e-01 -5.16987205e-01
6.47640377e-02 -3.15630227e-01 -2.13090226e-01 3.26571584e-01
3.03791970e-01 8.48205864e-01 -8.30018878e-01 -6.53376102e-01
1.77352265e-01 3.67802531e-01 -1.09908327e-01 3.66080374e-01
-5.53097904e-01 4.48590398e-01 -3.80969852e-01 5.94678223e-01
6.65773571e-01 -8.43933150e-02 1.05478793e-01 1.11372462e-02
-2.28402019e-01 8.61555815e-01 -8.59898508e-01 1.70742679e+00
-2.82514274e-01 2.99688101e-01 -2.44040281e-01 -8.01782250e-01
1.01962137e+00 4.09059048e-01 2.05930710e-01 -6.30346179e-01
4.21108365e-01 1.11835226e-02 -1.45484805e-01 -4.13115561e-01
7.47228146e-01 1.04368821e-01 -3.22949290e-01 2.60977894e-01
8.64949003e-02 9.86237079e-02 7.03978360e-01 3.87541384e-01
1.33945239e+00 5.09051085e-01 2.49333218e-01 -2.41633549e-01
7.46718585e-01 -9.20947567e-02 9.27287221e-01 4.80726868e-01
-4.04693931e-03 4.37961131e-01 5.38294137e-01 -1.95167080e-01
-9.74779904e-01 -7.43951678e-01 -1.26896322e-01 1.10025692e+00
5.50263077e-02 -8.51185799e-01 -7.17632353e-01 -9.54424858e-01
-2.27716640e-01 1.28355408e+00 -6.46646857e-01 -9.01925862e-02
-3.90204251e-01 -6.10680163e-01 7.93699324e-01 7.91606665e-01
4.75568146e-01 -1.47943568e+00 -4.44677085e-01 2.22559094e-01
-5.98841846e-01 -9.79530036e-01 -5.28883159e-01 7.18090415e-01
-6.79130316e-01 -1.09441435e+00 -3.36345077e-01 -6.33017123e-01
4.36453849e-01 -1.67877927e-01 1.04233968e+00 1.51528791e-01
-3.05550843e-01 -3.81449312e-01 -8.46861303e-01 -6.24309123e-01
-3.11887652e-01 3.08774501e-01 -3.12620848e-01 -2.98066705e-01
5.65871835e-01 -3.36872488e-01 -4.49113965e-01 3.20042104e-01
-7.59370744e-01 2.07285270e-01 7.49863625e-01 8.94949973e-01
4.54630464e-01 -2.97667801e-01 7.84931660e-01 -1.24110413e+00
5.87006509e-01 -4.55515593e-01 -2.66928256e-01 1.68753356e-01
-7.06822872e-01 2.20142171e-01 7.98021376e-01 -1.28792658e-01
-1.24522686e+00 2.56871313e-01 -7.00889409e-01 -1.27815768e-01
-1.12355076e-01 5.35984993e-01 -5.78815401e-01 7.35319555e-01
5.23998916e-01 2.08183959e-01 -5.48156857e-01 -9.38522935e-01
4.28107947e-01 1.00552094e+00 1.77291125e-01 -5.16483128e-01
4.65707093e-01 -1.77164689e-01 -3.75639230e-01 -5.80064654e-01
-1.00149953e+00 -6.26377702e-01 -9.94854212e-01 -1.20211221e-01
8.01210523e-01 -9.65230107e-01 -3.06048810e-01 7.07036018e-01
-1.26436543e+00 -3.41072381e-01 -1.59375936e-01 3.89831066e-01
-3.77733946e-01 3.80862951e-01 -9.23650324e-01 -7.87724495e-01
-6.73135817e-01 -8.96649659e-01 8.75683188e-01 3.10853899e-01
-1.98179483e-01 -6.13109648e-01 1.64038077e-01 6.11299694e-01
6.94164410e-02 6.61181360e-02 1.09353065e+00 -1.08665502e+00
-1.97874606e-01 -6.33897707e-02 -1.64712995e-01 2.94419467e-01
-1.22064732e-01 5.75415567e-02 -1.24911678e+00 -7.81908110e-02
-4.57302213e-01 -5.68817079e-01 1.38253319e+00 1.48134023e-01
1.38242245e+00 -1.90626934e-01 -5.05254149e-01 2.85462648e-01
1.24058104e+00 2.88854986e-01 9.13264394e-01 3.63735825e-01
6.06414974e-01 3.13114405e-01 9.04678047e-01 6.71024859e-01
2.78672963e-01 5.27768433e-01 4.83158708e-01 8.46745372e-02
-2.11603239e-01 -3.66494060e-01 6.15787327e-01 8.89573932e-01
9.31964144e-02 -5.21362185e-01 -8.69758904e-01 5.47268271e-01
-1.89116943e+00 -9.73420560e-01 -4.61632073e-01 1.83123064e+00
1.02514398e+00 4.34724092e-01 1.34312570e-01 3.47289890e-01
8.86559308e-01 1.81581914e-01 -4.78712499e-01 -7.82764494e-01
5.87987714e-02 1.80324554e-01 2.95626104e-01 2.66875952e-01
-1.30663407e+00 1.15013242e+00 5.43707132e+00 1.12630749e+00
-7.93963850e-01 2.70013243e-01 5.70961177e-01 2.09389552e-01
-2.13407934e-01 -3.97427194e-02 -1.10703242e+00 6.75443530e-01
1.20319533e+00 -5.66599593e-02 -8.53069425e-02 8.32764506e-01
3.50559682e-01 -1.69816822e-01 -1.03446221e+00 4.26795810e-01
9.03890580e-02 -1.08525336e+00 -6.57033846e-02 -2.76260614e-01
3.52441311e-01 1.37690574e-01 -2.12410033e-01 6.91612899e-01
5.52303016e-01 -1.06761038e+00 9.67989385e-01 7.12575078e-01
6.84479535e-01 -7.94933558e-01 9.17672276e-01 5.10593891e-01
-1.30297375e+00 -3.63020301e-02 -3.84244442e-01 -6.32298067e-02
4.21982110e-02 9.57115233e-01 -1.04728162e+00 8.36109459e-01
6.21787190e-01 8.60229135e-01 -7.70852625e-01 1.26272941e+00
-8.17297339e-01 9.84018445e-01 -4.53598723e-02 -2.56936640e-01
7.73485526e-02 -2.94877402e-02 3.29274267e-01 1.69648957e+00
1.81929737e-01 -1.54778197e-01 3.16312522e-01 6.69637859e-01
-4.21876758e-01 4.82497185e-01 -3.26506436e-01 -2.14998703e-02
6.16248965e-01 1.53282821e+00 -9.53673422e-01 -4.52522427e-01
-3.30391169e-01 7.57513165e-01 5.46134293e-01 -2.95670182e-02
-1.01735520e+00 -7.00986803e-01 -1.38282944e-02 -6.16434216e-02
4.73617136e-01 -2.68784873e-02 -5.33992529e-01 -9.93009806e-01
-6.54929131e-02 -6.68089271e-01 5.78061640e-01 -7.35037506e-01
-1.19799638e+00 8.19715738e-01 -1.68992355e-01 -1.13825417e+00
3.16670425e-02 -5.25693655e-01 -9.01721001e-01 9.83263195e-01
-1.25695622e+00 -1.26416790e+00 -2.87600011e-01 4.01593715e-01
8.58686805e-01 6.80765063e-02 8.37815106e-01 2.04385191e-01
-8.40663433e-01 6.67101085e-01 2.84667641e-01 2.87489653e-01
8.57804596e-01 -1.41580439e+00 4.89272952e-01 1.03202450e+00
-3.76802273e-02 2.81070322e-01 4.56350446e-01 -9.10185635e-01
-6.31552696e-01 -1.49523151e+00 1.30896688e+00 -3.85337502e-01
5.35984576e-01 -5.47244430e-01 -7.65616775e-01 6.91832900e-01
3.86960566e-01 -2.30525166e-01 7.73338675e-01 2.19220549e-01
-4.75775242e-01 1.94204628e-01 -1.01289523e+00 1.67727187e-01
1.06395435e+00 -3.01842153e-01 -8.31813455e-01 2.87737340e-01
8.20905805e-01 -2.78716654e-01 -7.92961419e-01 2.89362639e-01
2.86782980e-01 -6.17151201e-01 5.52884698e-01 -4.93542850e-01
6.32178783e-01 -1.71484381e-01 -2.05118321e-02 -1.41451490e+00
-6.11701548e-01 -2.69542411e-02 -2.01492146e-01 1.53553307e+00
7.64611185e-01 -1.88427329e-01 4.53685939e-01 1.16919033e-01
-5.69143653e-01 -9.06408727e-01 -8.10105741e-01 -8.91667545e-01
2.58378655e-01 -3.83689433e-01 4.79689032e-01 5.85382104e-01
3.20388108e-01 8.58386934e-01 -3.79224449e-01 -1.12452172e-01
3.10259432e-01 8.68192911e-02 1.97460920e-01 -1.16535008e+00
1.88175086e-02 -2.51322538e-01 -1.01973891e-01 -1.00360560e+00
2.24466637e-01 -1.22431278e+00 4.55757469e-01 -1.78804588e+00
3.96701902e-01 -3.55162233e-01 -7.40368724e-01 9.31523919e-01
-4.82340485e-01 1.39073327e-01 3.11298966e-01 6.67192861e-02
-8.02148104e-01 7.26739526e-01 9.30363059e-01 -3.23169976e-01
-3.60190533e-02 1.04335047e-01 -6.16186082e-01 6.44047856e-01
1.26569235e+00 -5.91841400e-01 -2.18550250e-01 -6.46159872e-02
-2.74686571e-02 -1.44220889e-01 -1.24857806e-01 -9.85903263e-01
8.91627092e-03 -1.80409607e-02 8.05505991e-01 -1.25562859e+00
1.49705231e-01 -3.86579692e-01 -1.29506052e-01 7.02467918e-01
-5.68220496e-01 2.43016779e-02 1.56055436e-01 3.96949917e-01
3.57127525e-02 -5.53137839e-01 8.29903722e-01 -1.01288512e-01
-6.26096129e-01 1.65600404e-01 -5.67525923e-01 1.19911045e-01
9.45341170e-01 3.44559282e-01 -5.26710570e-01 4.24399376e-02
-7.10950732e-01 4.16081756e-01 1.20984845e-01 4.66917366e-01
5.42569041e-01 -1.05570495e+00 -8.71995449e-01 -2.91572332e-01
1.99743882e-01 -1.91324517e-01 1.30875215e-01 8.79213810e-01
-3.29118192e-01 5.77313721e-01 -2.98588425e-01 -2.15017676e-01
-1.45502591e+00 6.49838150e-01 -9.57318582e-03 -1.02121294e+00
-5.47662973e-01 8.25304210e-01 -1.54807139e-02 -5.37023604e-01
3.43356639e-01 -3.25225204e-01 -6.93183839e-01 1.13065124e-01
5.54057300e-01 4.96745646e-01 3.51086795e-01 -6.11392319e-01
-6.21500790e-01 1.10253297e-01 -4.03581768e-01 3.91394868e-02
1.29645932e+00 -1.25793498e-02 -7.66341984e-02 4.62729782e-01
8.09284866e-01 -6.19207583e-02 -9.47423398e-01 -3.99075478e-01
4.23792750e-01 -1.44624770e-01 -1.07326962e-01 -1.28833282e+00
-7.84062207e-01 1.07413089e+00 3.31053793e-01 -1.39928073e-01
1.12478089e+00 -1.45796761e-01 8.07672858e-01 1.23522550e-01
3.06510031e-01 -1.29346013e+00 1.79440696e-02 9.59315896e-01
9.61862743e-01 -8.13691378e-01 -5.38304634e-02 -3.50853652e-01
-6.83840215e-01 1.01496112e+00 8.09348464e-01 7.81575590e-02
5.01199543e-01 1.53907567e-01 -1.59719929e-01 1.29084542e-01
-1.07259583e+00 -3.48809749e-01 2.21053213e-01 4.59622800e-01
7.18914390e-01 8.09519365e-02 -1.02828920e+00 1.15414178e+00
-1.72052652e-01 1.95289999e-02 3.41678232e-01 9.83287454e-01
-7.40966320e-01 -1.31502807e+00 -1.65197417e-01 6.65204048e-01
-5.86608648e-01 -3.54742974e-01 -6.06200814e-01 5.01498818e-01
3.92918855e-01 1.14236629e+00 -2.80194908e-01 -6.84963882e-01
2.99537838e-01 6.65479898e-01 1.36658266e-01 -8.40161502e-01
-8.89259160e-01 4.17435579e-02 4.75922227e-01 -4.33774531e-01
-1.06743477e-01 -4.82695311e-01 -1.51423168e+00 -1.43746302e-01
-4.29045737e-01 5.99315584e-01 5.92293262e-01 9.40573871e-01
1.88588977e-01 7.95429170e-01 6.23220921e-01 -5.38291991e-01
-4.45056021e-01 -1.69037116e+00 -6.36807621e-01 2.83816606e-01
-1.50991753e-01 -6.38713479e-01 -1.10728972e-01 1.40064836e-01] | [8.985345840454102, 10.564370155334473] |
f630a55f-0168-4727-a84a-3b94bffdb4f1 | disentanglement-in-a-gan-for-unconditional | 2307.01673 | null | https://arxiv.org/abs/2307.01673v1 | https://arxiv.org/pdf/2307.01673v1.pdf | Disentanglement in a GAN for Unconditional Speech Synthesis | Can we develop a model that can synthesize realistic speech directly from a latent space, without explicit conditioning? Despite several efforts over the last decade, previous adversarial and diffusion-based approaches still struggle to achieve this, even on small-vocabulary datasets. To address this, we propose AudioStyleGAN (ASGAN) -- a generative adversarial network for unconditional speech synthesis tailored to learn a disentangled latent space. Building upon the StyleGAN family of image synthesis models, ASGAN maps sampled noise to a disentangled latent vector which is then mapped to a sequence of audio features so that signal aliasing is suppressed at every layer. To successfully train ASGAN, we introduce a number of new techniques, including a modification to adaptive discriminator augmentation which probabilistically skips discriminator updates. We apply it on the small-vocabulary Google Speech Commands digits dataset, where it achieves state-of-the-art results in unconditional speech synthesis. It is also substantially faster than existing top-performing diffusion models. We confirm that ASGAN's latent space is disentangled: we demonstrate how simple linear operations in the space can be used to perform several tasks unseen during training. Specifically, we perform evaluations in voice conversion, speech enhancement, speaker verification, and keyword classification. Our work indicates that GANs are still highly competitive in the unconditional speech synthesis landscape, and that disentangled latent spaces can be used to aid generalization to unseen tasks. Code, models, samples: https://github.com/RF5/simple-asgan/ | ['Herman Kamper', 'Matthew Baas'] | 2023-07-04 | null | null | null | null | ['voice-conversion', 'image-generation', 'disentanglement', 'voice-conversion', 'speech-enhancement', 'speaker-verification', 'speech-synthesis'] | ['audio', 'computer-vision', 'methodology', 'speech', 'speech', 'speech', 'speech'] | [ 5.19297838e-01 3.02797735e-01 -1.52737141e-01 -1.45124659e-01
-1.39816916e+00 -9.86888647e-01 9.15819168e-01 -8.46289337e-01
4.23280485e-02 7.17569649e-01 6.18019283e-01 -5.78238368e-01
3.02422673e-01 -5.65334976e-01 -8.21522176e-01 -7.97517240e-01
1.53246462e-01 4.04182106e-01 -2.50958890e-01 -3.29090476e-01
-4.56398010e-01 3.50093484e-01 -1.14274073e+00 2.91032046e-01
5.90250015e-01 4.56586480e-01 -1.26175344e-01 1.05667043e+00
2.33021364e-01 7.54858255e-01 -8.59450638e-01 -4.54289317e-01
3.86414111e-01 -7.21712649e-01 -4.88004893e-01 -6.16655536e-02
3.67078245e-01 -5.97315431e-01 -7.69555271e-01 9.36414897e-01
8.42049301e-01 -7.24690259e-02 7.02269435e-01 -1.28168440e+00
-1.08069003e+00 9.54084396e-01 9.17431638e-02 -1.90658737e-02
1.90945342e-01 6.39806092e-01 1.01725996e+00 -9.21832979e-01
5.29711246e-01 1.43009770e+00 5.35922587e-01 1.07545066e+00
-1.51337206e+00 -1.14720023e+00 4.91766818e-02 -3.99890751e-01
-1.26724422e+00 -9.96446848e-01 8.37352097e-01 -4.39102262e-01
9.24885333e-01 4.99926180e-01 3.46042573e-01 2.12279272e+00
-2.57867455e-01 1.00388384e+00 1.11283994e+00 -2.88577706e-01
1.33550659e-01 5.36873266e-02 -5.02462447e-01 5.76218426e-01
-2.41254061e-01 6.04052961e-01 -6.20834470e-01 -2.56377876e-01
6.90290987e-01 -3.56025100e-01 -5.67649186e-01 -1.68450549e-01
-1.42936027e+00 1.12767649e+00 2.53310233e-01 1.48194596e-01
-1.04913890e-01 5.40889978e-01 2.30254665e-01 5.82627773e-01
7.71395564e-01 5.14425755e-01 -1.94750622e-01 -2.03768134e-01
-1.11479342e+00 2.14813471e-01 9.25268412e-01 9.05527711e-01
3.35879713e-01 7.84890950e-01 -3.07034373e-01 7.06580818e-01
3.04663032e-01 8.18957925e-01 5.09243667e-01 -9.94491458e-01
5.62294006e-01 -2.00212285e-01 -3.57594460e-01 -3.78780156e-01
3.90884578e-01 -5.99777400e-01 -9.41642165e-01 3.61825973e-01
1.34171456e-01 -5.21647334e-01 -1.25840294e+00 2.05458927e+00
-1.24629214e-01 5.39137602e-01 4.29051131e-01 6.96325183e-01
6.24646366e-01 8.83959532e-01 -1.71140164e-01 1.45548925e-01
9.19976354e-01 -1.03178585e+00 -6.88967764e-01 -4.48411435e-01
1.85190782e-01 -8.43036234e-01 1.17658615e+00 4.43312913e-01
-1.21177089e+00 -3.66623998e-01 -1.30270362e+00 -7.14204311e-02
-2.57516831e-01 2.76946146e-02 5.96294761e-01 1.02100039e+00
-1.26090813e+00 4.73639280e-01 -9.70019400e-01 9.27325934e-02
4.15220708e-01 3.49185258e-01 -4.14673328e-01 -1.71505138e-01
-1.37646770e+00 5.69788277e-01 1.96818467e-02 -1.50348410e-01
-1.62033176e+00 -7.52616704e-01 -9.90480185e-01 9.25598480e-03
1.67298481e-01 -1.03253615e+00 1.35996830e+00 -9.99508560e-01
-2.08423305e+00 5.26862323e-01 4.16680425e-02 -5.68105757e-01
6.13989770e-01 -6.42125309e-02 -5.75520456e-01 -5.29797785e-02
-9.13358852e-02 8.35709870e-01 1.49547255e+00 -1.13639855e+00
2.44346224e-02 -3.96074355e-03 -1.10226497e-01 1.43718213e-01
-4.20125157e-01 -1.40546322e-01 -3.20416361e-01 -1.21833551e+00
-1.77805230e-01 -1.16255999e+00 -7.17322752e-02 -1.99405208e-01
-5.87369382e-01 7.83337355e-02 9.13417459e-01 -7.65773356e-01
7.78544664e-01 -2.35619593e+00 5.69108963e-01 -2.48183571e-02
3.55900258e-01 2.40262479e-01 -4.44104970e-01 3.81437153e-01
-3.09396803e-01 4.18621838e-01 -3.26084048e-01 -9.75378275e-01
3.34033012e-01 2.75498182e-01 -8.67816031e-01 3.75120461e-01
3.72989982e-01 1.04052830e+00 -7.63527155e-01 1.98505238e-01
-5.85468933e-02 9.10778284e-01 -7.92429566e-01 3.01314384e-01
-4.22813714e-01 6.76655948e-01 -5.96011931e-04 3.55005711e-01
4.19777691e-01 -7.80890658e-02 8.80514011e-02 5.42836785e-02
3.06479633e-01 6.41884446e-01 -7.95070767e-01 2.02861762e+00
-6.17869318e-01 9.74485755e-01 2.24221870e-01 -7.57603705e-01
7.31695652e-01 6.86257958e-01 3.25823016e-02 -2.23901838e-01
-3.56848575e-02 3.17381948e-01 -9.79536846e-02 -2.65020784e-02
1.35042921e-01 -3.04129779e-01 -1.13496415e-01 4.73934621e-01
4.50441003e-01 -6.48484349e-01 -3.97194535e-01 4.45929408e-01
1.23875368e+00 -4.15835865e-02 -1.36825249e-01 9.84461233e-02
3.18353586e-02 -4.45357203e-01 1.69784352e-01 7.55051792e-01
1.28470168e-01 8.53524923e-01 5.16119123e-01 2.28344038e-01
-1.16168833e+00 -1.57846904e+00 2.69436449e-01 9.79203999e-01
-5.13831735e-01 -3.62652600e-01 -7.84582675e-01 -7.44914591e-01
-3.46929058e-02 9.73067880e-01 -5.62867105e-01 -2.77186275e-01
-4.04921561e-01 -3.92339826e-01 1.19835436e+00 4.64227796e-01
2.02548251e-01 -8.63918066e-01 3.83977234e-01 -1.00085028e-02
7.09026530e-02 -1.07911861e+00 -8.78024638e-01 3.55421513e-01
-5.57393909e-01 -3.74858290e-01 -1.06094646e+00 -5.68027556e-01
3.50243270e-01 -6.69703335e-02 1.13701737e+00 -4.10905957e-01
9.36336443e-02 4.83837187e-01 -1.37873247e-01 -2.62613118e-01
-1.11486101e+00 3.01426768e-01 2.35834777e-01 -1.60280377e-01
-4.37052809e-02 -9.36307490e-01 -4.88529503e-01 1.67279974e-01
-9.33519006e-01 4.15334059e-03 5.04248679e-01 1.07144094e+00
2.46184021e-01 -2.12824911e-01 6.12063169e-01 -7.73766160e-01
9.81325150e-01 -5.60123861e-01 -4.77891356e-01 7.67588266e-04
-4.39389288e-01 3.58396471e-01 4.87521797e-01 -7.14033663e-01
-7.26038396e-01 -7.33306780e-02 -5.85206807e-01 -8.05438042e-01
-2.11897902e-02 2.75202483e-01 -3.87831807e-01 1.47786826e-01
8.77465725e-01 3.83213669e-01 2.33616456e-01 -3.76644075e-01
9.54671323e-01 7.53160119e-01 5.78443825e-01 -4.46365923e-01
1.04618919e+00 2.83490062e-01 -4.62793410e-01 -7.06896007e-01
-4.62759525e-01 6.71763346e-02 -8.86777341e-02 2.74194688e-01
7.98124492e-01 -1.37306094e+00 -3.78054023e-01 3.35241497e-01
-1.11333394e+00 -7.93541849e-01 -6.51394546e-01 5.23222208e-01
-6.41859770e-01 8.91661197e-02 -6.71862781e-01 -6.41942739e-01
-3.70816261e-01 -1.34073687e+00 1.17645574e+00 -3.21694493e-01
-3.21324229e-01 -1.12431967e+00 1.91237792e-01 3.30182761e-01
6.30490065e-01 1.11654460e-01 7.39478946e-01 -7.69791424e-01
-7.60515153e-01 3.61312963e-02 2.74774253e-01 9.14967954e-01
2.08630964e-01 -1.30518124e-01 -1.31604612e+00 -5.29387772e-01
5.50771728e-02 -4.94394630e-01 1.14827335e+00 1.19108945e-01
8.25907946e-01 -6.16727948e-01 -1.35562032e-01 1.05053246e+00
7.70473838e-01 6.07745163e-03 6.04078531e-01 -2.96453297e-01
6.47654116e-01 5.06844446e-02 -3.31756145e-01 -1.49093186e-02
-1.67127699e-02 6.70195401e-01 3.22479069e-01 -2.45067686e-01
-6.86548114e-01 -6.95024312e-01 8.82309437e-01 1.23894930e+00
3.41657192e-01 -6.72374964e-01 -6.23156667e-01 5.32185256e-01
-1.28257525e+00 -1.00201297e+00 4.46099788e-01 1.89222789e+00
1.08777130e+00 2.44447365e-01 -6.40296051e-03 1.64417312e-01
3.13694149e-01 4.78822887e-01 -7.30986595e-01 -2.81964570e-01
-3.33586574e-01 7.67125726e-01 5.36664367e-01 9.73747551e-01
-9.18974459e-01 1.03556728e+00 6.66448736e+00 1.03958762e+00
-1.42475390e+00 5.58059156e-01 5.18566549e-01 -2.62444705e-01
-9.75965083e-01 -1.59287244e-01 -5.93838692e-01 3.21759015e-01
1.08066821e+00 -9.16456729e-02 9.04467046e-01 6.89653933e-01
-1.45306572e-01 7.80841410e-01 -1.21910524e+00 9.45067704e-01
1.44859269e-01 -1.51610839e+00 1.58286497e-01 1.62264839e-01
9.06532764e-01 3.39971095e-01 9.34926748e-01 5.47819138e-01
8.75031292e-01 -1.48112154e+00 6.69262826e-01 8.14540982e-02
1.37466252e+00 -5.52073479e-01 1.70740157e-01 3.20412159e-01
-6.89553857e-01 1.57433122e-01 4.01418917e-02 2.75534242e-01
1.85499266e-01 3.14316720e-01 -1.15471411e+00 3.04320127e-01
1.66264251e-01 5.26644051e-01 -2.08251670e-01 2.14449048e-01
-7.05252945e-01 1.12371087e+00 -3.81877333e-01 2.69517004e-01
2.94236392e-01 1.84336126e-01 8.77645373e-01 1.09750926e+00
5.78274012e-01 -1.20056078e-01 -2.00117528e-01 1.16703141e+00
-4.40259248e-01 -3.98809701e-01 -9.68156815e-01 -4.72484678e-01
3.60955834e-01 7.64112830e-01 -2.03604445e-01 -2.04492956e-01
-1.86357930e-01 1.43714178e+00 1.02289394e-01 8.35724533e-01
-9.31345284e-01 -2.06038609e-01 1.00523937e+00 -6.23469539e-02
4.00754362e-01 -4.51183379e-01 -1.01685971e-01 -1.52173996e+00
-3.15264195e-01 -1.40336359e+00 -7.90073425e-02 -8.26687753e-01
-1.35314143e+00 9.58418250e-01 -2.23804906e-01 -9.20211911e-01
-7.98006058e-01 -4.01258886e-01 -4.31049794e-01 1.25963426e+00
-1.16671848e+00 -1.29680467e+00 4.84153517e-02 7.68029571e-01
7.65052438e-01 -6.32481515e-01 1.21501660e+00 2.74288416e-01
-3.13973486e-01 9.54022765e-01 2.14352071e-01 2.36799076e-01
7.01100230e-01 -1.25775325e+00 1.18130243e+00 9.94187355e-01
6.71551406e-01 6.27917588e-01 8.05423200e-01 -5.09991825e-01
-1.26992619e+00 -1.05548024e+00 4.45775777e-01 -7.30947733e-01
7.87564158e-01 -9.73613322e-01 -5.31853378e-01 1.07768321e+00
5.91879368e-01 1.31715044e-01 7.23443389e-01 -6.52009100e-02
-7.25952923e-01 1.67064935e-01 -8.24866951e-01 8.11357915e-01
1.15910494e+00 -1.10729921e+00 -3.15944523e-01 4.20023084e-01
1.37973595e+00 -5.38565695e-01 -6.14893734e-01 2.22982913e-01
4.36908156e-01 -6.58083797e-01 1.11643529e+00 -6.96568012e-01
3.03816915e-01 -1.63676012e-02 -4.20326918e-01 -1.75093138e+00
-7.40672871e-02 -1.40842938e+00 -3.02694172e-01 1.26639104e+00
6.30145073e-01 -8.43561888e-01 7.59017169e-01 1.69055045e-01
-2.13151261e-01 -4.93555397e-01 -9.59561765e-01 -8.25551689e-01
3.78286958e-01 -6.55881345e-01 6.89228237e-01 9.93773818e-01
-4.70452070e-01 5.15801370e-01 -6.85764849e-01 3.12329262e-01
5.20595670e-01 -3.67649615e-01 8.75733316e-01 -5.82972527e-01
-8.44741464e-01 -3.24415863e-01 -2.88008302e-01 -1.44171739e+00
4.85050440e-01 -1.08246720e+00 -1.23270720e-01 -1.15382910e+00
-3.62958938e-01 -4.67455715e-01 -8.03087314e-04 5.04732370e-01
6.68498799e-02 4.25141543e-01 2.58257031e-01 1.98630597e-02
7.75084943e-02 7.82128930e-01 1.17415822e+00 -5.24158537e-01
-5.30028343e-02 1.59597918e-01 -8.36175859e-01 4.79603261e-01
7.50513315e-01 -6.40303850e-01 -8.23529661e-01 -5.93411505e-01
-7.10524991e-02 2.22899273e-01 4.94674981e-01 -9.55918610e-01
1.73783392e-01 2.43895903e-01 3.73126082e-02 -3.53710502e-02
8.27099383e-01 -5.38877130e-01 3.89130712e-01 2.69872487e-01
-4.81260091e-01 -1.38891995e-01 2.70204782e-01 6.14614487e-01
-3.07506025e-01 1.60275325e-01 6.09408438e-01 8.35609287e-02
-1.40761793e-01 3.47353667e-01 -3.31975251e-01 1.82975128e-01
6.64255738e-01 2.56534696e-01 -3.60129982e-01 -9.92242336e-01
-1.04829752e+00 -3.04772884e-01 2.92571276e-01 5.42365611e-01
6.80779815e-01 -1.40558958e+00 -9.50230658e-01 6.68702245e-01
-2.35696137e-01 -2.22306073e-01 8.37659091e-02 4.28266019e-01
-2.86049634e-01 3.42282355e-01 1.53146163e-01 -4.96983439e-01
-1.09616530e+00 5.01412094e-01 3.95394772e-01 -1.87682956e-01
-4.46682602e-01 1.24430799e+00 2.93279380e-01 -4.79169786e-01
2.34561637e-01 -4.35767740e-01 4.71290022e-01 -2.65175402e-01
2.35687688e-01 -6.48012534e-02 -5.02227359e-02 -3.99833858e-01
-8.16551670e-02 1.24664500e-01 1.36039063e-01 -7.95457602e-01
1.21368635e+00 1.32752389e-01 3.19189101e-01 3.85582238e-01
1.52464545e+00 6.85532868e-01 -1.54114211e+00 -1.11445606e-01
-6.72387064e-01 -1.75589070e-01 1.01592124e-01 -8.76768887e-01
-1.11701703e+00 1.15686619e+00 5.73632002e-01 2.80539006e-01
9.49569345e-01 -1.03256293e-03 7.54269302e-01 3.17836404e-02
-1.75168943e-02 -2.71545768e-01 2.81770587e-01 4.68515277e-01
1.18777406e+00 -9.38192368e-01 -3.22135746e-01 -1.91050798e-01
-7.13206351e-01 7.70187378e-01 8.80576670e-02 -1.44035786e-01
7.03778684e-01 7.60004282e-01 1.37463957e-01 7.19459280e-02
-8.99264574e-01 8.37873202e-03 3.75883579e-01 7.21625328e-01
2.37419412e-01 1.50384992e-01 4.91617143e-01 4.59475368e-01
-6.37826145e-01 -2.19314426e-01 1.97294042e-01 4.29541975e-01
1.62423864e-01 -1.33464181e+00 -2.26479247e-01 -2.03525908e-02
-5.14632046e-01 -4.97139931e-01 -3.48492146e-01 6.40392184e-01
-1.02969982e-01 9.03571606e-01 -1.00740924e-01 -5.67403376e-01
7.18991607e-02 2.58375615e-01 4.28819865e-01 -7.26742983e-01
-4.55779582e-01 8.65463391e-02 1.37948826e-01 -4.61329728e-01
-6.55917600e-02 -4.84247804e-01 -7.15184927e-01 -3.51109207e-01
-2.02029601e-01 1.93504035e-01 8.17837119e-01 6.44240558e-01
3.91359776e-01 7.62296677e-01 4.82467353e-01 -9.03919756e-01
-1.01081121e+00 -9.37479913e-01 -3.29886466e-01 2.08674297e-01
7.85408199e-01 -2.66291589e-01 -8.27543259e-01 1.05581127e-01] | [15.111006736755371, 6.386163234710693] |
ede90b55-d507-4470-8454-83cabe9ce100 | dynamic-negative-example-construction-for | null | null | https://aclanthology.org/2022.ccl-1.83 | https://aclanthology.org/2022.ccl-1.83.pdf | Dynamic Negative Example Construction for Grammatical Error Correction using Contrastive Learning | “Grammatical error correction (GEC) aims at correcting texts with different types of grammatical errors into natural and correct forms. Due to the difference of error type distribution and error density, current grammatical error correction systems may over-correct writings and produce a low precision. To address this issue, in this paper, we propose a dynamic negative example construction method for grammatical error correction using contrastive learning. The proposed method can construct sufficient negative examples with diverse grammatical errors, and can be dynamically used during model training. The constructed negative examples are beneficial for the GEC model to correct sentences precisely and suppress the model from over-correction. Experimental results show that our proposed method enhances model precision, proving the effectiveness of our method.” | ['Li Xia', 'Zhuang Junbin', 'He Junyi'] | null | null | null | null | ccl-2022-10 | ['grammatical-error-correction'] | ['natural-language-processing'] | [ 1.43067613e-01 1.29975438e-01 -1.40076708e-02 -4.82817024e-01
-5.13464510e-01 -2.52077371e-01 2.48601980e-04 4.47742671e-01
-3.73766959e-01 8.88816178e-01 -3.51049677e-02 -3.48471433e-01
2.17082351e-01 -8.30108523e-01 -6.82082474e-01 -1.91911668e-01
3.42443347e-01 2.59042412e-01 1.03479318e-01 -5.63781381e-01
9.25937414e-01 -3.21924537e-02 -1.54556513e+00 2.66235024e-01
1.87366700e+00 1.24684006e-01 6.12755239e-01 7.63664663e-01
-7.25403309e-01 8.83401632e-01 -1.03579664e+00 -5.09889245e-01
-3.46551538e-01 -5.94223142e-01 -5.77191651e-01 -4.94673073e-01
2.89600164e-01 -6.61661774e-02 3.29390734e-01 1.46634066e+00
4.76548404e-01 -3.99179989e-03 5.45504034e-01 -9.48590219e-01
-9.85738873e-01 8.17777574e-01 -2.44322896e-01 2.45749950e-01
3.37255031e-01 -1.66573137e-01 6.35717630e-01 -1.27097106e+00
4.53504264e-01 1.33829188e+00 9.80182588e-01 1.42180681e+00
-8.08559179e-01 -7.94534504e-01 3.53446752e-01 2.29023948e-01
-1.08508003e+00 -2.12700382e-01 7.62604415e-01 -1.51842818e-01
9.87856388e-01 5.19362867e-01 7.46628284e-01 8.48860383e-01
3.66726458e-01 7.95422912e-01 9.81075227e-01 -1.00618112e+00
9.07760486e-03 3.10324490e-01 5.67417383e-01 7.32513845e-01
4.30407941e-01 -3.90899815e-02 -4.69079643e-01 3.46846022e-02
2.07726270e-01 -1.00745142e-01 -4.65249062e-01 4.17150825e-01
-5.20808280e-01 6.49640679e-01 9.82142165e-02 3.54261220e-01
8.41062590e-02 1.54035896e-01 5.10605097e-01 4.62991267e-01
6.75544083e-01 5.73509932e-01 -7.19137311e-01 -4.70025092e-01
-3.89979810e-01 3.63800615e-01 5.71013093e-01 1.08513105e+00
4.85178083e-01 1.35352477e-01 -1.22579433e-01 1.35877180e+00
5.01148582e-01 8.10780227e-01 7.13637829e-01 -4.63767052e-01
7.06366777e-01 9.36927557e-01 1.15109809e-01 -1.10482657e+00
-3.97107869e-01 -5.12496233e-01 -8.65771234e-01 -2.05148831e-02
2.41216078e-01 3.51398140e-02 -6.27349436e-01 1.68599188e+00
3.26850340e-02 -2.05273867e-01 -2.57907454e-02 6.95108175e-01
8.99564862e-01 6.86646044e-01 5.32519639e-01 -4.48533505e-01
8.28436136e-01 -6.87427700e-01 -1.16257465e+00 -3.70997906e-01
1.41637385e+00 -7.74574697e-01 1.55834520e+00 3.59238237e-01
-9.34769511e-01 -4.34790164e-01 -8.78200471e-01 -4.39208373e-02
-1.69599503e-01 4.21994090e-01 4.30435717e-01 6.89567804e-01
-6.11656129e-01 6.89450383e-01 -3.66363078e-01 -2.72000711e-02
2.90634274e-01 4.40440932e-03 1.61573708e-01 -1.38465285e-01
-1.31913614e+00 1.11165237e+00 4.85211879e-01 2.31457744e-02
-2.20167816e-01 -8.61521363e-01 -7.36670554e-01 9.81989428e-02
-5.43991774e-02 -3.27043742e-01 1.28040957e+00 -1.22727597e+00
-9.37151134e-01 5.19775271e-01 -4.64759707e-01 -8.66160765e-02
3.78858179e-01 -4.37651634e-01 -5.04998803e-01 -5.19428551e-01
-1.84873864e-02 3.55682224e-01 5.47304034e-01 -1.44926810e+00
-8.34250450e-01 -3.71218055e-01 -2.04024404e-01 1.65553704e-01
-4.50799078e-01 1.25121683e-01 -7.33796507e-02 -9.73603547e-01
3.86551887e-01 -5.81157446e-01 8.50961208e-02 -2.89226592e-01
6.30131811e-02 -7.68565774e-01 5.49562216e-01 -9.00276303e-01
1.96190631e+00 -1.84972811e+00 5.95722720e-02 1.48608044e-01
3.56723890e-02 6.99548423e-01 -1.76032931e-01 -5.82627729e-02
-4.41046692e-02 5.42596161e-01 -2.76099414e-01 -5.04300773e-01
-3.33075523e-01 3.55991572e-01 -1.30289078e-01 -1.40261590e-01
2.14365795e-01 6.75299108e-01 -1.38426590e+00 -5.78272343e-01
-1.52904138e-01 1.07000515e-01 -6.01565778e-01 1.68632150e-01
-2.85807520e-01 1.07839100e-01 -1.57826364e-01 7.54597902e-01
8.93301964e-01 1.34064555e-01 1.58581585e-01 3.78864408e-01
1.61356658e-01 5.11909544e-01 -9.93595600e-01 1.12512553e+00
-6.17082775e-01 2.82469809e-01 -4.45212752e-01 -7.12491095e-01
1.39271867e+00 -4.89341803e-02 -4.32756186e-01 -9.40041304e-01
1.13146484e-01 7.46709108e-01 4.14782902e-03 -5.90996921e-01
9.23229039e-01 -1.70244440e-01 6.77620098e-02 4.32464242e-01
5.66958077e-02 -1.14102662e-01 2.36061305e-01 2.79861331e-01
6.94384396e-01 -8.30307752e-02 6.59995899e-02 -3.03105086e-01
8.68934751e-01 -1.23684220e-01 9.61239636e-01 8.27029586e-01
-2.32315958e-01 1.95458338e-01 3.79534513e-01 -2.17021108e-01
-9.37954545e-01 -5.88814795e-01 -2.23127436e-02 9.09216046e-01
6.57465160e-02 -6.81037724e-01 -1.04129958e+00 -1.12501121e+00
-1.95442051e-01 1.23947358e+00 -3.76415819e-01 -5.76160192e-01
-7.86775172e-01 -6.39489353e-01 4.47418958e-01 5.27137935e-01
2.87019998e-01 -1.23889112e+00 8.80667567e-02 3.27007324e-01
-5.19991755e-01 -2.08240092e-01 -4.54664975e-01 -3.67715321e-02
-1.25099611e+00 -1.28388846e+00 -2.18050286e-01 -1.14458311e+00
1.09533143e+00 1.92732349e-01 1.33892095e+00 1.15818095e+00
1.96433440e-01 3.09079960e-02 -8.25439692e-01 -6.63507640e-01
-1.20151722e+00 3.88713032e-02 8.91302601e-02 -6.06405914e-01
5.65580785e-01 -2.15610266e-01 8.78279656e-02 -1.59568980e-01
-5.17779291e-01 1.02073908e-01 1.32578790e-01 1.18587673e+00
4.56952244e-01 -1.49442807e-01 9.58421469e-01 -1.31160498e+00
1.20426941e+00 -2.58376926e-01 -4.01860893e-01 7.40393937e-01
-1.22165394e+00 -4.43001203e-02 9.45909798e-01 -2.70677686e-01
-1.26075149e+00 -4.91275728e-01 -3.68891925e-01 9.50502902e-02
3.07470083e-01 5.30544043e-01 -1.39596000e-01 -1.39268950e-01
7.60198057e-01 4.36763704e-01 -8.33218023e-02 -4.14091468e-01
-1.68115214e-01 7.94567168e-01 3.35766166e-01 -7.07961679e-01
2.88115978e-01 -5.01335979e-01 -1.97323427e-01 -2.68382281e-01
-8.90439808e-01 1.04247384e-01 -3.55573922e-01 -5.98924279e-01
4.54782397e-02 -6.50886059e-01 -2.81705052e-01 8.36840928e-01
-1.73907936e+00 -1.03581876e-01 -2.63710879e-02 3.32466543e-01
-2.05916971e-01 5.38234651e-01 -6.86834455e-01 -1.12158751e+00
-5.78860879e-01 -6.36040747e-01 6.11979544e-01 4.49478626e-01
-2.06266135e-01 -1.17648113e+00 -4.06588875e-02 -6.06026724e-02
3.32125366e-01 -4.14146572e-01 1.28908861e+00 -4.23724592e-01
-2.71543056e-01 -1.30883813e-01 8.68108869e-03 6.83817208e-01
-2.96701249e-02 1.86998844e-01 -5.76752067e-01 1.74830947e-02
-1.10543236e-01 -1.07048780e-01 8.05139542e-01 -9.02415365e-02
1.55084956e+00 -3.36615562e-01 -1.06150180e-01 3.82294744e-01
1.39159989e+00 3.21977854e-01 9.00781691e-01 3.68609190e-01
7.38629997e-01 4.50515866e-01 1.16700554e+00 3.33425403e-01
2.74018437e-01 2.04807207e-01 2.36207515e-01 3.63139540e-01
-2.09205374e-01 -6.44588709e-01 1.91188633e-01 1.44792557e+00
-2.10870896e-02 -5.09656847e-01 -9.55796540e-01 6.22500420e-01
-1.78988731e+00 -9.38576043e-01 -8.31322789e-01 2.09586906e+00
1.32629180e+00 1.75702825e-01 -6.64087057e-01 3.76829952e-01
8.54563594e-01 -4.30855751e-01 -1.76388517e-01 -8.34973752e-01
-2.42921174e-01 3.00956100e-01 1.82140142e-01 7.71779120e-01
-6.73718274e-01 1.01090360e+00 6.37590694e+00 1.05784881e+00
-8.67440462e-01 1.94389477e-01 4.16960150e-01 2.80680239e-01
-8.85181785e-01 -5.10718152e-02 -1.06441426e+00 9.82867718e-01
6.61305070e-01 -1.39738575e-01 2.18243912e-01 7.91681468e-01
3.64600509e-01 -1.59502402e-01 -7.47543454e-01 9.39643741e-01
2.13142008e-01 -1.25127745e+00 2.39056364e-01 -6.14097476e-01
6.44435525e-01 -6.45554304e-01 -3.18539977e-01 7.82378316e-01
1.84232578e-01 -7.98732996e-01 8.46833289e-01 8.75687003e-01
5.38489640e-01 -8.63284707e-01 9.05824840e-01 7.67904937e-01
-4.97445107e-01 -1.85059115e-01 -6.93322837e-01 -4.17589277e-01
-4.70154956e-02 7.24100709e-01 -5.45784354e-01 1.43084794e-01
6.37397051e-01 8.14908981e-01 -1.02879333e+00 8.68614912e-01
-6.89214230e-01 1.04797971e+00 1.38507470e-01 -7.16292381e-01
-4.76815641e-01 -1.80232450e-01 5.00963807e-01 1.24581254e+00
6.31412864e-01 2.67238736e-01 -2.71885812e-01 9.15963590e-01
-1.76397488e-01 4.32780147e-01 -3.35074961e-01 1.83665007e-01
1.15122437e+00 6.98569179e-01 -9.30822715e-02 -5.81402063e-01
-6.74147084e-02 9.25320029e-01 8.26014698e-01 -9.34187323e-02
-8.20882082e-01 -5.74596703e-01 2.22326696e-01 -5.26785180e-02
-3.79265010e-01 1.20062500e-01 -1.05279076e+00 -1.23025215e+00
4.03418213e-01 -7.90551305e-01 4.91094254e-02 -7.98404694e-01
-1.28837574e+00 1.08417504e-01 -4.56017941e-01 -1.18506706e+00
1.26899600e-01 -3.78945142e-01 -8.07688355e-01 9.33382750e-01
-1.46297359e+00 -6.91482723e-01 -3.45262975e-01 8.85621086e-02
6.58104181e-01 -3.24508101e-01 9.32706237e-01 4.69829679e-01
-5.42412281e-01 1.15351570e+00 1.57955408e-01 -1.28535144e-02
7.80468404e-01 -1.37414658e+00 2.79847980e-01 9.91862595e-01
-4.86726463e-01 9.34819281e-01 6.53980911e-01 -1.05123317e+00
-8.52662742e-01 -1.28832364e+00 1.86912537e+00 -2.59332150e-01
1.46986470e-01 -1.33462429e-01 -1.37686133e+00 3.66996557e-01
-3.21294069e-01 -3.08137447e-01 5.76788366e-01 2.61061162e-01
-3.80375266e-01 -1.17604762e-01 -1.38644874e+00 5.31698883e-01
1.11767280e+00 -2.61304826e-01 -7.63965666e-01 4.02683169e-01
7.74438858e-01 -4.97598141e-01 -3.38379234e-01 3.96201879e-01
1.57169446e-01 -7.32668519e-01 3.67309093e-01 -6.77226424e-01
8.41745794e-01 -1.89266339e-01 1.76895216e-01 -1.76993513e+00
-4.18227851e-01 -3.18717510e-02 -3.09112221e-01 1.69054830e+00
5.35807073e-01 -5.51506162e-01 3.13727707e-01 4.91884202e-01
-5.74355602e-01 -6.78137183e-01 -6.77961886e-01 -6.86125994e-01
4.35540169e-01 -5.30463517e-01 7.12467313e-01 1.05443776e+00
1.59844771e-01 1.11146323e-01 -4.99593854e-01 -6.74845949e-02
3.83188009e-01 -5.42626083e-01 3.98712635e-01 -1.25849199e+00
-4.22324277e-02 -2.54265428e-01 -3.69389262e-03 -9.05156255e-01
2.38426581e-01 -9.49578404e-01 4.20184463e-01 -1.25248849e+00
2.06525043e-01 -9.96750593e-01 3.82066444e-02 4.61510539e-01
-9.41626966e-01 -1.65813342e-01 2.61611510e-02 8.99253860e-02
-4.23602313e-01 5.93819201e-01 1.20237017e+00 -2.24308714e-01
-1.23204738e-01 -2.55528450e-01 -7.22847223e-01 6.83627486e-01
1.11268103e+00 -8.32756162e-01 -1.64816454e-01 -7.57685959e-01
7.16784239e-01 -1.72173873e-01 1.32105693e-01 -6.52133882e-01
-2.62412801e-02 -2.94310272e-01 2.03242466e-01 -4.26540464e-01
-4.64974016e-01 -4.91803616e-01 -3.53849709e-01 7.45956838e-01
-4.95163172e-01 1.31956145e-01 1.19947173e-01 4.63934958e-01
-3.73134948e-02 -1.06564927e+00 8.42109799e-01 -1.65581435e-01
-7.47908711e-01 -2.63010770e-01 -3.93950522e-01 1.33640349e-01
6.57992005e-01 5.29260607e-03 -4.81716692e-01 2.68333610e-02
-4.62500572e-01 3.59121770e-01 4.34541404e-01 6.22909307e-01
9.00507271e-01 -1.47599411e+00 -8.67790103e-01 2.84109652e-01
3.76269132e-01 -9.78527591e-02 2.57342607e-01 4.87998217e-01
-6.43192708e-01 6.70763478e-02 1.67630240e-01 -3.96186203e-01
-1.69879436e+00 1.01739742e-01 5.45115948e-01 -1.82561532e-01
-2.43051708e-01 9.98036027e-01 -4.77735013e-01 -1.08589590e+00
2.01525420e-01 -1.23592637e-01 -4.44009662e-01 -3.65830421e-01
7.62934923e-01 3.60033840e-01 3.25566083e-01 -1.38060391e-01
-8.89532417e-02 2.93499410e-01 -2.97725052e-01 5.53803504e-01
1.10143161e+00 -2.58607984e-01 -4.55124021e-01 4.76260364e-01
6.66006565e-01 1.77205890e-01 -5.77472210e-01 7.24528730e-02
5.71810976e-02 -7.99502790e-01 -2.03024521e-01 -1.23830247e+00
-7.42790759e-01 8.76480520e-01 6.69049799e-01 -1.24141939e-01
1.04134226e+00 -3.42659563e-01 8.09796035e-01 4.24861580e-01
4.36017305e-01 -1.53309572e+00 -9.38329399e-02 1.05564332e+00
8.58052611e-01 -1.20380819e+00 -2.85168439e-01 -6.38887167e-01
-3.32820743e-01 1.27505553e+00 1.29647088e+00 -1.05609953e-01
3.54001850e-01 1.95883185e-01 9.95700508e-02 8.22333097e-02
-7.74338484e-01 4.23805803e-01 -1.02907486e-01 7.97086716e-01
8.25028360e-01 1.45639971e-01 -1.52341139e+00 1.03698385e+00
-2.25135967e-01 4.03300859e-03 9.59558129e-01 9.09647048e-01
-8.99226069e-01 -1.42245233e+00 -3.51634026e-01 5.62130451e-01
-7.51519054e-02 -3.74785960e-01 -4.49695110e-01 4.76066798e-01
5.43857098e-01 1.06259012e+00 8.49297792e-02 -4.82055038e-01
4.57355022e-01 3.42166632e-01 6.32361948e-01 -7.12820828e-01
-8.17920148e-01 -6.19851291e-01 1.23093463e-01 -9.35864747e-02
-1.27105042e-01 -5.46352208e-01 -1.71401727e+00 -4.94073004e-01
-8.53975594e-01 3.46124142e-01 6.32560432e-01 8.78430903e-01
3.33544075e-01 6.32697403e-01 6.45412087e-01 -1.66255981e-02
-9.20539141e-01 -1.32533348e+00 -5.03714383e-01 6.13486528e-01
-3.00641842e-02 -5.27382016e-01 -6.48447156e-01 -1.96952656e-01] | [11.011369705200195, 10.76950740814209] |
930e0029-b863-4a71-9dfd-fc9365c5a01c | sphereflow-6-dof-scene-flow-from-rgb-d-pairs | null | null | http://openaccess.thecvf.com/content_cvpr_2014/html/Hornacek_SphereFlow_6_DoF_2014_CVPR_paper.html | http://openaccess.thecvf.com/content_cvpr_2014/papers/Hornacek_SphereFlow_6_DoF_2014_CVPR_paper.pdf | SphereFlow: 6 DoF Scene Flow from RGB-D Pairs | We take a new approach to computing dense scene flow between a pair of consecutive RGB-D frames. We exploit the availability of depth data by seeking correspondences with respect to patches specified not as the pixels inside square windows, but as the 3D points that are the inliers of spheres in world space. Our primary contribution is to show that by reasoning in terms of such patches under 6 DoF rigid body motions in 3D, we succeed in obtaining compelling results at displacements large and small without relying on either of two simplifying assumptions that pervade much of the earlier literature: brightness constancy or local surface planarity. As a consequence of our approach, our output is a dense field of 3D rigid body motions, in contrast to the 3D translations that are the norm in scene flow. Reasoning in our manner additionally allows us to carry out occlusion handling using a 6 DoF consistency check for the flow computed in both directions and a patchwise silhouette check to help reason about alignments in occlusion areas, and to promote smoothness of the flow fields using an intuitive local rigidity prior. We carry out our optimization in two steps, obtaining a first correspondence field using an adaptation of PatchMatch, and subsequently using alpha-expansion to jointly handle occlusions and perform regularization. We show attractive flow results on challenging synthetic and real-world scenes that push the practical limits of the aforementioned assumptions. | ['Andrew Fitzgibbon', 'Michael Hornacek', 'Carsten Rother'] | 2014-06-01 | null | null | null | cvpr-2014-6 | ['occlusion-handling'] | ['computer-vision'] | [ 1.95163682e-01 9.17532369e-02 1.78338900e-01 -2.63792556e-02
-5.11113882e-01 -7.14814544e-01 6.21473789e-01 -6.94750026e-02
-2.18272418e-01 6.14031494e-01 3.29893440e-01 -1.73864961e-01
-4.23910245e-02 -6.97935581e-01 -6.88127220e-01 -6.88184261e-01
-2.22584624e-02 4.22742456e-01 3.90074074e-01 -3.14077348e-01
4.62439507e-01 9.98251379e-01 -1.65852261e+00 -1.30748212e-01
7.37589717e-01 7.51720130e-01 -3.51971149e-01 8.99888396e-01
8.09178967e-03 7.18785763e-01 -1.38101578e-01 -2.34240174e-01
7.75713623e-01 -3.66341799e-01 -9.48303103e-01 6.69119298e-01
9.35369015e-01 -5.03056645e-01 -3.19397539e-01 7.95484006e-01
2.64178365e-01 4.69744146e-01 3.45032364e-01 -1.01164687e+00
-9.57890227e-02 -4.81614828e-01 -7.74202824e-01 1.11729816e-01
8.33969533e-01 3.87623310e-01 9.38166916e-01 -8.56606781e-01
9.88990963e-01 1.30452585e+00 6.86111450e-01 2.93349564e-01
-1.48038006e+00 1.05164997e-01 1.51676655e-01 -3.49472404e-01
-1.18572700e+00 -7.50523388e-01 9.98248041e-01 -6.81236804e-01
1.08090878e+00 5.31481445e-01 9.91919100e-01 4.41359222e-01
-2.28560227e-03 3.47135425e-01 7.52240419e-01 -5.65490603e-01
3.28946412e-01 -9.60959196e-02 -9.61337835e-02 6.87200367e-01
1.79967821e-01 4.39592153e-02 -5.02515018e-01 -2.42276713e-01
1.38285661e+00 -1.16074488e-01 -5.73886931e-01 -9.57556069e-01
-1.23241520e+00 8.10841560e-01 3.87886465e-01 1.46177769e-01
-3.10859680e-01 1.29249170e-01 -7.50216171e-02 7.63940215e-02
6.38858438e-01 2.88046509e-01 -2.12915674e-01 -2.21312512e-02
-7.08198130e-01 3.93970728e-01 9.10321534e-01 9.22154009e-01
1.08988714e+00 -4.44261841e-02 4.48276222e-01 3.26701760e-01
3.85853052e-01 4.91550088e-01 9.42082629e-02 -1.65443504e+00
4.51757848e-01 4.28843260e-01 3.13626051e-01 -1.36962807e+00
-2.76666671e-01 -1.50175259e-01 -4.80369627e-01 5.78405023e-01
8.54372561e-01 6.51939735e-02 -7.54301369e-01 1.50397575e+00
7.89147079e-01 2.64124125e-01 -1.21792547e-01 9.71176505e-01
2.48903349e-01 3.70398492e-01 -3.96304995e-01 -2.76366204e-01
1.13553262e+00 -6.19193614e-01 -3.88223290e-01 -7.35266358e-02
6.89181447e-01 -1.01051188e+00 8.79074633e-01 3.14282894e-01
-1.45182371e+00 -3.53938639e-01 -8.18301558e-01 -4.81869936e-01
1.35093659e-01 -4.32464153e-01 7.26434827e-01 3.40626806e-01
-1.21806180e+00 5.90776384e-01 -1.04454887e+00 -4.47108537e-01
2.65269816e-01 2.19625354e-01 -5.85546792e-01 -6.43082485e-02
-6.02863312e-01 8.56699407e-01 -2.89033771e-01 1.89633161e-01
-3.71650189e-01 -6.75936162e-01 -1.05131352e+00 -2.39938274e-01
2.32833952e-01 -9.94015872e-01 8.62504900e-01 -9.25846398e-01
-1.40131867e+00 1.17535877e+00 -6.00121260e-01 -1.83649048e-01
9.04179573e-01 -1.73470989e-01 3.25125366e-01 4.59277481e-01
1.19080795e-02 5.54327607e-01 6.07456923e-01 -1.35356772e+00
-4.72172707e-01 -4.15512413e-01 3.63122195e-01 5.35598397e-01
2.73368657e-01 -3.99189919e-01 -5.92915356e-01 -3.69385779e-01
6.52857959e-01 -9.79784012e-01 -4.19182926e-01 4.44066823e-01
-2.94288397e-01 1.06050327e-01 6.07057273e-01 -5.71832299e-01
7.80346632e-01 -2.12424755e+00 3.12569946e-01 6.26386762e-01
3.99000615e-01 -1.88326418e-01 1.71168655e-01 7.70168453e-02
-1.24081343e-01 -9.19975415e-02 -3.67679685e-01 -5.74685574e-01
-1.74895197e-01 3.93941104e-01 -4.38786954e-01 1.05348063e+00
2.52647728e-01 5.84398806e-01 -9.86773193e-01 -4.53003943e-01
5.44903874e-01 6.87716424e-01 -9.06171560e-01 1.27960816e-01
-1.31719247e-01 7.94710040e-01 -4.92827922e-01 4.50751096e-01
7.42859423e-01 -8.37480351e-02 -1.67729318e-01 -1.95324302e-01
-3.99326295e-01 3.81487727e-01 -1.64548361e+00 2.00376773e+00
-1.83241844e-01 4.95410711e-01 3.22293580e-01 -8.40016484e-01
6.18742228e-01 2.16057897e-01 9.85497236e-01 -4.09372270e-01
1.13266535e-01 2.52772331e-01 -2.83840209e-01 -4.26891476e-01
3.23542118e-01 -1.93825245e-01 4.90657330e-01 2.81728119e-01
-2.69046545e-01 -6.74176157e-01 7.41209611e-02 1.44783691e-01
1.01545477e+00 4.29603964e-01 1.01072155e-01 -3.59127402e-01
6.02415621e-01 2.00444013e-01 5.03734291e-01 3.60381901e-01
-1.90356568e-01 9.96884644e-01 5.76624990e-01 -7.36508429e-01
-1.25038350e+00 -9.99587119e-01 -4.33471352e-01 1.65223092e-01
2.93655962e-01 -2.75049865e-01 -5.50692797e-01 -2.26366907e-01
8.29243511e-02 2.04995930e-01 -6.67950332e-01 3.41569513e-01
-8.51235747e-01 -5.73347509e-01 -4.61496264e-02 3.31892699e-01
3.49608332e-01 -5.95304906e-01 -1.04639137e+00 6.67194426e-02
-1.44456118e-01 -1.05597210e+00 -3.64363283e-01 1.50066480e-01
-1.10215902e+00 -1.27625918e+00 -6.92182660e-01 -5.23764312e-01
9.62544024e-01 5.07243574e-01 1.11841893e+00 2.31970489e-01
-3.73245537e-01 5.19511342e-01 5.87769337e-02 2.74373174e-01
4.06815894e-02 -5.07126689e-01 -6.64806217e-02 4.80220206e-02
-4.53319810e-02 -8.64969730e-01 -7.84046531e-01 3.65133077e-01
-8.93066704e-01 5.92831112e-02 -1.35577202e-01 5.82405150e-01
6.94869459e-01 -1.43983647e-01 -4.15404946e-01 -6.09404862e-01
-3.70606445e-02 -1.76380187e-01 -9.31749642e-01 4.46023382e-02
-1.35523528e-02 5.99416047e-02 1.00243054e-01 -1.08767025e-01
-9.44562018e-01 4.53869015e-01 -1.34892985e-01 -6.20441139e-01
-1.09066151e-01 -9.44568310e-04 -3.81145924e-02 -4.17524576e-01
7.03973889e-01 -1.84258506e-01 3.88952792e-02 -2.31712654e-01
5.38803399e-01 3.50934826e-02 6.08547032e-01 -8.40119660e-01
9.94494677e-01 1.14193797e+00 4.71136451e-01 -9.64604855e-01
-5.69542885e-01 -6.92524016e-01 -1.02297056e+00 -1.45011649e-01
1.10291708e+00 -7.91052401e-01 -8.45622599e-01 2.33355612e-01
-1.27758670e+00 -2.09079608e-01 -6.62119985e-01 5.34680963e-01
-8.88280690e-01 5.91320395e-01 -5.03954589e-01 -8.01155567e-01
1.56169280e-01 -1.32759953e+00 1.24730086e+00 -6.53799996e-02
-3.44386190e-01 -1.26620221e+00 2.84695745e-01 2.59332359e-01
2.30800554e-01 6.09964907e-01 5.39079010e-01 8.73836428e-02
-8.99854958e-01 -8.91185775e-02 1.61664858e-02 8.16531628e-02
1.32159650e-01 2.75064975e-01 -1.19720125e+00 -1.35809064e-01
3.14553589e-01 9.09716189e-02 6.12096190e-01 5.91026068e-01
4.81727719e-01 -8.43864530e-02 -1.68059722e-01 1.14814234e+00
1.60266793e+00 1.45346243e-02 7.28563845e-01 3.93575281e-01
9.43062782e-01 9.35174882e-01 3.23543161e-01 4.25181568e-01
3.19872737e-01 7.98771441e-01 5.35817981e-01 -3.36673319e-01
-1.56971365e-01 -1.85594290e-01 -9.85487481e-04 4.53086525e-01
-4.29660261e-01 1.33702189e-01 -8.26776087e-01 6.30686760e-01
-1.90298998e+00 -7.83948243e-01 -4.09965485e-01 2.53673887e+00
6.99876130e-01 5.25159054e-02 1.28991619e-01 1.74850821e-01
3.45250070e-01 6.84370920e-02 -4.87937421e-01 -2.30328947e-01
-2.55609840e-01 2.51003474e-01 6.62847281e-01 1.31021345e+00
-9.24589157e-01 7.70080507e-01 6.05320215e+00 1.86061069e-01
-9.33381081e-01 -1.75813019e-01 4.82560158e-01 -1.24342814e-01
-6.99359775e-01 5.54801643e-01 -5.60217261e-01 8.22821483e-02
2.93267012e-01 1.44679859e-01 4.15526539e-01 4.92826819e-01
3.19322705e-01 -4.61961061e-01 -1.11363721e+00 9.69786346e-01
6.13900274e-02 -1.22568905e+00 -2.30185091e-01 2.34576210e-01
9.04743075e-01 -9.47084129e-02 -1.81947455e-01 -6.23720467e-01
3.54821056e-01 -8.09521437e-01 7.08338082e-01 4.30582255e-01
4.50331807e-01 -3.06866318e-01 1.67378038e-01 1.27678230e-01
-1.03315306e+00 4.62186605e-01 -2.96203166e-01 -2.68634170e-01
4.43964809e-01 7.59554684e-01 -3.49959761e-01 4.29959983e-01
5.10372102e-01 8.81589532e-01 -3.39132957e-02 1.06933141e+00
-1.69338495e-01 -1.70734748e-02 -7.14716434e-01 6.97062552e-01
1.50164366e-01 -5.79704762e-01 8.09316695e-01 7.87804842e-01
1.87183470e-01 3.49535853e-01 1.01658657e-01 8.13273072e-01
3.19503099e-01 -6.61312789e-02 -7.56307185e-01 7.48556852e-01
7.59654045e-02 9.82866049e-01 -8.12805831e-01 -3.07450771e-01
-5.05948782e-01 9.32625771e-01 1.28296912e-01 7.13872135e-01
-4.72574383e-01 -5.57526276e-02 1.05611694e+00 3.95477623e-01
2.04315275e-01 -6.35950565e-01 -5.54592252e-01 -1.61638200e+00
4.42595094e-01 -5.31185985e-01 1.07257970e-01 -8.23536575e-01
-8.97214711e-01 3.88587058e-01 -6.88236430e-02 -1.27387834e+00
-1.59992635e-01 -5.13810933e-01 -5.02886534e-01 1.19743311e+00
-1.75453663e+00 -8.27475250e-01 -3.31435889e-01 9.38060462e-01
2.62143493e-01 6.47740722e-01 5.74231029e-01 1.73523277e-01
-1.95503592e-01 -3.41974162e-02 -3.07203472e-01 -1.04914963e-01
6.06481612e-01 -1.15231252e+00 4.02890623e-01 1.14435518e+00
1.55550241e-01 7.54624486e-01 8.24724317e-01 -5.28146923e-01
-1.47382116e+00 -4.57914501e-01 9.51801181e-01 -7.74064600e-01
6.28522635e-01 -2.91455984e-01 -9.04385448e-01 8.91598642e-01
-1.61460131e-01 4.59239811e-01 1.29810125e-02 -1.73748106e-01
-1.68367088e-01 2.94795390e-02 -1.09092116e+00 4.11235631e-01
1.16301775e+00 -4.35153604e-01 -4.26075280e-01 3.84732664e-01
5.24524033e-01 -9.33307290e-01 -8.18768680e-01 2.45700136e-01
5.41038990e-01 -1.13162744e+00 1.21892989e+00 -5.42245090e-01
3.84371430e-01 -6.22685611e-01 -2.66563594e-01 -9.58678186e-01
-3.78669463e-02 -1.04773867e+00 1.81858063e-01 8.92659903e-01
-7.63610750e-03 -6.43644452e-01 9.71548259e-01 1.13608932e+00
-2.17847317e-01 -5.04563332e-01 -1.11887670e+00 -4.23528582e-01
-7.58808479e-02 -5.13872445e-01 3.02498758e-01 1.04988086e+00
-8.49920064e-02 -6.73831776e-02 -9.82754305e-02 2.23737225e-01
6.90803647e-01 5.01673222e-02 1.13728034e+00 -1.22291481e+00
-3.85582030e-01 -4.72718000e-01 -6.44256353e-01 -1.50000644e+00
-9.65938047e-02 -5.21024466e-01 -2.11022934e-03 -1.25817537e+00
-3.40075195e-01 -6.77553594e-01 3.16402674e-01 4.28890020e-01
1.11273266e-01 3.85613650e-01 5.43333143e-02 5.76672614e-01
-1.61556438e-01 3.77044648e-01 1.43565536e+00 2.75924534e-01
-4.38237339e-01 -1.79778770e-01 -3.77538055e-01 9.60364580e-01
2.50219613e-01 -9.76547301e-02 -3.61117572e-01 -6.91799045e-01
3.07245672e-01 2.50750422e-01 5.65985382e-01 -7.44084358e-01
6.04281873e-02 -3.16286117e-01 3.52567196e-01 -3.56747448e-01
5.45087814e-01 -1.01947892e+00 2.07499474e-01 2.36855701e-01
-3.73811461e-02 2.09301054e-01 1.35482475e-01 3.36365134e-01
-4.68116254e-02 7.87793770e-02 8.05964470e-01 -2.72936821e-01
-5.39562464e-01 2.68447220e-01 1.17390156e-01 5.15511557e-02
1.02539098e+00 -5.62708557e-01 -2.63782471e-01 -3.68165016e-01
-9.43957031e-01 7.79072940e-02 1.13365805e+00 -2.71750372e-02
5.69327056e-01 -1.19178605e+00 -5.12088656e-01 6.63332283e-01
-9.26959589e-02 5.30244291e-01 4.12829779e-02 1.18785405e+00
-1.16922569e+00 3.23652178e-01 -1.31144941e-01 -9.98599410e-01
-1.03709114e+00 3.47113252e-01 5.26922524e-01 2.24939808e-02
-9.23759043e-01 8.58296990e-01 3.91657472e-01 -9.49663371e-02
3.46568853e-01 -5.10134816e-01 1.79514125e-01 -2.31281146e-01
2.32899874e-01 3.72859120e-01 1.91450417e-01 -9.27322030e-01
-4.37067419e-01 1.22766542e+00 4.25390661e-01 -3.11173707e-01
1.25315869e+00 -3.73609155e-01 -2.98326492e-01 1.25774264e-01
1.29551530e+00 4.53638703e-01 -1.71779752e+00 -4.45657037e-02
-3.66582602e-01 -1.02123797e+00 -8.84757861e-02 -1.91542521e-01
-1.09580302e+00 8.44928741e-01 1.59510523e-01 1.69634551e-01
1.05972266e+00 -1.87669657e-02 5.59454858e-01 5.62455580e-02
1.79294556e-01 -5.84575713e-01 -3.64727437e-01 3.27593356e-01
8.07212949e-01 -1.12177372e+00 1.72019675e-01 -8.08500767e-01
-1.26846373e-01 1.25957882e+00 2.88523406e-01 -5.43411791e-01
5.64134717e-01 1.01042867e-01 2.05253512e-01 -2.33572274e-01
-3.94736856e-01 -2.85749018e-01 3.59111845e-01 5.71352363e-01
4.77179855e-01 -4.03083682e-01 -1.77397624e-01 -6.91917002e-01
-2.37679973e-01 -2.56371200e-01 5.22182047e-01 9.97971117e-01
-4.57638055e-01 -1.10093343e+00 -5.89334965e-01 -1.72123149e-01
-1.85785666e-01 8.82336795e-02 -1.75486103e-01 9.57179070e-01
3.12505178e-02 9.11840856e-01 3.08705419e-01 8.85168836e-02
5.54379404e-01 -2.50482947e-01 7.48496532e-01 -4.18076396e-01
-1.34129047e-01 4.73098874e-01 -2.86857616e-02 -9.42298055e-01
-8.10884118e-01 -8.98506224e-01 -1.24451578e+00 -4.15910631e-01
-8.68720710e-02 3.21269631e-02 5.93642175e-01 8.88116181e-01
4.19140942e-02 1.40027246e-02 6.26294076e-01 -1.23043108e+00
-1.83764219e-01 -3.46159816e-01 -4.23774660e-01 7.68084586e-01
8.12139153e-01 -6.67877555e-01 -7.87231147e-01 3.81498694e-01] | [8.712102890014648, -2.11586332321167] |
ce6dc914-c5f0-4c30-8940-273a30ff91f2 | influence-of-mother-tongue-on-english-accent | null | null | https://aclanthology.org/W14-5109 | https://aclanthology.org/W14-5109.pdf | Influence of Mother Tongue on English Accent | null | ['R. Krishnan', 'G. Radha Krishna'] | 2014-12-01 | null | null | null | ws-2014-12 | ['text-independent-speaker-recognition'] | ['speech'] | [-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] | [-7.230069160461426, 3.812074661254883] |
1f1d2658-d50b-4ee6-9708-ff75e3a9ea03 | stability-of-graph-neural-networks-to | 1910.09655 | null | https://arxiv.org/abs/1910.09655v1 | https://arxiv.org/pdf/1910.09655v1.pdf | Stability of Graph Neural Networks to Relative Perturbations | Graph neural networks (GNNs), consisting of a cascade of layers applying a graph convolution followed by a pointwise nonlinearity, have become a powerful architecture to process signals supported on graphs. Graph convolutions (and thus, GNNs), rely heavily on knowledge of the graph for operation. However, in many practical cases the GSO is not known and needs to be estimated, or might change from training time to testing time. In this paper, we are set to study the effect that a change in the underlying graph topology that supports the signal has on the output of a GNN. We prove that graph convolutions with integral Lipschitz filters lead to GNNs whose output change is bounded by the size of the relative change in the topology. Furthermore, we leverage this result to show that the main reason for the success of GNNs is that they are stable architectures capable of discriminating features on high eigenvalues, which is a feat that cannot be achieved by linear graph filters (which are either stable or discriminative, but cannot be both). Finally, we comment on the use of this result to train GNNs with increased stability and run experiments on movie recommendation systems. | ['Fernando Gama', 'Alejandro Ribeiro', 'Joan Bruna'] | 2019-10-21 | null | null | null | null | ['movie-recommendation'] | ['miscellaneous'] | [ 1.33851230e-01 2.62255669e-01 2.47501791e-01 -1.31908566e-01
2.91305602e-01 -9.05793369e-01 4.12198901e-01 1.69282898e-01
-2.62019128e-01 1.91397414e-01 -3.41500826e-02 -5.68197906e-01
-1.17911719e-01 -9.61835146e-01 -1.07151258e+00 -6.42906427e-01
-5.41041017e-01 -1.10729225e-03 3.48109663e-01 -3.56286705e-01
2.45699305e-02 6.18198633e-01 -1.01831520e+00 1.94629967e-01
3.89312148e-01 9.75186646e-01 -1.81803256e-01 1.10060918e+00
4.21613753e-02 6.13480389e-01 -3.34549665e-01 -3.58793795e-01
5.10571778e-01 -5.58635354e-01 -5.23223996e-01 -4.72815521e-02
5.26737034e-01 -7.51791373e-02 -5.87922335e-01 1.35138357e+00
2.30588347e-01 3.27352285e-01 6.40441239e-01 -1.02918983e+00
-8.63759995e-01 9.04561758e-01 -9.95411649e-02 4.35567081e-01
1.43189877e-01 7.48760253e-02 1.24271095e+00 -6.01656914e-01
5.74855387e-01 1.08040071e+00 9.76077378e-01 2.64078021e-01
-1.34303606e+00 -3.78247738e-01 4.51887280e-01 -1.31812349e-01
-9.73956168e-01 -3.18931133e-01 7.51217663e-01 -4.03378099e-01
8.13958049e-01 1.55969962e-01 8.68646979e-01 8.85049820e-01
2.40432739e-01 3.43551219e-01 6.89249754e-01 -2.67034084e-01
2.58710921e-01 -7.98355341e-02 1.66990504e-01 1.11552727e+00
2.92643607e-01 -6.19160943e-02 -2.80241936e-01 4.59658280e-02
1.17958105e+00 -4.75317053e-02 -7.17185915e-01 -4.07893360e-01
-1.00249541e+00 9.82730627e-01 1.00998759e+00 3.87204736e-01
-2.66842544e-01 4.82189655e-01 1.41082302e-01 1.02230299e+00
2.24187255e-01 5.07522881e-01 -7.18456805e-02 2.66977847e-01
-5.52029312e-01 -2.64118224e-01 1.04540122e+00 5.24483979e-01
5.22722006e-01 2.20619574e-01 1.18862242e-01 1.07798904e-01
-8.67405068e-03 3.67548048e-01 3.66393924e-01 -4.80161339e-01
7.53445104e-02 6.52961791e-01 -3.18086863e-01 -1.29482591e+00
-7.74265230e-01 -7.62508631e-01 -9.68971014e-01 1.77988753e-01
9.32669342e-01 -2.18135044e-01 -8.30685496e-01 1.92753470e+00
-7.46201873e-02 3.16573262e-01 -1.38491482e-01 9.38458979e-01
6.41845822e-01 3.31496745e-01 -3.98812234e-01 1.79687157e-01
9.02696252e-01 -4.97275770e-01 -2.29991361e-01 -4.11441252e-02
5.96218288e-01 -2.60898113e-01 1.19256818e+00 3.45577121e-01
-1.01558304e+00 -3.31808418e-01 -1.26669407e+00 1.94329366e-01
-5.44924200e-01 -1.54754996e-01 8.73536646e-01 5.97839475e-01
-1.43360889e+00 1.10251248e+00 -8.41593862e-01 -4.87505972e-01
2.08473995e-01 5.32872021e-01 -3.42058569e-01 1.93181604e-01
-1.28334188e+00 6.09406829e-01 9.11370218e-02 2.99995363e-01
-4.71068919e-01 -2.76350111e-01 -7.57468760e-01 5.57719946e-01
1.66109160e-01 -5.55965900e-01 7.95036733e-01 -1.49737525e+00
-1.39427817e+00 4.17882204e-01 3.19644779e-01 -8.56944442e-01
5.22425354e-01 3.53898704e-01 -3.41949254e-01 2.70475954e-01
-3.53020698e-01 1.13344505e-01 1.11098826e+00 -6.25051618e-01
-2.22427905e-01 -2.28760645e-01 5.44243097e-01 -2.76185968e-03
-3.74752641e-01 -2.02683598e-01 -1.46371722e-01 -4.64304268e-01
3.17454219e-01 -1.02043056e+00 -2.74974138e-01 -4.33643050e-02
-1.97983250e-01 4.48525511e-02 4.40337479e-01 -5.06912410e-01
9.66009557e-01 -2.28750849e+00 8.25066864e-02 8.83368194e-01
5.05107939e-01 1.00561924e-01 -2.50946492e-01 3.89167249e-01
-1.82409734e-01 1.56071261e-01 2.19210604e-04 1.51666343e-01
-1.64834559e-02 -1.11641921e-01 -5.04051149e-01 8.43929052e-01
1.66665822e-01 1.14661431e+00 -8.29068422e-01 2.19250828e-01
-5.27530536e-02 6.23326540e-01 -5.48037529e-01 -1.32917970e-01
-2.46943444e-01 2.26702929e-01 -2.26978406e-01 2.92945653e-02
2.94271141e-01 -7.33478367e-01 4.07121569e-01 -1.76382542e-01
1.07724883e-01 2.91589826e-01 -1.28716052e+00 1.16570389e+00
-1.90809891e-01 7.81561852e-01 1.41140789e-01 -1.16864824e+00
7.02118635e-01 1.64367944e-01 2.81323016e-01 -5.27107239e-01
3.12245667e-01 9.22633410e-02 4.15209979e-01 -7.40811676e-02
7.28760809e-02 -7.51048550e-02 1.89302653e-01 6.07056558e-01
1.18981823e-01 2.27075040e-01 2.52814084e-01 2.79429495e-01
1.54529262e+00 -4.03577626e-01 -8.69034603e-02 -4.65239495e-01
2.15795994e-01 -3.15273196e-01 1.71069816e-01 9.00447011e-01
2.17192583e-02 4.45794970e-01 1.07928956e+00 -4.21262860e-01
-8.99326146e-01 -1.09797108e+00 2.49296740e-01 9.97778654e-01
8.81179348e-02 -2.26309374e-01 -6.82404459e-01 -6.63997054e-01
5.80572039e-02 1.29644692e-01 -6.50426805e-01 -4.07011867e-01
-5.86873829e-01 -6.01708829e-01 5.00867069e-01 6.86880231e-01
2.59159923e-01 -9.01967764e-01 -4.89956826e-01 2.81852633e-01
4.16172683e-01 -1.08942699e+00 -6.70672715e-01 3.15531403e-01
-8.14941525e-01 -1.27662051e+00 -5.25745690e-01 -8.52967858e-01
9.13931310e-01 2.45111734e-01 9.97399271e-01 3.63767236e-01
1.86147571e-01 6.32266700e-01 -1.47144914e-01 -1.32581979e-01
-2.95142055e-01 1.23956084e-01 -7.67684961e-03 3.02006662e-01
-1.49220273e-01 -9.28311884e-01 -5.68528116e-01 1.64971828e-01
-8.80706489e-01 -7.69448876e-02 3.84591192e-01 7.84177065e-01
2.41176769e-01 4.65462714e-01 4.52574253e-01 -1.12231684e+00
9.40867305e-01 -2.30252519e-01 -8.35732996e-01 2.27293655e-01
-4.79244798e-01 3.38240594e-01 1.05973375e+00 -5.57584822e-01
-1.85923100e-01 5.20362444e-02 1.37753561e-01 -5.21453857e-01
4.18775618e-01 8.88095438e-01 2.33571112e-01 -5.39145052e-01
7.38911211e-01 -9.27212983e-02 1.75179183e-01 -2.55010217e-01
5.05064428e-01 -4.09308709e-02 5.21087527e-01 -1.22483164e-01
7.28808761e-01 5.59439480e-01 2.98488379e-01 -8.32275927e-01
-3.96990150e-01 -1.04659140e-01 -4.53095168e-01 -2.54665345e-01
6.93403840e-01 -6.45493746e-01 -8.75982821e-01 3.43653619e-01
-9.06254768e-01 -7.79109120e-01 -2.44249403e-01 3.75240654e-01
-1.69073388e-01 1.51382551e-01 -9.10472989e-01 -6.23198926e-01
-2.02315345e-01 -6.74458325e-01 3.25394213e-01 1.28716499e-01
8.95328447e-02 -1.27855873e+00 -3.79075676e-01 -5.29077649e-01
6.90807760e-01 3.23021978e-01 1.05945480e+00 -7.38139808e-01
-5.49400568e-01 -4.36834425e-01 -2.53140688e-01 3.10172588e-01
-2.18221441e-01 7.60445669e-02 -6.50475264e-01 -6.02477729e-01
4.68324907e-02 1.78240106e-01 9.56930995e-01 5.46604574e-01
9.10763741e-01 -4.32959199e-01 -2.71373056e-02 7.10590184e-01
1.35096431e+00 -2.86265910e-01 2.96909869e-01 -8.16310719e-02
8.03016424e-01 2.54553348e-01 -4.38145876e-01 -4.77912650e-02
6.65161684e-02 3.16529572e-01 3.88135880e-01 -2.80299366e-01
-2.04496980e-01 -2.58989543e-01 5.28491318e-01 8.70970130e-01
-1.88775122e-01 -3.27703774e-01 -6.82739913e-01 2.30043903e-01
-1.81402874e+00 -7.55642295e-01 -2.66314179e-01 2.31280780e+00
3.39486778e-01 6.36982977e-01 2.77079701e-01 1.34335786e-01
7.02710927e-01 6.70933798e-02 -6.19438469e-01 -5.27056038e-01
-2.57858276e-01 4.55587655e-01 9.03640330e-01 7.22241104e-01
-1.00585735e+00 6.45629585e-01 6.43911409e+00 1.55495048e-01
-1.72302842e+00 -2.43476897e-01 2.50563204e-01 1.67918012e-01
-3.24414343e-01 -6.02041706e-02 -8.89032483e-02 3.57609361e-01
9.64022636e-01 -1.57646239e-01 9.53317761e-01 6.96449757e-01
-1.10017121e-01 3.63205552e-01 -1.22541010e+00 7.28055894e-01
-1.30960062e-01 -1.18400931e+00 -8.67564082e-02 1.15963161e-01
5.70326269e-01 1.68675840e-01 2.58446753e-01 1.84168428e-01
6.30310118e-01 -1.19030714e+00 6.00053728e-01 4.19229031e-01
6.79964662e-01 -4.50577617e-01 5.44882655e-01 7.36357570e-02
-1.24575627e+00 -1.50632218e-01 -5.31443775e-01 -3.47691923e-01
-1.13629408e-01 7.71563828e-01 -8.33250701e-01 1.33371919e-01
3.74137819e-01 5.86871028e-01 -5.03432989e-01 9.79836941e-01
-5.22289336e-01 7.94257820e-01 -3.89378935e-01 -1.49976045e-01
3.18236470e-01 -2.31852546e-01 5.76104462e-01 1.14468074e+00
2.05164880e-01 9.98442993e-02 1.71260700e-01 9.64512885e-01
-3.18498433e-01 -7.67514408e-02 -6.73882484e-01 -4.62410778e-01
-2.69630048e-02 1.27689898e+00 -1.12910140e+00 -2.98750643e-02
-5.29296279e-01 8.58955383e-01 4.66185510e-01 6.97839439e-01
-5.88162899e-01 -4.31809843e-01 3.92779589e-01 3.11672837e-01
6.61361039e-01 -4.78385448e-01 -1.85103655e-01 -1.20600224e+00
-2.82720216e-02 -7.15211987e-01 4.29980397e-01 -4.68626052e-01
-1.24980569e+00 5.52629530e-01 -6.90556586e-01 -7.62092412e-01
-1.11211888e-01 -8.51298690e-01 -8.07180762e-01 8.07950556e-01
-1.13857234e+00 -9.28159654e-01 -1.33092478e-01 7.02088296e-01
-2.53412217e-01 1.48851082e-01 6.28935456e-01 1.66503772e-01
-3.60243469e-01 5.95332444e-01 -7.10024685e-02 5.88827491e-01
1.43964082e-01 -1.43868685e+00 7.87013352e-01 1.05362761e+00
5.16314209e-01 7.28509605e-01 5.78458071e-01 -4.54144299e-01
-1.75783670e+00 -9.40910339e-01 5.30715644e-01 -3.27150911e-01
9.65688467e-01 -6.53070569e-01 -9.01026905e-01 9.63987052e-01
-1.72321528e-01 3.51438046e-01 9.11941230e-02 2.49206647e-01
-5.41681886e-01 5.11982590e-02 -8.46092284e-01 5.65661490e-01
1.24973512e+00 -6.56497002e-01 -7.42132887e-02 3.34338471e-02
6.02649629e-01 -4.18688983e-01 -5.93606830e-01 2.65441447e-01
6.01744354e-01 -1.01095867e+00 7.04680622e-01 -9.91548598e-01
2.34956406e-02 -2.40921438e-01 2.13492345e-02 -1.40703237e+00
-6.29745901e-01 -6.74163938e-01 -1.36752054e-01 4.94125158e-01
5.01000285e-01 -1.06538260e+00 6.76833451e-01 5.18186569e-01
-3.28642987e-02 -6.70694828e-01 -6.89571857e-01 -8.48842919e-01
-8.04481208e-02 -2.45151177e-01 4.93685007e-01 9.18710411e-01
1.66623592e-01 4.96217698e-01 9.25083011e-02 3.57160836e-01
2.17758894e-01 1.93605214e-01 4.93369132e-01 -1.24744439e+00
-6.96769238e-01 -8.61687303e-01 -8.72916102e-01 -1.04605997e+00
8.26823860e-02 -1.27362835e+00 -1.79061204e-01 -1.34131193e+00
-2.94047832e-01 -2.60991246e-01 -5.38215339e-01 4.62874532e-01
1.36821419e-01 1.81382731e-01 6.99097738e-02 1.56908687e-02
-3.88916969e-01 -3.48353423e-02 9.71345842e-01 -1.03598833e-02
-2.99795210e-01 1.27951354e-01 -7.14632452e-01 5.94155252e-01
5.52998602e-01 -5.12280315e-02 -4.57044631e-01 -2.49808744e-01
7.88483977e-01 -1.77436560e-01 5.27045608e-01 -1.04101598e+00
2.78341025e-01 3.61617208e-01 3.49824816e-01 2.11001009e-01
-9.91921872e-02 -7.04214871e-01 1.72383726e-01 6.74296021e-01
-4.03282583e-01 1.68326885e-01 -2.92202681e-02 6.92101657e-01
7.79907778e-02 2.89183296e-03 7.09153116e-01 -1.53607816e-01
-4.29210752e-01 4.84544724e-01 -1.39913797e-01 -2.74165664e-02
4.27040815e-01 -1.03136897e-01 -2.63114631e-01 -8.26874316e-01
-8.71782005e-01 -4.71503008e-03 4.50048000e-01 3.47590446e-02
3.01749587e-01 -1.27713382e+00 -4.07437354e-01 3.99873078e-01
-3.69587302e-01 -3.92593116e-01 -1.11886911e-01 9.92345572e-01
-3.64502013e-01 1.08431220e-01 -1.05143733e-01 -3.46068174e-01
-9.72213984e-01 6.87294185e-01 6.21113837e-01 -1.08905874e-01
-8.98619533e-01 1.01516867e+00 2.15173244e-01 -3.42954360e-02
3.27245116e-01 -7.78872252e-01 2.97948020e-03 -1.27205208e-01
2.41418004e-01 1.52734667e-02 3.51214021e-01 -2.46388912e-01
-2.25446030e-01 3.96370888e-01 2.83271372e-01 9.49376449e-02
1.39689624e+00 9.51862708e-02 -1.00465059e-01 4.80612993e-01
1.05836475e+00 8.39475840e-02 -1.17500114e+00 -1.72941625e-01
-2.10228384e-01 -1.04033969e-01 7.42405877e-02 -4.47001338e-01
-1.36942649e+00 8.06903720e-01 3.54390562e-01 9.55253303e-01
1.01198184e+00 -6.93254098e-02 6.22950435e-01 4.10743803e-01
1.65445283e-01 -7.99013793e-01 4.19826210e-02 5.67107320e-01
7.66806483e-01 -8.86437893e-01 -3.59434754e-01 -3.51894110e-01
-6.43832088e-02 1.43417907e+00 1.44085750e-01 -6.31914854e-01
9.76727366e-01 8.98935869e-02 -3.05604398e-01 -5.77338398e-01
-5.37286639e-01 -3.68252009e-01 5.32171845e-01 3.70636821e-01
3.51320446e-01 1.93427458e-01 -6.52751327e-02 5.26751876e-01
-3.85475010e-01 -2.81107277e-01 5.50524235e-01 4.72403646e-01
-5.01029789e-01 -5.95122397e-01 4.26118672e-02 7.54880965e-01
-3.12087297e-01 -2.12644890e-01 -5.73075891e-01 6.34627759e-01
-1.80952251e-01 8.01523983e-01 -2.53833905e-02 -5.73306859e-01
3.54999840e-01 -9.87211149e-03 6.43915176e-01 -5.27353764e-01
-4.90537226e-01 -2.26932496e-01 -3.25956917e-03 -5.33377290e-01
1.04942717e-01 -3.38420510e-01 -1.33735847e+00 -5.23842931e-01
-4.56644565e-01 -4.80382964e-02 5.99653184e-01 7.15316772e-01
2.53134251e-01 5.15791714e-01 4.99793530e-01 -4.69446808e-01
-6.10868096e-01 -6.56928241e-01 -7.95352757e-01 4.50804055e-01
4.57777888e-01 -3.14491928e-01 -6.79848194e-01 -2.01272726e-01] | [6.796566009521484, 6.091092109680176] |
372a0b0b-bfe3-47d0-9f0d-f3fb7348052f | relaxed-attention-for-transformer-models | 2209.09735 | null | https://arxiv.org/abs/2209.09735v1 | https://arxiv.org/pdf/2209.09735v1.pdf | Relaxed Attention for Transformer Models | The powerful modeling capabilities of all-attention-based transformer architectures often cause overfitting and - for natural language processing tasks - lead to an implicitly learned internal language model in the autoregressive transformer decoder complicating the integration of external language models. In this paper, we explore relaxed attention, a simple and easy-to-implement smoothing of the attention weights, yielding a two-fold improvement to the general transformer architecture: First, relaxed attention provides regularization when applied to the self-attention layers in the encoder. Second, we show that it naturally supports the integration of an external language model as it suppresses the implicitly learned internal language model by relaxing the cross attention in the decoder. We demonstrate the benefit of relaxed attention across several tasks with clear improvement in combination with recent benchmark approaches. Specifically, we exceed the former state-of-the-art performance of 26.90% word error rate on the largest public lip-reading LRS3 benchmark with a word error rate of 26.31%, as well as we achieve a top-performing BLEU score of 37.67 on the IWSLT14 (DE$\rightarrow$EN) machine translation task without external language models and virtually no additional model parameters. Code and models will be made publicly available. | ['Tim Fingscheidt', 'Zhengyang Li', 'Björn Möller', 'Timo Lohrenz'] | 2022-09-20 | null | null | null | null | ['lipreading'] | ['computer-vision'] | [ 2.68849194e-01 6.21946216e-01 -2.44436398e-01 -1.86857477e-01
-1.36042440e+00 -4.30240393e-01 5.70633709e-01 -2.29460657e-01
-4.64428782e-01 5.92169225e-01 6.60067499e-01 -7.47910202e-01
5.38561881e-01 -3.18955123e-01 -1.11250114e+00 -4.46085006e-01
4.41074073e-01 6.49238765e-01 -5.47689535e-02 -4.80938375e-01
-1.87678859e-01 3.49334702e-02 -9.71468687e-01 2.74305701e-01
9.08806860e-01 8.59273851e-01 3.27511698e-01 5.62054813e-01
-2.81733344e-03 8.30804348e-01 -4.36964571e-01 -7.06506729e-01
-1.47213861e-02 -1.88309669e-01 -8.82330418e-01 -2.76380330e-01
4.73149687e-01 -3.31508696e-01 -4.61456299e-01 7.36458719e-01
4.65535939e-01 -1.37712553e-01 5.37016869e-01 -6.74769223e-01
-1.39659548e+00 8.78705859e-01 -5.49071431e-01 1.59545004e-01
5.10821007e-02 2.93884933e-01 1.40207589e+00 -1.17340183e+00
3.81673485e-01 1.38386583e+00 7.30904281e-01 5.70864201e-01
-1.52154338e+00 -5.82264483e-01 3.30308288e-01 6.10422902e-02
-1.26604724e+00 -9.18878794e-01 4.32306468e-01 -1.77376971e-01
1.81415987e+00 1.02082089e-01 2.20870703e-01 1.44704187e+00
3.85212302e-01 9.69636679e-01 9.74988699e-01 -4.50588167e-01
-2.09528938e-01 1.55643612e-01 1.91790849e-01 6.42390013e-01
-1.86254978e-01 -1.44296169e-01 -5.37160277e-01 8.31975564e-02
4.75042403e-01 -4.67173547e-01 -2.62161374e-01 3.78235094e-02
-1.18024707e+00 6.77008152e-01 4.13492292e-01 2.12322369e-01
-2.02527270e-01 4.61788774e-01 5.43785453e-01 4.04395998e-01
7.93308735e-01 3.58307093e-01 -8.61890614e-01 -2.20929489e-01
-7.88074672e-01 -2.26096541e-01 5.13308048e-01 1.14583218e+00
4.59856927e-01 3.23917150e-01 -4.69342321e-01 1.05426216e+00
3.17732513e-01 6.65363014e-01 6.63443387e-01 -6.14334166e-01
8.17385852e-01 1.57359704e-01 -2.04886213e-01 -3.66035730e-01
-9.47114825e-02 -8.02797914e-01 -9.02406871e-01 -2.43482456e-01
3.61416638e-01 -6.10657269e-03 -1.07681119e+00 2.16942263e+00
-2.90607721e-01 -2.28979394e-01 2.26658851e-01 5.30954659e-01
7.10725129e-01 8.08707833e-01 1.65977716e-01 -6.35993108e-02
1.39171839e+00 -1.25967002e+00 -8.04836631e-01 -6.91626787e-01
5.93455434e-01 -8.38215292e-01 1.71037066e+00 2.53082275e-01
-1.42516649e+00 -5.74186683e-01 -9.12976623e-01 -8.41563046e-01
-1.97393090e-01 3.68212819e-01 3.17985386e-01 2.17921212e-01
-1.48053861e+00 2.93652862e-01 -9.06509340e-01 -3.63611311e-01
1.27995133e-01 5.13176680e-01 -2.88456291e-01 1.51391178e-01
-1.38316774e+00 1.22725236e+00 -8.38981345e-02 -1.17403194e-02
-7.94834137e-01 -9.25843239e-01 -9.72703040e-01 2.27352828e-01
2.20566958e-01 -8.09001744e-01 1.56176698e+00 -1.06945598e+00
-1.91585088e+00 9.36708212e-01 -5.94815195e-01 -7.50779927e-01
4.88684744e-01 -6.58507228e-01 -2.42179394e-01 -3.30066830e-01
-8.54206309e-02 7.45218456e-01 7.11910367e-01 -7.31607914e-01
-6.25391528e-02 -7.73585737e-02 -1.85102150e-01 1.16410263e-01
-3.20045948e-01 1.96785852e-01 -7.37509727e-01 -8.36868465e-01
-2.46543229e-01 -8.93587828e-01 6.12297542e-02 -3.77046943e-01
-4.44169819e-01 -2.99559295e-01 5.74635804e-01 -1.10136151e+00
1.26641488e+00 -1.95069635e+00 3.90390068e-01 -4.21011239e-01
-7.41028115e-02 3.59001756e-01 -4.85069096e-01 2.76016653e-01
-2.63370961e-01 2.24511266e-01 -2.99025297e-01 -8.45864356e-01
6.01702519e-02 8.16693157e-02 -7.50781596e-01 3.23632240e-01
5.47550559e-01 1.37618124e+00 -5.36173224e-01 5.94468638e-02
-1.95431821e-02 9.07605886e-01 -7.21122861e-01 2.23597094e-01
-3.35640848e-01 2.63791919e-01 6.47600219e-02 3.07922482e-01
3.21238697e-01 -2.88883537e-01 -1.08727030e-02 -6.07672483e-02
3.95803750e-02 1.24111974e+00 -3.58805746e-01 1.69262123e+00
-8.81127656e-01 8.34210813e-01 2.08063066e-01 -7.52247214e-01
6.98208928e-01 4.10259157e-01 -2.72802338e-02 -8.86730969e-01
9.20112506e-02 2.04644114e-01 7.37669617e-02 -7.55533278e-02
4.93875802e-01 -2.25613877e-01 -1.41119733e-01 3.51950824e-01
5.04627824e-01 -5.56283370e-02 -2.89644182e-01 2.10157245e-01
9.02792931e-01 2.49137580e-01 2.33329087e-01 -5.94456673e-01
4.79181439e-01 -5.47778785e-01 4.70901787e-01 6.72059417e-01
1.65238783e-01 6.30085766e-01 5.56778610e-01 -7.92318285e-02
-1.21783948e+00 -9.63383555e-01 -2.41212752e-02 1.40673649e+00
-4.80169505e-01 -7.04915822e-01 -7.95711219e-01 -4.93565321e-01
-1.33026108e-01 1.03547060e+00 -4.90788102e-01 -3.70447129e-01
-8.11743319e-01 -7.29883909e-01 8.17492306e-01 7.19500363e-01
2.09779158e-01 -9.12424386e-01 8.85080360e-03 3.26227844e-01
-4.24710631e-01 -1.19517958e+00 -8.31759572e-01 4.63586509e-01
-7.56943524e-01 -3.38597506e-01 -8.67456198e-01 -6.82495832e-01
2.30652303e-01 -2.04340160e-01 1.52846336e+00 2.67233467e-03
2.56931245e-01 9.83642880e-03 1.41991049e-01 -3.00890595e-01
-4.93481517e-01 6.08201146e-01 4.73130830e-02 -3.01578283e-01
4.94103879e-01 -3.59775215e-01 -1.34358242e-01 1.05090946e-01
-3.78778100e-01 3.16162527e-01 6.09770417e-01 1.13335180e+00
5.16314864e-01 -8.59067559e-01 6.08834922e-01 -5.76365232e-01
6.13273203e-01 -4.05628890e-01 -5.95680594e-01 2.71226555e-01
-5.33472657e-01 4.99768257e-01 7.18320668e-01 -3.62721622e-01
-9.93653595e-01 -1.93679988e-01 -6.41548812e-01 -1.82774112e-01
1.90301508e-01 3.11777562e-01 -3.67784977e-01 3.52753997e-01
2.04768375e-01 3.60031754e-01 -3.50358561e-02 -7.05914974e-01
4.33477670e-01 6.96575940e-01 5.86430073e-01 -6.15207434e-01
5.72253883e-01 -1.48860797e-01 -5.29285133e-01 -7.32800186e-01
-9.66666102e-01 -1.50462940e-01 -4.03533250e-01 4.88492250e-01
8.42056036e-01 -1.31258285e+00 -4.30573970e-01 4.84349579e-01
-1.38795531e+00 -7.00447977e-01 -1.35451615e-01 3.16258550e-01
-7.86869466e-01 2.14383319e-01 -9.94630814e-01 -5.71044624e-01
-6.81507885e-01 -1.46064079e+00 1.32968605e+00 -3.07383746e-01
-4.25962925e-01 -9.10695314e-01 -1.23744912e-01 4.09015536e-01
7.26539910e-01 -5.96116006e-01 1.09814012e+00 -6.19677126e-01
-5.14628351e-01 2.82562315e-01 -1.51515022e-01 5.10112524e-01
-1.35030150e-01 -1.42484695e-01 -1.33732569e+00 -3.78947794e-01
6.74210563e-02 -4.05232012e-01 1.23717058e+00 3.79147172e-01
1.12857127e+00 -3.94775152e-01 -1.11110732e-01 7.13520288e-01
1.10600805e+00 -1.37880355e-01 7.59778142e-01 6.17456771e-02
6.70231700e-01 3.05019498e-01 -2.65713036e-02 -1.50746822e-01
4.98981893e-01 8.62473071e-01 6.17872812e-02 -3.91222298e-01
-3.72753441e-01 -5.63531935e-01 8.87069762e-01 1.34475386e+00
2.08449483e-01 -4.83473778e-01 -9.00729537e-01 5.62527835e-01
-1.56470060e+00 -6.38790905e-01 3.74666601e-02 2.16750288e+00
1.14389884e+00 3.02908123e-01 -1.32254809e-01 -2.01381013e-01
3.52793127e-01 8.86289328e-02 -5.29040873e-01 -9.05352414e-01
-2.20800906e-01 5.11879027e-01 6.55775785e-01 1.16696489e+00
-9.35340285e-01 1.43913114e+00 6.86550713e+00 8.39410722e-01
-1.09972429e+00 5.13908863e-01 8.33542287e-01 -9.16120261e-02
-5.22384942e-01 -2.32613817e-01 -1.09914827e+00 3.01646262e-01
1.44432676e+00 -5.30216880e-02 5.65798163e-01 5.53180337e-01
1.49190351e-01 3.75867784e-01 -1.27227271e+00 6.15400851e-01
6.95896056e-03 -1.04019964e+00 1.92774624e-01 1.33570522e-01
3.91232908e-01 6.73261046e-01 3.72805297e-01 6.87126279e-01
4.38250780e-01 -1.26019955e+00 9.00737464e-01 2.77935624e-01
1.18239844e+00 -6.33922458e-01 5.32617569e-01 3.44230682e-01
-1.00326192e+00 -1.86633129e-04 -3.08419973e-01 -1.21853411e-01
2.52240330e-01 4.24352378e-01 -6.67563856e-01 1.92569792e-01
5.82918108e-01 5.35700500e-01 -4.18750256e-01 3.33718538e-01
-4.21986133e-01 9.38905299e-01 -3.37248266e-01 1.66708127e-01
3.70092124e-01 1.24519452e-01 6.52794540e-01 1.49884152e+00
2.36188322e-01 -2.33118996e-01 -3.26766193e-01 9.75181043e-01
-4.88414019e-01 2.24414334e-01 -5.73258340e-01 -1.76213048e-02
8.64084363e-02 7.69451141e-01 1.73472390e-02 -4.49327648e-01
-5.67590594e-01 1.10786521e+00 7.55382895e-01 5.80958247e-01
-1.01607430e+00 -2.12938130e-01 9.50314164e-01 1.48379013e-01
4.33058500e-01 -3.57524663e-01 -3.43609273e-01 -1.42976439e+00
8.55100825e-02 -1.07919514e+00 -9.24337146e-05 -8.36192906e-01
-1.11845541e+00 8.39342952e-01 -3.31554949e-01 -5.90504706e-01
-4.58527267e-01 -6.78048551e-01 -3.98448914e-01 1.45234609e+00
-1.62589502e+00 -1.24567461e+00 3.32020879e-01 3.67625743e-01
8.43123853e-01 -2.35079423e-01 9.91609335e-01 2.95705527e-01
-4.76683289e-01 1.13919842e+00 1.66691631e-01 1.34280697e-01
8.82791519e-01 -1.15443540e+00 1.04371881e+00 9.30767000e-01
2.00652316e-01 8.66751373e-01 6.34054899e-01 -4.40947831e-01
-1.54568565e+00 -9.78913844e-01 1.50737667e+00 -6.54968262e-01
9.69167292e-01 -9.81471479e-01 -1.06690788e+00 1.18581879e+00
7.34545469e-01 -2.23959342e-01 5.00265360e-01 3.79908472e-01
-6.48370385e-01 2.90074963e-02 -7.61041403e-01 6.84069216e-01
1.00913143e+00 -8.16006243e-01 -8.47889066e-01 1.49834216e-01
1.30700362e+00 -3.57071579e-01 -5.91373563e-01 3.77779335e-01
4.11390901e-01 -4.63455379e-01 9.73545790e-01 -7.19394028e-01
4.99729365e-01 4.98147495e-02 -2.51927465e-01 -1.31493008e+00
-5.57515264e-01 -8.49764407e-01 -2.46710867e-01 1.27718246e+00
8.89314413e-01 -7.28518307e-01 2.74814188e-01 5.59904218e-01
-3.13874751e-01 -8.84693205e-01 -1.14453888e+00 -6.23226166e-01
7.40443170e-01 -5.44512928e-01 3.29682052e-01 5.07633507e-01
1.55050337e-01 8.53616655e-01 -5.35489738e-01 -1.10412888e-01
2.77605414e-01 -4.94627684e-01 4.64357197e-01 -7.67474294e-01
-6.79324865e-01 -5.37674010e-01 1.36884719e-01 -1.74509299e+00
5.21507382e-01 -1.01552510e+00 8.79666060e-02 -1.33297694e+00
1.99714899e-01 -1.16944857e-01 -3.54525506e-01 7.21581757e-01
-1.59723416e-01 2.88087219e-01 1.89277172e-01 -6.64505139e-02
-2.85608917e-01 8.95858645e-01 9.13139701e-01 -2.83220768e-01
1.55170737e-02 -2.83919305e-01 -1.01455104e+00 5.81593156e-01
6.68428838e-01 -2.39094391e-01 -3.65219146e-01 -1.12411010e+00
1.33064747e-01 -2.17062950e-01 1.22091703e-01 -6.85847044e-01
2.31413804e-02 3.25661778e-01 2.04094246e-01 -4.41180527e-01
3.98436785e-01 -4.87396777e-01 -2.11355448e-01 3.50071937e-01
-6.14784420e-01 3.49667937e-01 5.75952411e-01 2.29604185e-01
-1.09782487e-01 1.62270904e-01 8.54591429e-01 -6.72044903e-02
-2.42899433e-01 2.32953578e-02 -6.55562818e-01 2.40782350e-01
3.88607204e-01 2.69018799e-01 -3.00400436e-01 -5.01865745e-01
-6.33667350e-01 1.10166483e-01 3.61736536e-01 7.64218569e-01
2.69946277e-01 -1.15377295e+00 -9.06189144e-01 5.04658461e-01
-3.75815444e-02 -2.74752975e-01 -1.48770750e-01 9.58655059e-01
9.56061110e-02 8.00170183e-01 1.86481133e-01 -4.47462082e-01
-1.08018553e+00 5.63971221e-01 5.34293830e-01 -3.97036999e-01
-7.29276657e-01 9.74684954e-01 5.43156266e-01 -5.06994486e-01
3.01387757e-01 -7.20359921e-01 2.80070007e-01 -1.92883924e-01
4.83300656e-01 -1.25237882e-01 3.48120898e-01 -8.11977684e-01
-4.49991375e-01 5.06582558e-01 -3.49109292e-01 -1.20409675e-01
1.23511147e+00 -2.84242094e-01 -4.78354283e-02 5.41203201e-01
1.42340410e+00 2.25842923e-01 -1.07081270e+00 -4.60352153e-01
-3.74164730e-02 1.86547622e-01 2.11300954e-01 -1.19987094e+00
-8.83498251e-01 1.27161467e+00 1.92878336e-01 -2.75499284e-01
9.65901852e-01 1.60088331e-01 8.75831842e-01 3.41889858e-01
2.52313241e-02 -1.03712249e+00 -2.65134484e-01 1.11140358e+00
1.26762271e+00 -1.12032795e+00 -5.12762547e-01 -7.90123120e-02
-6.42913938e-01 8.43780398e-01 5.10372281e-01 7.71509996e-03
4.07545567e-01 7.82723725e-01 3.36044692e-02 2.95826167e-01
-1.31527328e+00 6.30100742e-02 4.18160260e-01 3.32611829e-01
1.06591272e+00 -5.30148298e-02 -1.50961220e-01 8.59265447e-01
-3.77146125e-01 -8.46287459e-02 2.10639909e-01 2.32881784e-01
-1.96141168e-01 -9.90684867e-01 -2.26680823e-02 1.30071908e-01
-8.38280678e-01 -8.39356661e-01 -4.54380482e-01 5.60672998e-01
-3.81050140e-01 7.51005054e-01 1.99033096e-01 -1.49103403e-01
2.83933342e-01 4.28796470e-01 3.36004257e-01 -4.95053560e-01
-7.30658889e-01 2.69646466e-01 2.18330353e-01 -5.87873042e-01
2.11919144e-01 -4.41818714e-01 -1.01017416e+00 -3.03335547e-01
-2.20898136e-01 -3.22109535e-02 5.50642073e-01 9.36032891e-01
6.24914885e-01 5.35073459e-01 3.13332900e-02 -6.97597623e-01
-8.30865204e-01 -1.25878787e+00 1.04984045e-01 4.74461764e-02
7.73847818e-01 -3.77862185e-01 -3.74747962e-01 -9.25257206e-02] | [11.06336498260498, 7.502165794372559] |
61eaae61-3685-4ec4-8745-dcfa0ce0b023 | stable-and-effective-one-step-method-for | null | null | https://ieeexplore.ieee.org/document/9413460 | https://ieeexplore.ieee.org/document/9413460 | Stable and Effective One-Step Method for Person Search | Person search, which requires both pedestrian detection and person re-identification, is a challenging computer vision task applied to real-world scenarios. The challenges faced by detection and re-identification, such as occlusion, poor illumination, confusing background, are still urgent for person search. In addition, one-step methods for person search need to deal with the divergence between two tasks. In this work, we propose an end-to-end model containing the feature extractor, the region proposal network, and the multi-task learning module. In order to process divergence between detection and re-identification, we introduce switchable normalization and gradient centralization to improve the stability of the model. To solve the imbalance problem of hard examples, we introduce focal loss as a classification loss in the multi-task learning module. The experimental results on two bench-marks, i.e., CUHK-SYSU and PRW, well demonstrate that our method outperforms the state-of-the-art one-step methods. | ['Abdulmotaleb El Saddik', 'Rokia Abdeen', 'Jie Yang', 'Xinyao Wang', 'Xuezhi Xiang', 'Ning Lv'] | 2021-05-13 | null | null | null | ieee-international-conference-on-acoustics-10 | ['person-search'] | ['computer-vision'] | [-1.92476884e-01 -7.90233552e-01 2.45894119e-01 -3.65804315e-01
-8.18203747e-01 -3.31239551e-01 3.93607974e-01 -1.31823719e-01
-1.16364717e+00 7.11478770e-01 -7.66156912e-02 9.39422399e-02
2.26214767e-01 -3.48689824e-01 -3.38439435e-01 -7.29197860e-01
3.85586500e-01 4.27514136e-01 4.16643769e-01 2.71935195e-01
5.07879704e-02 1.00737564e-01 -1.46342933e+00 6.60926923e-02
1.02049983e+00 1.05005062e+00 1.79638743e-01 5.38877070e-01
3.47840846e-01 -3.72850075e-02 -5.53519905e-01 -8.18955719e-01
3.83175701e-01 -1.39561877e-01 -4.48976159e-01 1.81658745e-01
8.03474247e-01 -4.25627619e-01 -4.48221207e-01 1.28137183e+00
1.25030327e+00 3.70755464e-01 4.74806786e-01 -1.18393695e+00
-5.55957317e-01 -1.89905670e-02 -9.75842834e-01 4.43288177e-01
3.08445632e-01 6.16737366e-01 5.50705969e-01 -1.07480955e+00
5.25719449e-02 1.55482268e+00 7.63664126e-01 8.02753747e-01
-1.17583025e+00 -9.37258542e-01 5.35828471e-01 6.18029773e-01
-1.71064270e+00 -5.56389689e-01 5.30808806e-01 -4.70615566e-01
4.57636088e-01 2.71127045e-01 5.75362921e-01 1.23022902e+00
-2.87824333e-01 9.71418738e-01 1.09697878e+00 -3.74626637e-01
-1.37739152e-01 4.41713780e-01 4.42771584e-01 6.12463593e-01
4.65619713e-01 2.27258280e-01 -2.86628693e-01 -1.39850929e-01
5.74976861e-01 2.62105703e-01 -2.40309685e-01 -2.39066929e-01
-9.49627638e-01 4.70261663e-01 4.13405806e-01 -1.87761500e-01
-9.99406427e-02 -9.40382406e-02 5.94989777e-01 -1.06309637e-01
3.60504150e-01 -2.65451074e-01 -1.94165528e-01 2.29743123e-01
-9.03013945e-01 3.91265690e-01 3.90034944e-01 9.04178679e-01
3.43871951e-01 -3.65935683e-01 -8.45171094e-01 1.16886854e+00
5.42503417e-01 6.11983836e-01 5.96372068e-01 -1.78468138e-01
7.08423078e-01 4.75210160e-01 4.25296903e-01 -7.26133466e-01
-3.57095420e-01 -8.33855152e-01 -1.02135873e+00 -5.29779680e-02
7.19261944e-01 -2.05579802e-01 -9.68321502e-01 1.61871481e+00
6.13690376e-01 4.71070528e-01 -2.21175373e-01 1.34348893e+00
9.20521200e-01 3.59358251e-01 3.48587662e-01 -7.14490116e-02
1.79185915e+00 -1.40268970e+00 -3.95319879e-01 -5.17549694e-01
1.31897360e-01 -6.56338751e-01 9.40797448e-01 3.45120654e-02
-1.03735101e+00 -9.99190748e-01 -8.62987518e-01 -4.36750650e-02
-3.27531159e-01 7.10031807e-01 1.14413455e-01 7.27130294e-01
-5.99584639e-01 8.63446519e-02 -2.75024384e-01 -4.86600041e-01
4.80036616e-01 3.02462935e-01 -2.14571401e-01 -1.50412858e-01
-1.13632548e+00 7.00975716e-01 4.31248277e-01 4.88369197e-01
-6.78615510e-01 -4.48702931e-01 -5.40179968e-01 1.79051265e-01
5.16076863e-01 -9.82980788e-01 1.06842768e+00 -5.27446866e-01
-1.19588590e+00 1.24226367e+00 -2.33278111e-01 -2.24795535e-01
1.09717977e+00 -3.11944425e-01 -4.10116166e-01 -3.16501737e-01
2.93139309e-01 3.59458596e-01 8.19870055e-01 -1.10130298e+00
-1.21568191e+00 -6.43651128e-01 -3.79329801e-01 4.21951294e-01
-2.73233682e-01 4.18180823e-01 -1.14797342e+00 -5.76297462e-01
-1.38084084e-01 -8.35583925e-01 -3.02763283e-01 1.36769712e-01
-5.29699445e-01 -5.29377580e-01 5.22651017e-01 -9.23860550e-01
1.16336024e+00 -2.17844796e+00 -5.08305840e-02 1.52282506e-01
1.28016919e-01 4.68582809e-01 -1.45917209e-02 -4.84911650e-01
6.31276742e-02 -1.72372505e-01 2.00882703e-01 -8.94517481e-01
8.91551524e-02 -4.26970333e-01 1.47465125e-01 7.91544914e-01
-1.49692520e-01 7.71569133e-01 -6.81992829e-01 -7.37844348e-01
2.33498320e-01 3.27618062e-01 -1.12248175e-01 2.30285272e-01
3.25748503e-01 5.67967892e-01 -4.19335783e-01 7.80020833e-01
1.00863516e+00 -2.24569649e-01 -4.56206083e-01 -3.13741833e-01
-2.11891755e-01 -2.77958483e-01 -1.50227737e+00 1.48027074e+00
-1.41178116e-01 2.01543897e-01 2.06999078e-01 -7.59532332e-01
6.49102807e-01 -1.59806814e-02 1.91005562e-02 -8.51388276e-01
3.33406366e-02 2.47227371e-01 -7.77472332e-02 -4.06423956e-01
2.08205402e-01 3.17534089e-01 -4.40283902e-02 5.63805737e-02
-2.66760826e-01 7.19085038e-01 2.31280446e-01 -2.20562518e-01
5.09417236e-01 -5.04020564e-02 1.48434654e-01 -2.20229954e-01
1.06726801e+00 -3.91882628e-01 9.02520537e-01 8.86687636e-01
-7.96299458e-01 6.63595557e-01 -1.37867361e-01 -6.76986337e-01
-1.01539540e+00 -9.46800053e-01 -1.21786125e-01 1.10039222e+00
6.70149505e-01 -2.44738087e-02 -7.59209692e-01 -6.48607552e-01
2.15777069e-01 2.24767357e-01 -3.63377601e-01 -2.09253073e-01
-7.27198243e-01 -1.30603588e+00 5.79335153e-01 4.34102416e-01
1.07268524e+00 -6.88856840e-01 -4.67110127e-01 1.63933188e-01
-2.95406640e-01 -1.30920708e+00 -1.15875304e+00 -4.50771511e-01
-1.79071903e-01 -9.81920063e-01 -1.44827342e+00 -1.04727769e+00
7.61839688e-01 4.73765045e-01 7.74458587e-01 1.71400264e-01
-7.28179336e-01 2.73439765e-01 1.53605535e-03 -2.27598146e-01
2.53218234e-01 5.10122143e-02 2.10680813e-01 3.89365137e-01
4.82630432e-01 -1.37077853e-01 -1.17991555e+00 7.95972586e-01
-2.01604962e-01 -1.81529652e-02 4.79498923e-01 9.28330660e-01
6.71981394e-01 4.99707572e-02 3.16775292e-01 -1.51212826e-01
6.50446534e-01 -1.42086633e-02 -7.73978531e-01 8.27338517e-01
-6.47452295e-01 -3.48359674e-01 3.06796074e-01 -8.26622725e-01
-1.14553010e+00 1.94531217e-01 -1.31166738e-03 -2.51161724e-01
-7.02247694e-02 -1.69400021e-01 -4.51294422e-01 -2.54685611e-01
4.66379464e-01 4.93529826e-01 -2.44529203e-01 -7.02081740e-01
1.35038823e-01 8.46090496e-01 8.66289258e-01 -4.17456210e-01
9.38894451e-01 3.59005362e-01 -2.85187304e-01 -5.74000537e-01
-7.92778373e-01 -8.75899613e-01 -6.26278758e-01 -2.85777956e-01
8.78532350e-01 -1.41799152e+00 -1.06753969e+00 9.64048147e-01
-1.41479933e+00 3.81587744e-02 9.30990055e-02 3.73834670e-01
-5.05514853e-02 6.26082420e-01 -3.76392931e-01 -1.11897969e+00
-7.23042309e-01 -1.10519218e+00 1.07807076e+00 9.42771971e-01
2.60087430e-01 -5.70232868e-01 -2.05878064e-01 5.55116534e-01
3.11160415e-01 -8.45645443e-02 2.13501155e-01 -5.60177624e-01
-5.86167753e-01 -4.30671901e-01 -7.96496451e-01 1.52579263e-01
-8.50869119e-02 -5.43766618e-01 -1.02671361e+00 -7.62292802e-01
-1.79018646e-01 -2.85313159e-01 1.25935447e+00 3.80118459e-01
1.30387950e+00 -2.40364328e-01 -7.01941192e-01 9.55919981e-01
1.15188730e+00 6.56016171e-02 3.08094531e-01 5.14863193e-01
7.39159107e-01 4.63615865e-01 5.18665373e-01 4.81865793e-01
7.25417256e-01 9.84997094e-01 -2.51627900e-02 -3.21576238e-01
-3.99436384e-01 -1.87690556e-01 6.14092574e-02 -1.07068904e-02
-8.54418054e-02 -1.55891672e-01 -8.29078794e-01 3.42630923e-01
-2.30441022e+00 -1.04352295e+00 2.91758813e-02 2.48023582e+00
7.27354944e-01 1.80730954e-01 5.07556438e-01 -2.21116632e-01
1.17724156e+00 -4.21792828e-02 -7.82790303e-01 5.13348460e-01
-2.68781871e-01 -4.19586807e-01 5.84804595e-01 5.15236557e-01
-1.60029936e+00 9.88736928e-01 5.38084650e+00 1.02948189e+00
-8.59772384e-01 3.60687554e-01 8.64821970e-01 -2.66491473e-01
4.94800657e-01 -3.69586617e-01 -1.60515165e+00 1.02204752e+00
2.76273996e-01 -1.01168990e-01 3.61407131e-01 7.35936105e-01
1.51585996e-01 -1.36154324e-01 -1.05885661e+00 1.77294302e+00
3.54708046e-01 -7.28865325e-01 -3.50452542e-01 -2.30460837e-01
3.47190529e-01 -3.38953465e-01 1.60341948e-01 4.41109568e-01
3.87780135e-03 -8.45605612e-01 7.46081710e-01 6.11100554e-01
6.75277114e-01 -5.68911433e-01 7.73343265e-01 3.34691703e-01
-1.57239246e+00 -3.17953974e-01 -4.33072865e-01 2.94127941e-01
3.80790085e-01 5.18206775e-01 -2.40457267e-01 4.30340588e-01
1.07650054e+00 4.03940856e-01 -9.37293947e-01 1.81497502e+00
-2.46554110e-02 2.41421647e-02 -4.55302179e-01 -4.34871316e-02
-1.12624489e-01 -2.06565544e-01 5.46254277e-01 1.44344473e+00
9.32450742e-02 -1.27571806e-01 7.28904963e-01 7.91238546e-01
1.93319812e-01 -4.02797312e-02 2.15782179e-03 6.77454829e-01
2.99529225e-01 1.25264490e+00 -3.47351819e-01 -4.20612961e-01
-3.94802779e-01 1.44401562e+00 3.03540260e-01 6.35716856e-01
-1.10258341e+00 -2.10171446e-01 5.75074553e-01 4.61933352e-02
4.74438891e-02 -1.28723115e-01 -1.98735178e-01 -1.34365284e+00
5.29327333e-01 -6.67244673e-01 6.73432350e-01 -2.81317383e-01
-1.64349961e+00 4.18012589e-01 -1.30219340e-01 -1.05565250e+00
1.64489016e-01 -4.94348377e-01 -6.56701088e-01 1.46263826e+00
-1.72715032e+00 -1.41019022e+00 -6.87757075e-01 6.57863855e-01
7.66996205e-01 -4.58181590e-01 2.54510134e-01 9.87396836e-01
-1.25727928e+00 1.28821230e+00 -5.43143488e-02 3.67872357e-01
1.08487177e+00 -8.04694772e-01 4.29563344e-01 1.07455921e+00
-4.13284808e-01 4.06863183e-01 4.86341387e-01 -6.28890157e-01
-9.78796005e-01 -1.15017211e+00 6.95218205e-01 -2.72291243e-01
1.89516410e-01 -6.07068896e-01 -6.91836178e-01 2.72452235e-01
-2.54663110e-01 3.39512080e-01 5.23203909e-01 1.49287969e-01
-1.95349574e-01 -4.31688786e-01 -1.08005941e+00 7.58975208e-01
1.21597183e+00 -2.16438234e-01 -1.78233936e-01 5.37900507e-01
3.71286452e-01 -4.49106961e-01 -2.47547239e-01 2.48782828e-01
6.53422713e-01 -7.72303283e-01 1.48341537e+00 -4.56864893e-01
-4.75562632e-01 -4.08920735e-01 1.26440689e-01 -1.07415664e+00
-6.73745513e-01 -5.65310359e-01 -2.02361345e-02 1.36556423e+00
3.02397072e-01 -7.28279650e-01 7.91490138e-01 9.08336818e-01
3.29196870e-01 -5.49174964e-01 -1.28958142e+00 -9.43623781e-01
-2.43903935e-01 2.13499337e-01 3.99145871e-01 3.10575932e-01
-5.21251559e-01 5.07299006e-01 -6.98962688e-01 3.61621797e-01
1.20502448e+00 1.52113801e-02 9.01287973e-01 -1.32787776e+00
-3.00932825e-01 -6.24509275e-01 -2.12360516e-01 -1.30454159e+00
2.49485392e-03 -5.24536192e-01 1.05851561e-01 -1.33858728e+00
7.17746019e-01 -4.71820146e-01 -3.17013472e-01 1.97099224e-01
-7.85466790e-01 -1.53025091e-01 3.25254053e-01 4.84074175e-01
-9.05645967e-01 7.86497712e-01 9.99291539e-01 -4.48123991e-01
-2.88174987e-01 4.84518766e-01 -6.65574431e-01 6.32464647e-01
6.47562563e-01 -1.60618737e-01 1.04331393e-02 -5.94994664e-01
-3.48491848e-01 -5.39547563e-01 8.83956552e-01 -1.16513181e+00
8.42829287e-01 8.28461647e-02 9.31675434e-01 -7.50344455e-01
5.19629359e-01 -6.79906249e-01 -1.87845558e-01 6.31269872e-01
-1.22316763e-01 1.77772626e-01 1.31240636e-01 5.69436073e-01
-1.33614214e-02 -1.20915279e-01 1.17177093e+00 -2.30075523e-01
-7.93840349e-01 7.63896346e-01 3.61717254e-01 -3.06623038e-02
1.15773654e+00 -3.75125498e-01 -4.08882618e-01 8.70746896e-02
-4.87218827e-01 1.00038218e+00 1.53987840e-01 4.38456923e-01
7.33572006e-01 -1.36983240e+00 -1.09172082e+00 1.87472016e-01
3.04238573e-02 6.12138808e-02 4.53431129e-01 7.29142487e-01
-6.40649945e-02 2.66953081e-01 5.39074466e-03 -5.16508818e-01
-1.66238046e+00 5.89150786e-01 6.41705930e-01 -3.18549186e-01
-5.26664257e-01 1.02404761e+00 3.40324610e-01 -2.91131616e-01
8.51270556e-01 2.40733415e-01 -1.51671842e-01 7.78973382e-03
8.03571582e-01 5.40267646e-01 -3.58166665e-01 -5.67803383e-01
-6.24622464e-01 7.90629327e-01 -4.42723334e-01 -1.71084404e-02
6.94336653e-01 -4.19168413e-01 1.74687713e-01 -6.93691671e-02
8.51854503e-01 -4.01387662e-01 -1.33069766e+00 -4.18721497e-01
-4.77765277e-02 -6.41643524e-01 -2.10085779e-01 -8.66582036e-01
-8.38233829e-01 7.76118934e-01 1.32794690e+00 -2.70921409e-01
8.53407800e-01 -1.62414879e-01 8.89593899e-01 2.84518749e-01
2.95211434e-01 -1.42948699e+00 4.13586050e-02 3.06948036e-01
7.99709737e-01 -1.78321326e+00 1.27705425e-01 -4.89220291e-01
-3.30598772e-01 6.30302012e-01 1.10909832e+00 2.10937873e-01
5.65336227e-01 -3.28409076e-01 -6.86492324e-02 4.23150808e-01
-2.32817411e-01 -4.17010695e-01 5.31759739e-01 5.28507531e-01
-1.40325561e-01 2.59912722e-02 -2.76655495e-01 8.58252048e-01
1.93147093e-01 -7.46870488e-02 -2.54139304e-01 4.80626762e-01
-4.80870724e-01 -8.28759015e-01 -7.31167018e-01 3.00363362e-01
-3.11265975e-01 -3.26886997e-02 -2.46309936e-01 4.35474068e-01
4.84543651e-01 9.53354418e-01 -6.92936257e-02 -2.13803694e-01
5.70982933e-01 -6.76093325e-02 2.83960134e-01 -2.47450858e-01
-5.39452553e-01 1.20178677e-01 -9.70713794e-02 -3.07103634e-01
-8.00646171e-02 -6.54370546e-01 -6.90143883e-01 -1.28195807e-01
-4.82108891e-01 -3.65922488e-02 3.86233747e-01 7.40844607e-01
3.53169918e-01 2.96598345e-01 5.14019310e-01 -6.82880104e-01
-9.80493963e-01 -9.61970866e-01 -4.15010661e-01 5.39796352e-01
3.42770606e-01 -7.18045712e-01 -2.32431605e-01 -1.71989739e-01] | [14.79964542388916, 0.8364032506942749] |
ba2bedfd-8832-4509-952b-797b6f98c364 | probabilistic-regular-tree-priors-for | 2306.08506 | null | https://arxiv.org/abs/2306.08506v1 | https://arxiv.org/pdf/2306.08506v1.pdf | Probabilistic Regular Tree Priors for Scientific Symbolic Reasoning | Symbolic Regression (SR) allows for the discovery of scientific equations from data. To limit the large search space of possible equations, prior knowledge has been expressed in terms of formal grammars that characterize subsets of arbitrary strings. However, there is a mismatch between context-free grammars required to express the set of syntactically correct equations, missing closure properties of the former, and a tree structure of the latter. Our contributions are to (i) compactly express experts' prior beliefs about which equations are more likely to be expected by probabilistic Regular Tree Expressions (pRTE), and (ii) adapt Bayesian inference to make such priors efficiently available for symbolic regression encoded as finite state machines. Our scientific case studies show its effectiveness in soil science to find sorption isotherms and for modeling hyper-elastic materials. | ['Steffen Staab', 'Wolfgang Nowak', 'Amin Totounferoush', 'Tim Schneider'] | 2023-06-14 | null | null | null | null | ['symbolic-regression', 'bayesian-inference'] | ['knowledge-base', 'methodology'] | [ 5.67624152e-01 5.74105799e-01 -9.73622128e-02 -5.47003329e-01
-5.73183060e-01 -6.03020787e-01 3.60107332e-01 5.43118827e-02
1.48128167e-01 9.22338128e-01 -1.68158591e-01 -1.19753790e+00
-6.32271171e-01 -1.11018956e+00 -9.79947448e-01 -3.05542916e-01
-1.37709990e-01 8.49640489e-01 1.98451862e-01 -4.44314033e-02
3.29679608e-01 8.56779277e-01 -1.60238695e+00 1.52554914e-01
9.91522372e-01 7.12377071e-01 3.73875171e-01 7.02344537e-01
-3.97600412e-01 1.02389514e+00 -2.97620803e-01 -2.42277279e-01
-3.13448191e-01 -2.07044929e-01 -6.48487031e-01 -2.62086213e-01
2.95860041e-02 -2.95981646e-01 -7.35230967e-02 1.19882524e+00
-2.09526226e-01 -6.00834331e-03 9.73485231e-01 -9.96019542e-01
-5.35700381e-01 8.94777477e-01 -4.85274335e-03 -1.56494483e-01
7.13226974e-01 -6.54554088e-03 9.14946079e-01 -1.34556159e-01
7.05935121e-01 1.46052635e+00 4.92300540e-01 3.91420096e-01
-1.64613426e+00 -7.02087522e-01 1.69272989e-01 -1.48470074e-01
-1.70884252e+00 -5.51865757e-01 4.25325692e-01 -5.51441789e-01
1.23372757e+00 5.52929640e-01 6.90207601e-01 1.11102986e+00
3.54948968e-01 5.02034903e-01 1.20377696e+00 -6.86345339e-01
7.50992477e-01 1.84514120e-01 3.97807598e-01 7.57047832e-01
6.03937924e-01 2.98423827e-01 -5.55490434e-01 -6.17150724e-01
9.84272778e-01 -4.78683800e-01 9.40706730e-02 -1.53433293e-01
-6.15968645e-01 9.19232666e-01 -3.76306981e-01 5.98721392e-03
-2.97318608e-01 3.76520783e-01 -2.92084277e-01 -6.36468222e-03
6.11538067e-02 5.98525882e-01 -7.30295897e-01 3.90404388e-02
-7.51177311e-01 6.84496403e-01 1.44175744e+00 1.14726770e+00
6.99475765e-01 6.44630641e-02 1.62440300e-01 2.90338516e-01
8.89386833e-01 1.10630548e+00 -1.15279458e-01 -1.27908051e+00
2.02713106e-02 2.54946440e-01 4.81989056e-01 -9.91006613e-01
5.80970533e-02 -7.49656782e-02 -2.57473558e-01 1.56677246e-01
6.32505715e-01 -9.20003876e-02 -1.00020766e+00 1.81460285e+00
-1.39765022e-02 1.22898296e-01 1.42706960e-01 4.04603094e-01
4.59612429e-01 7.18066931e-01 4.04873639e-01 -3.10005188e-01
1.16449058e+00 4.35560226e-01 -5.44526637e-01 -3.08613807e-01
5.06802797e-01 -3.13729733e-01 5.65260291e-01 5.84396064e-01
-9.55635309e-01 -3.77603024e-02 -8.84144545e-01 2.06366003e-01
-3.66418958e-01 -1.99098498e-01 1.39434552e+00 1.04496431e+00
-7.83488154e-01 6.04972720e-01 -1.21811891e+00 1.89179093e-01
2.16072708e-01 6.07313395e-01 -1.08220324e-01 9.29388255e-02
-1.32361162e+00 1.01050520e+00 3.23316902e-01 2.24341914e-01
-5.82690001e-01 -6.46969676e-01 -1.11796486e+00 4.21739109e-02
4.56368506e-01 -5.03384769e-01 1.22281444e+00 -6.84995234e-01
-1.77470756e+00 5.05148530e-01 -5.97319484e-01 -2.99907804e-01
2.04783566e-02 1.57913655e-01 -3.69793653e-01 3.37531269e-02
-5.93560375e-02 4.28128988e-01 4.39986140e-01 -1.22139919e+00
-2.68014044e-01 -3.83291364e-01 5.47834970e-02 -2.28330553e-01
3.76689315e-01 2.48394653e-01 -1.36808097e-01 -1.69757053e-01
5.50039828e-01 -9.04801071e-01 -4.81262684e-01 -7.51162544e-02
-5.21519601e-01 -3.40551704e-01 1.75754815e-01 -7.24348247e-01
1.16624343e+00 -1.69424307e+00 3.14294584e-02 8.90997350e-01
-3.41020487e-02 -3.31202090e-01 3.24868709e-01 8.86868238e-02
-8.90130699e-02 4.04904008e-01 -3.89943451e-01 3.75539541e-01
3.05609971e-01 7.94747293e-01 -7.85031378e-01 2.04121381e-01
3.80545080e-01 6.21093988e-01 -7.27774978e-01 -6.40172899e-01
1.87123999e-01 1.17085963e-01 -4.52239275e-01 4.24189530e-02
-8.25807214e-01 8.05135518e-02 -1.13637578e+00 6.03072524e-01
7.14680076e-01 -1.62428483e-01 5.42830586e-01 2.52286047e-01
-3.23862195e-01 5.82345068e-01 -1.57101548e+00 1.20143008e+00
-1.70827135e-01 -7.97280073e-02 -3.98820303e-02 -8.41328263e-01
1.09655118e+00 1.61804572e-01 3.47982496e-01 -1.37992293e-01
-6.49934411e-02 1.07055649e-01 -2.93733943e-02 -6.93053842e-01
1.43845752e-01 -3.53860915e-01 -2.10822538e-01 5.68412721e-01
-9.22245979e-02 -6.06374502e-01 1.83791772e-01 4.72823642e-02
9.20242190e-01 8.20118189e-01 2.41737649e-01 -5.56762815e-01
1.87940553e-01 1.08400144e-01 7.57714927e-01 1.19392097e+00
4.71154809e-01 2.07041398e-01 7.10313916e-01 -3.50535542e-01
-8.21475625e-01 -1.16326594e+00 -4.74878430e-01 7.46671796e-01
-1.14911757e-01 -4.00697678e-01 -2.58816689e-01 -5.60638607e-02
3.02566975e-01 1.41698313e+00 -4.17943031e-01 1.90149710e-01
-2.97574252e-01 -8.24641764e-01 6.13621891e-01 4.92209852e-01
-3.13100070e-01 -7.17686892e-01 -7.18092620e-01 3.16490859e-01
-1.50210075e-02 -1.00108981e+00 3.38443339e-01 6.92865491e-01
-1.00166619e+00 -9.32670832e-01 1.60318673e-01 -8.58414397e-02
6.46399498e-01 -4.20229822e-01 9.71274734e-01 -1.97138116e-01
-2.50039697e-01 2.79062271e-01 -5.13392389e-02 -7.04940200e-01
-8.84064674e-01 -3.96528423e-01 -1.50075227e-01 -5.67373872e-01
5.47526419e-01 -7.71486938e-01 3.24713081e-01 4.73625809e-02
-8.16602886e-01 1.05974212e-01 4.43250895e-01 3.08204293e-01
5.84705830e-01 8.32679346e-02 -2.64738258e-02 -1.09897017e+00
3.88378829e-01 -4.02163208e-01 -1.10911131e+00 8.45572054e-01
-7.29370773e-01 7.53190696e-01 1.92511737e-01 -4.55721289e-01
-1.35750282e+00 3.04436296e-01 3.94134745e-02 7.03997090e-02
-5.25783122e-01 1.03914738e+00 -1.97259068e-01 1.23726971e-01
6.97147846e-01 1.49499059e-01 -2.39987262e-02 -2.04870373e-01
1.87704954e-02 4.31888223e-01 4.91006345e-01 -1.63143170e+00
4.72613454e-01 4.74046543e-02 6.01140797e-01 -9.09575045e-01
-6.23717964e-01 2.92549670e-01 -4.33638513e-01 -6.72008190e-03
5.02934933e-01 -6.99300587e-01 -9.69873190e-01 -1.24647439e-01
-1.16733897e+00 -2.54012376e-01 -1.86241910e-01 5.76244891e-01
-5.77739835e-01 5.02610505e-01 -2.12689236e-01 -1.51859963e+00
1.24289699e-01 -1.11994290e+00 9.28493857e-01 1.11180216e-01
-8.03627133e-01 -7.59495974e-01 9.46724713e-02 1.40080424e-02
1.43523648e-01 3.50155383e-01 1.25633371e+00 -6.22322202e-01
-5.65079629e-01 -3.01848143e-01 1.09632192e-02 -1.56604737e-01
-2.14048997e-01 5.74716628e-01 -8.62974524e-01 3.38645637e-01
-2.23880887e-01 -2.17458397e-01 3.10511917e-01 5.88792801e-01
1.16734993e+00 -3.68708998e-01 -6.11479104e-01 4.56308991e-01
1.08448339e+00 3.44597101e-01 8.95137787e-01 -1.88082859e-01
1.66307449e-01 7.60396779e-01 5.05046621e-02 4.68646199e-01
3.45845431e-01 4.72304046e-01 -2.67449990e-02 6.15287364e-01
5.18004477e-01 -4.56460148e-01 4.45081890e-01 4.26765978e-01
-3.04145575e-01 -1.34338006e-01 -1.07157385e+00 1.12197518e-01
-1.71895921e+00 -9.31741178e-01 -3.34531307e-01 2.14106727e+00
1.37492132e+00 1.95630774e-01 -3.43145251e-01 -6.98337033e-02
6.03397846e-01 -4.66595262e-01 -5.60642123e-01 -3.51202667e-01
-1.34819537e-01 8.06011438e-01 7.08440125e-01 9.48245287e-01
-6.37151539e-01 7.46728122e-01 7.82275867e+00 6.90065265e-01
-6.14771307e-01 -3.67336959e-01 2.19574556e-01 4.17823076e-01
-9.50505078e-01 7.08898365e-01 -1.00825870e+00 2.36284226e-01
1.28256786e+00 -1.64528847e-01 6.12856686e-01 6.53228104e-01
6.12261258e-02 -4.07538831e-01 -1.14182580e+00 3.89649034e-01
-4.69531655e-01 -1.14406228e+00 2.26605684e-01 9.88193378e-02
3.99283022e-01 -4.48058039e-01 -3.47204983e-01 1.67995974e-01
1.13401723e+00 -1.37094247e+00 9.14397061e-01 9.84047949e-01
8.25201571e-01 -5.53775311e-01 3.19454879e-01 4.06927228e-01
-7.54796624e-01 8.32129866e-02 -5.84567785e-01 -3.33228052e-01
-2.25668415e-01 7.28291810e-01 -7.62313008e-01 5.97503960e-01
3.06870311e-01 2.09807634e-01 -2.36917272e-01 4.30720717e-01
-5.33687294e-01 9.64991331e-01 -1.09386444e+00 -3.07178706e-01
-1.59623608e-01 -3.52926433e-01 4.10862625e-01 1.16211796e+00
3.94518375e-01 5.99147916e-01 -8.38368237e-02 1.64292669e+00
7.43690670e-01 -4.67568547e-01 -5.60753822e-01 -3.65577132e-01
7.29746103e-01 4.97166485e-01 -6.31833911e-01 -1.07680865e-01
-2.12012902e-01 8.18842500e-02 -1.31741136e-01 4.99523431e-01
-5.04450738e-01 -3.55193526e-01 4.28978682e-01 1.75225437e-01
2.63570189e-01 -5.49285710e-01 -6.08460248e-01 -1.09955060e+00
-2.81446397e-01 -8.37629616e-01 2.74914831e-01 -1.13014674e+00
-1.00101781e+00 -1.11844212e-01 6.06952131e-01 -1.78834110e-01
-7.26694286e-01 -1.02082348e+00 -3.19717884e-01 1.35325062e+00
-9.79364276e-01 -9.98398304e-01 3.07123750e-01 2.55242825e-01
-8.48773867e-02 7.04104379e-02 1.45175898e+00 -5.27116776e-01
-3.30252051e-01 1.84236512e-01 2.94287764e-02 -2.81572223e-01
5.51338084e-02 -1.28348279e+00 1.94543704e-01 6.83123589e-01
-2.54862905e-01 1.17414486e+00 1.21194994e+00 -1.26378739e+00
-1.86467683e+00 -4.66794848e-01 9.86437619e-01 -6.69946373e-01
7.23800540e-01 -2.16837704e-01 -8.90275478e-01 8.11963081e-01
-6.48240507e-01 -4.03295368e-01 6.17002785e-01 4.01677728e-01
-5.11999369e-01 1.95061997e-01 -1.08303273e+00 5.12354553e-01
7.30293334e-01 -4.77205873e-01 -5.86504459e-01 9.69818160e-02
3.61914158e-01 -5.22789717e-01 -1.06816494e+00 4.20849591e-01
9.66586590e-01 -3.56672555e-01 9.09807146e-01 -9.27996755e-01
4.66356397e-01 -4.58182812e-01 -4.75803792e-01 -4.21744436e-01
-2.34453738e-01 -7.72994161e-01 -2.11113930e-01 8.59131634e-01
6.18224502e-01 -5.87969720e-01 7.01701105e-01 1.57183945e+00
9.08173099e-02 -4.92992461e-01 -9.72292423e-01 -6.41149461e-01
2.09570900e-01 -9.03891325e-01 7.10058153e-01 7.57444501e-01
8.76719803e-02 -1.70760170e-01 4.07322943e-02 5.51061511e-01
7.57599115e-01 2.77797639e-01 3.45314801e-01 -1.72449195e+00
-6.97919250e-01 -2.57301211e-01 -1.78160667e-01 -1.03984165e+00
3.51064086e-01 -8.89303923e-01 2.57811099e-01 -1.16755104e+00
2.59496003e-01 -6.88283563e-01 2.01836884e-01 6.27144694e-01
1.93431124e-01 -7.30940342e-01 -4.39535379e-01 3.38908136e-02
-1.07179932e-01 1.00882776e-01 8.38574290e-01 4.97710407e-02
-6.03937730e-02 1.25541180e-01 -9.24251139e-01 8.13271701e-01
4.49139237e-01 -8.25922728e-01 -3.75462562e-01 -2.09414229e-01
1.01747501e+00 6.05470777e-01 5.67595780e-01 -3.85363340e-01
1.85888156e-01 -9.55926657e-01 4.83811110e-01 -4.35392737e-01
-4.25204933e-02 -6.35022521e-01 8.46236885e-01 3.70146900e-01
-6.39095545e-01 -4.53443766e-01 2.91019499e-01 5.57904541e-01
4.33441550e-01 -8.37081432e-01 2.49186084e-01 -1.19007640e-01
-2.09020749e-01 -2.09928408e-01 -8.36984694e-01 -2.68271476e-01
4.78335917e-01 -1.80324867e-01 5.54272830e-02 -2.37167269e-01
-9.22837675e-01 5.30676804e-02 3.18951339e-01 -2.22152784e-01
5.66474378e-01 -6.07158780e-01 -5.48711538e-01 5.60250916e-02
-2.45869428e-01 2.13183895e-01 -1.88754231e-01 1.24966003e-01
-6.16778195e-01 5.13330162e-01 4.16192710e-02 -3.66015494e-01
-7.66806424e-01 1.83667496e-01 2.41523653e-01 -2.66231984e-01
-4.63452905e-01 6.84357941e-01 -1.46245748e-01 -4.20391530e-01
6.82244599e-02 -5.56280375e-01 2.09314808e-01 -6.80295408e-01
2.63147980e-01 1.95711002e-01 -2.98915297e-01 5.24696382e-03
-4.08222795e-01 2.57979274e-01 1.31028056e-01 -3.85411203e-01
1.60477412e+00 2.33847186e-01 -2.99526036e-01 5.73399961e-01
2.71301925e-01 5.14936261e-02 -1.08229697e+00 -1.42434672e-01
9.79253575e-02 -1.69038311e-01 1.46921933e-01 -1.05178070e+00
-2.62327760e-01 5.56813955e-01 9.30442661e-02 1.12428725e-01
5.08308351e-01 6.32917434e-02 1.54372215e-01 1.00875890e+00
4.51017171e-01 -8.06492567e-01 -8.35577071e-01 4.66125309e-01
8.19489479e-01 -6.27265573e-01 5.58739483e-01 -7.39468932e-01
-2.83542424e-01 1.59758162e+00 2.07259178e-01 9.68005732e-02
7.01002896e-01 9.37473536e-01 -5.21159768e-01 -3.25282872e-01
-6.89678848e-01 1.05631845e-02 3.64645245e-03 8.06776345e-01
3.59727770e-01 2.40695059e-01 7.19106868e-02 1.06167483e+00
-3.72719735e-01 4.42031682e-01 4.60807323e-01 1.25220346e+00
-6.07179821e-01 -1.09546793e+00 -7.46086955e-01 5.76674461e-01
-2.91943043e-01 -9.17615741e-02 -2.48384491e-01 6.10940754e-01
-8.75354279e-03 1.06471813e+00 -2.10821331e-01 3.61964107e-02
8.08471814e-02 2.85677105e-01 1.03017080e+00 -7.22020984e-01
1.43902242e-01 -1.04032420e-02 4.41516757e-01 -2.36721039e-01
-5.53845167e-02 -1.00040483e+00 -1.24741530e+00 -2.94497311e-01
-4.59826291e-01 2.61159688e-01 8.83532822e-01 1.26392758e+00
1.01167105e-01 3.94093156e-01 5.72225340e-02 -3.45148206e-01
-8.75285387e-01 -6.66058421e-01 -7.42216945e-01 -2.75270462e-01
-2.64706463e-01 -6.62914991e-01 -1.67926699e-01 3.25994492e-01] | [8.551045417785645, 6.544299602508545] |
ac945c50-0234-4f2b-b969-32cafdca5fcc | random-forest-classifier-for-eeg-based | 2106.04510 | null | https://arxiv.org/abs/2106.04510v1 | https://arxiv.org/pdf/2106.04510v1.pdf | Random Forest classifier for EEG-based seizure prediction | Epileptic seizure prediction has gained considerable interest in the computational Epilepsy research community. This paper presents a Machine Learning based method for epileptic seizure prediction which outperforms state-of-the art methods. We compute a probability for a given epoch, of being pre-ictal against interictal using the Random Forest classifier and introduce new concepts to enhance the robustness of the algorithm to false alarms. We assessed our method on 20 patients of the benchmark scalp EEG CHB-MIT dataset for a seizure prediction horizon (SPH) of 5 minutes and a seizure occurrence period (SOP) of 30 minutes. Our approach achieves a sensitivity of 82.07 % and a low false positive rate (FPR) of 0.0799 /h. We also tested our approach on intracranial EEG recordings. | ['Mario Chavez', 'Remy Ben Messaoud'] | 2021-06-02 | null | null | null | null | ['seizure-prediction'] | ['medical'] | [ 1.84711218e-01 1.43301725e-01 2.70838410e-01 -3.99370581e-01
-6.81177974e-01 -2.38061666e-01 5.12619376e-01 4.30269450e-01
-3.20007116e-01 1.14721501e+00 -1.04483046e-01 -4.55709696e-01
-3.37376177e-01 -5.40659189e-01 -2.73120254e-01 -7.17868030e-01
-9.50006425e-01 2.54615486e-01 4.31266189e-01 3.44070911e-01
3.74622643e-01 4.86821681e-01 -1.18937111e+00 5.87716997e-01
6.77681565e-01 1.22684360e+00 7.90306106e-02 4.67368454e-01
7.05625117e-01 6.48722410e-01 -1.06458473e+00 1.12084290e-02
1.99400276e-01 -2.43340418e-01 -6.53139234e-01 -1.03069454e-01
-6.49888575e-01 1.56817600e-01 -1.37411337e-02 7.87786543e-01
7.51665533e-01 -5.82540095e-01 7.09030151e-01 -1.42845619e+00
4.28259581e-01 5.86949587e-01 -4.73572940e-01 7.88529694e-01
4.15494293e-01 -1.76103607e-01 2.02234641e-01 -4.08399969e-01
3.50722432e-01 2.88084775e-01 6.90283298e-01 2.68516481e-01
-1.11699593e+00 -1.12375832e+00 -3.23492944e-01 5.01343489e-01
-1.82454252e+00 -2.29560062e-01 3.12901437e-01 -7.56404996e-01
1.19710994e+00 3.42250884e-01 1.14341712e+00 1.06523955e+00
1.15133142e+00 3.09218615e-01 1.53181458e+00 -3.14623177e-01
6.66544914e-01 -1.96444958e-01 1.89386215e-02 -1.61010548e-02
1.23268522e-01 4.71566379e-01 -7.37536728e-01 -4.81331766e-01
4.44077313e-01 -3.63295935e-02 -4.34308469e-01 2.52714753e-01
-1.19293725e+00 8.37807119e-01 -1.02214731e-01 5.44683099e-01
-7.56892741e-01 -1.97516918e-01 2.51206964e-01 3.00665677e-01
5.68302631e-01 5.91503024e-01 -7.37040699e-01 -4.51763481e-01
-1.34579217e+00 2.98602623e-03 1.02937007e+00 4.95836705e-01
1.86773762e-01 -1.24133192e-01 -1.46104410e-01 4.21047807e-01
-2.05898732e-01 1.18215166e-01 8.31722140e-01 4.02141400e-02
-2.06683621e-01 4.57454890e-01 1.19315470e-02 -3.58684629e-01
-7.13045657e-01 -8.19670796e-01 -8.67600441e-01 -1.87783130e-02
-1.06131295e-02 -5.63317597e-01 -8.12758803e-01 1.15249908e+00
-3.83742303e-01 6.50823414e-01 5.86612970e-02 3.58701199e-01
1.86209634e-01 3.30984473e-01 -1.35387471e-02 -8.68721962e-01
1.06248415e+00 -2.10289881e-01 -5.50202608e-01 -2.02251803e-02
7.29390740e-01 -6.67902887e-01 1.77517831e-01 1.11778188e+00
-6.40213966e-01 2.05205724e-01 -9.18227375e-01 1.22207093e+00
-6.48064017e-02 -3.07284500e-02 5.22569895e-01 6.65779233e-01
-1.04986167e+00 4.64393526e-01 -1.20289242e+00 -2.32885659e-01
3.16638917e-01 6.82417274e-01 -1.57765731e-01 3.84236515e-01
-1.08723092e+00 1.08793557e+00 4.96435612e-01 -5.38607895e-01
-9.44753528e-01 -7.38477528e-01 -2.47329563e-01 -6.35577440e-02
-1.53112605e-01 -1.09532952e-01 1.10195374e+00 -6.60267413e-01
-1.15376401e+00 6.16824687e-01 -2.05371559e-01 -1.22462940e+00
6.08491540e-01 -8.95751715e-02 -9.10012484e-01 6.19026348e-02
1.05299950e-02 2.87707388e-01 6.28061175e-01 -5.99550605e-01
-8.00695956e-01 -5.16993999e-01 -5.62479436e-01 -2.41541490e-01
1.42002553e-01 3.82828265e-01 2.65310436e-01 -8.62542391e-01
1.02570169e-01 -9.39471543e-01 -3.24479520e-01 -1.00245178e+00
-4.23871160e-01 -1.96205437e-01 4.77678895e-01 -6.52060866e-01
1.41646147e+00 -1.70524085e+00 -3.86333138e-01 5.14039576e-01
-7.54149184e-02 5.95863070e-03 3.21337283e-01 4.31182176e-01
-6.17517948e-01 -3.41856658e-01 -3.74447107e-01 3.54934931e-01
-6.79005623e-01 -2.87560731e-01 -3.74474317e-01 4.49312538e-01
-4.92514744e-02 5.10695159e-01 -7.53993571e-01 2.00247634e-02
3.22882980e-01 6.29013479e-01 -2.05612481e-01 3.19923460e-01
4.85353321e-01 4.48897988e-01 -1.72204152e-01 7.01321244e-01
2.99704224e-01 4.33401251e-03 3.68252918e-02 3.16749573e-01
-2.24670485e-01 2.79313982e-01 -9.23946083e-01 9.94890571e-01
-3.04600060e-01 8.20714116e-01 -9.06697989e-01 -1.00648320e+00
1.15916383e+00 6.91598535e-01 6.74951792e-01 -4.03365105e-01
1.23579144e-01 2.34410211e-01 3.68209243e-01 -1.84198007e-01
-4.10693645e-01 -8.01971629e-02 3.31598520e-01 3.17458957e-01
-3.99855301e-02 5.10344617e-02 -3.89675610e-03 -2.83618540e-01
1.88568246e+00 -4.36047077e-01 1.01494539e+00 -8.33347142e-01
2.32608259e-01 -2.63157159e-01 5.89993238e-01 5.85329175e-01
-9.95011479e-02 2.28429839e-01 4.29068387e-01 -5.80738485e-01
-3.21327895e-01 -9.88701463e-01 -9.15261984e-01 3.56531829e-01
-2.34467268e-01 -5.79236448e-01 -9.49548185e-01 -4.62357700e-01
-3.84221643e-01 8.49485755e-01 -6.34627759e-01 -1.42464101e-01
-1.17259480e-01 -1.61848605e+00 3.42145860e-01 4.11139905e-01
2.52268970e-01 -1.31324041e+00 -1.36639929e+00 6.04571819e-01
-4.03467007e-02 -9.39630866e-01 2.04905406e-01 7.45190740e-01
-8.00484776e-01 -1.26213503e+00 -6.78357244e-01 -4.99587566e-01
5.58702767e-01 -6.48830116e-01 1.12094963e+00 -1.43679857e-01
-5.62301159e-01 6.68890029e-03 -5.87749898e-01 -8.99777055e-01
-1.78247839e-01 -1.84146464e-01 3.19750279e-01 -3.02158687e-02
8.50591004e-01 -8.86624873e-01 -7.83664584e-01 3.78688574e-01
-5.48011363e-01 -5.24895117e-02 6.25025928e-01 6.56372964e-01
7.26980448e-01 1.95044413e-01 1.00695288e+00 -5.60938478e-01
6.31942868e-01 -7.25181878e-01 -8.81800950e-01 1.23434700e-01
-8.41380298e-01 -2.54227877e-01 2.07366750e-01 -6.92830622e-01
-2.54716188e-01 4.75254536e-01 -4.13298374e-03 4.62606251e-02
-3.13865304e-01 3.22804213e-01 1.90266296e-01 -3.10810417e-01
5.91759622e-01 3.97188276e-01 -7.23260641e-01 -1.27030075e-01
-7.00393558e-01 9.00773287e-01 3.48572671e-01 2.16058344e-01
2.51247257e-01 1.39063582e-01 5.05626388e-02 -7.84811616e-01
-2.69751132e-01 -5.44995785e-01 -4.43609625e-01 -1.53951690e-01
4.96477872e-01 -1.00835121e+00 -5.29201150e-01 6.07971370e-01
-8.47055078e-01 -3.38823557e-01 6.98793232e-02 8.98517907e-01
-6.96066737e-01 -1.79952785e-01 -2.00209454e-01 -9.02931213e-01
-6.41634643e-01 -1.14446783e+00 6.85497701e-01 -1.56430393e-01
-5.71755588e-01 -7.30089426e-01 1.58581212e-01 -3.77889931e-01
2.77578592e-01 6.68200850e-01 4.84768689e-01 -1.30082512e+00
-1.71337545e-01 -4.59078580e-01 1.32438943e-01 -1.12112961e-03
3.44828933e-01 -4.43300396e-01 -9.89299178e-01 -3.87977600e-01
2.64376879e-01 2.45018885e-01 6.31860018e-01 6.87239468e-01
1.33776283e+00 -2.95784593e-01 -7.90831625e-01 4.22065347e-01
1.48597848e+00 1.06462622e+00 7.87618101e-01 6.09646440e-01
-3.62880379e-01 1.72472626e-01 4.96897280e-01 9.65185106e-01
-1.34676695e-01 5.13672769e-01 4.12844002e-01 2.36740008e-01
4.63089973e-01 4.13891435e-01 5.19766705e-03 4.93657291e-01
-1.70513213e-01 -1.47034019e-01 -1.50368190e+00 9.11770523e-01
-1.41987371e+00 -6.01613045e-01 1.47238076e-01 2.54290152e+00
8.67904663e-01 3.90412360e-01 1.03192478e-01 7.38368332e-01
5.26615024e-01 -5.83993196e-01 -2.89508283e-01 -2.29572937e-01
-3.24690081e-02 6.80993378e-01 5.02123117e-01 2.03782246e-01
-9.32201684e-01 5.30372322e-01 6.45064831e+00 5.07758915e-01
-1.27368712e+00 1.47522073e-02 8.23428988e-01 -6.28002733e-02
6.54338419e-01 -1.60464123e-01 -6.13417685e-01 8.83429289e-01
1.50431418e+00 -4.79069382e-01 4.06478494e-01 7.43807971e-01
1.44684285e-01 -5.09890914e-01 -1.16180015e+00 1.22201693e+00
4.42347676e-02 -1.29270327e+00 -2.24966496e-01 2.34855458e-01
6.23760760e-01 4.57884461e-01 -4.88735944e-01 -2.88298726e-03
-2.17779577e-02 -1.27040863e+00 3.66539150e-01 6.44930124e-01
8.76990974e-01 -1.07113624e+00 1.21728027e+00 5.04043579e-01
-9.39753532e-01 -9.51488540e-02 5.75821698e-02 -3.77306014e-01
3.08287479e-02 9.37349439e-01 -1.37141895e+00 2.53850609e-01
1.06475890e+00 6.02976322e-01 -6.61104858e-01 1.75368929e+00
-2.18376011e-01 8.47212195e-01 -4.90798503e-01 -6.30482733e-02
-4.08685692e-02 3.50298554e-01 6.42622352e-01 1.32516658e+00
6.10541642e-01 4.28326547e-01 -2.35164031e-01 8.67195278e-02
4.22744453e-01 7.63384998e-02 -4.26879674e-01 3.45689446e-01
6.42150044e-01 8.86979938e-01 -8.91804338e-01 -2.33464211e-01
-1.36439815e-01 5.97943366e-01 -1.99059248e-01 3.09415478e-02
-4.99342352e-01 -5.76518118e-01 8.48917216e-02 2.68557876e-01
1.36623248e-01 4.61651862e-01 -4.24072474e-01 -1.10386074e+00
2.21611578e-02 -6.81040287e-01 2.17262417e-01 -6.30833805e-01
-9.12657142e-01 1.21975350e+00 4.46293922e-03 -1.52457941e+00
-7.47508585e-01 -3.49040747e-01 -8.82417560e-01 7.26962745e-01
-1.10105717e+00 -4.47290570e-01 -5.36837578e-02 7.38481164e-01
4.22209322e-01 -4.54251319e-01 1.26350105e+00 -1.41843498e-01
-9.92248878e-02 4.69644696e-01 -7.98161477e-02 4.50713821e-02
4.14281696e-01 -1.12055719e+00 1.62838623e-01 7.42314756e-01
2.67104488e-02 1.94588915e-01 9.98183787e-01 -5.75106680e-01
-5.82093835e-01 -1.26165259e+00 1.20624530e+00 -2.10192442e-01
9.04459059e-01 -3.78340017e-03 -7.21876264e-01 7.03633606e-01
1.50996864e-01 -1.24736272e-01 9.36013222e-01 -4.53231446e-02
3.45191211e-01 5.53651452e-02 -1.33748162e+00 2.10106015e-01
4.19796437e-01 -2.74256896e-02 -9.55265164e-01 4.33714151e-01
-1.12887911e-01 -2.18544453e-01 -1.17812073e+00 9.97515976e-01
5.53986192e-01 -1.08936572e+00 5.21739185e-01 -6.47521541e-02
-1.23743437e-01 1.15229182e-01 6.48695678e-02 -1.61326349e+00
6.60653487e-02 -8.88109446e-01 -4.34071124e-02 4.38029855e-01
4.98157352e-01 -8.92107248e-01 5.84697127e-01 2.19090149e-01
1.36983156e-01 -1.41062927e+00 -1.26781523e+00 -8.02680850e-01
-8.28477889e-02 -7.84483254e-01 6.36767924e-01 7.46186495e-01
6.53462768e-01 5.01590334e-02 -9.98755693e-02 3.02882761e-01
4.43247855e-01 -2.88563501e-02 -1.01911873e-02 -1.51920259e+00
-6.81983158e-02 -1.24127597e-01 -1.04388452e+00 7.46689215e-02
-1.92477614e-01 -6.32175267e-01 -2.53121436e-01 -1.16541076e+00
3.10938954e-01 -9.16580036e-02 -8.65505517e-01 7.68653691e-01
2.20037222e-01 4.04049456e-01 -3.43094945e-01 7.79306516e-02
-2.70523340e-01 -1.91385865e-01 2.78000504e-01 1.71271548e-01
-5.43144882e-01 5.41328073e-01 -3.12392525e-02 9.40203965e-01
1.30455887e+00 -7.96240509e-01 -1.82269782e-01 2.02156991e-01
-1.02109484e-01 4.68228281e-01 1.15705036e-01 -1.45398772e+00
1.63933933e-01 1.94127485e-01 7.18165457e-01 -7.98250258e-01
1.44979298e-01 -6.37538493e-01 4.75287229e-01 1.10221720e+00
-1.73271634e-02 2.02731386e-01 3.63294393e-01 3.22477490e-01
-2.17254594e-01 1.13389410e-01 6.98442817e-01 1.62896588e-01
-4.10285115e-01 2.18320161e-01 -7.87374139e-01 -3.34281147e-01
1.47603691e+00 -2.89713562e-01 3.06101590e-01 -3.04492712e-02
-1.00403690e+00 -4.86786477e-02 7.60713369e-02 4.08139855e-01
6.62867904e-01 -7.11568177e-01 -8.07368398e-01 4.38654959e-01
4.68714356e-01 -7.99804032e-01 -2.84349054e-01 1.06614053e+00
-2.83228308e-01 7.38332570e-01 -5.36485553e-01 -5.94147980e-01
-1.48880363e+00 9.78361368e-02 5.18899381e-01 -2.97079682e-01
-7.38908648e-01 7.52671242e-01 -6.35997504e-02 4.56978917e-01
3.24857682e-01 -2.89533317e-01 -2.79125810e-01 -2.13526338e-01
9.06762064e-01 3.30293953e-01 6.75349772e-01 -4.02341425e-01
-7.93546736e-01 1.48063064e-01 6.96031749e-02 -1.06275916e-01
1.42584479e+00 5.93320191e-01 -9.48797837e-02 3.51883501e-01
6.62242889e-01 -2.95499027e-01 -7.82060862e-01 3.61257076e-01
4.35884148e-01 -7.42867067e-02 2.51634955e-01 -1.53151941e+00
-7.93411374e-01 5.58790445e-01 1.19149268e+00 2.80689299e-01
1.58215046e+00 6.75815484e-03 2.95179516e-01 3.98350626e-01
9.21602607e-01 -5.64829946e-01 -7.11614370e-01 1.72066435e-01
8.01900387e-01 -8.90159130e-01 -6.44793063e-02 -1.76710159e-01
-5.15294015e-01 1.02688515e+00 8.08289926e-03 -3.62305284e-01
1.16078067e+00 8.03347945e-01 -1.52252093e-01 2.24635694e-02
-1.18633759e+00 1.89611539e-01 2.11823046e-01 6.61177218e-01
4.19890076e-01 6.40470147e-01 -8.03016245e-01 1.00434542e+00
-5.66494286e-01 5.65996945e-01 5.84343851e-01 9.54349220e-01
-3.37734967e-01 -8.54982615e-01 -8.40035677e-02 1.00820112e+00
-9.53594625e-01 -4.46847916e-01 -3.13593656e-01 8.36985290e-01
1.32860690e-01 1.14497995e+00 1.94773212e-01 -5.52142501e-01
2.19623838e-02 1.74635857e-01 3.52403313e-01 -5.18699646e-01
-7.21257210e-01 2.74466574e-01 -1.22233503e-01 -6.72447681e-01
-4.15761411e-01 -8.07323217e-01 -1.16067386e+00 4.30523217e-01
-4.44962442e-01 5.79714179e-01 6.59044147e-01 1.02537894e+00
2.82398373e-01 4.77462322e-01 6.71174049e-01 -4.07622665e-01
4.82037552e-02 -1.31971312e+00 -8.67984653e-01 -1.67750344e-01
3.44311506e-01 -6.55489922e-01 -6.09082520e-01 2.14724958e-01] | [13.23590087890625, 3.527452230453491] |
c7e5a8f1-8f65-4ac5-a4cf-199500e781d9 | selc-self-ensemble-label-correction-improves | 2205.01156 | null | https://arxiv.org/abs/2205.01156v1 | https://arxiv.org/pdf/2205.01156v1.pdf | SELC: Self-Ensemble Label Correction Improves Learning with Noisy Labels | Deep neural networks are prone to overfitting noisy labels, resulting in poor generalization performance. To overcome this problem, we present a simple and effective method self-ensemble label correction (SELC) to progressively correct noisy labels and refine the model. We look deeper into the memorization behavior in training with noisy labels and observe that the network outputs are reliable in the early stage. To retain this reliable knowledge, SELC uses ensemble predictions formed by an exponential moving average of network outputs to update the original noisy labels. We show that training with SELC refines the model by gradually reducing supervision from noisy labels and increasing supervision from ensemble predictions. Despite its simplicity, compared with many state-of-the-art methods, SELC obtains more promising and stable results in the presence of class-conditional, instance-dependent, and real-world label noise. The code is available at https://github.com/MacLLL/SELC. | ['Wenbo He', 'Yangdi Lu'] | 2022-05-02 | null | null | null | null | ['learning-with-noisy-labels', 'learning-with-noisy-labels'] | ['computer-vision', 'natural-language-processing'] | [ 3.70419681e-01 4.33660159e-03 1.69279814e-01 -7.41611600e-01
-7.90656626e-01 -4.77475882e-01 5.14549434e-01 4.43773896e-01
-6.69574142e-01 1.15602386e+00 -3.68269160e-02 -1.37410536e-01
5.14541306e-02 -6.27197921e-01 -6.56544089e-01 -7.79373884e-01
1.73864588e-01 3.10340077e-01 7.49664083e-02 -1.54792368e-02
1.29072458e-01 8.37346911e-02 -1.82352710e+00 4.57243055e-01
9.77721274e-01 8.71927679e-01 -1.72163576e-01 6.06289387e-01
5.44368774e-02 9.23115611e-01 -6.32584870e-01 -4.30593371e-01
-2.62482055e-02 -6.24306381e-01 -9.29716051e-01 -1.67028397e-01
3.00268412e-01 7.02423006e-02 9.33275670e-02 1.17348063e+00
5.69298148e-01 4.10611629e-01 5.58713436e-01 -9.83339906e-01
-6.20340228e-01 6.85379565e-01 -1.57258883e-01 3.44115011e-02
-1.03270188e-01 -1.30266538e-02 7.38068044e-01 -1.02546346e+00
4.47583914e-01 9.54925358e-01 1.13222194e+00 9.44723487e-01
-1.62925172e+00 -8.61029267e-01 3.68502200e-01 1.09788172e-01
-1.29117727e+00 -4.91393030e-01 5.61666906e-01 -2.83956110e-01
7.78518617e-01 2.38258362e-01 1.87242582e-01 1.29574323e+00
1.04043871e-01 6.03754103e-01 1.51043165e+00 -6.72250390e-01
4.56256121e-01 3.47035736e-01 7.06726491e-01 5.15296280e-01
1.25059128e-01 2.61869252e-01 -5.11335433e-01 -2.06955999e-01
5.95201924e-02 5.07610999e-02 -2.77399004e-01 2.39013046e-01
-8.19984734e-01 5.61978579e-01 4.86385792e-01 4.04446453e-01
-3.31528217e-01 2.46847600e-01 3.86478335e-01 4.85736072e-01
9.72693503e-01 5.66631734e-01 -7.70859480e-01 -1.52182028e-01
-9.84162033e-01 -7.99364783e-03 6.55106723e-01 5.22323191e-01
8.84464383e-01 8.46529379e-02 -7.78800771e-02 1.08021128e+00
-1.01601174e-02 3.32902104e-01 6.24420702e-01 -1.25708950e+00
-3.09221037e-02 3.21036071e-01 1.04842857e-01 -5.77234387e-01
-5.36645532e-01 -9.64906514e-01 -1.07066214e+00 2.89148629e-01
3.31124932e-01 -1.89644843e-01 -1.21358442e+00 1.93565047e+00
1.06955156e-01 3.84764135e-01 -5.84177412e-02 4.60072011e-01
7.24930704e-01 5.09950459e-01 5.24371326e-01 -2.92055249e-01
8.35763872e-01 -9.32125926e-01 -7.35847592e-01 -1.22712113e-01
9.71753478e-01 -3.67466182e-01 7.17084169e-01 4.22637373e-01
-8.29450667e-01 -7.65927315e-01 -8.59502673e-01 1.66575253e-01
-5.49920678e-01 1.48366811e-02 2.58861154e-01 6.14993751e-01
-1.29927826e+00 1.21629536e+00 -8.70441318e-01 -4.82533202e-02
5.29157341e-01 2.37952679e-01 -3.13086867e-01 -1.60738528e-01
-1.23143792e+00 1.12211990e+00 6.01621032e-01 6.99150488e-02
-6.98101282e-01 -5.74496150e-01 -8.15213144e-01 -6.67172894e-02
2.24122405e-01 -2.53712445e-01 1.53783178e+00 -1.15673602e+00
-1.34419906e+00 6.67175472e-01 -5.02287805e-01 -3.89683515e-01
4.12107706e-01 -2.46996731e-01 -3.71409982e-01 -5.98286033e-01
-8.81696120e-02 8.13799262e-01 4.23800230e-01 -1.55368519e+00
-6.66981101e-01 -3.47464383e-01 -3.95351261e-01 -4.98279408e-02
-2.26076603e-01 -2.31145218e-01 1.08732626e-01 -5.44512808e-01
2.56137311e-01 -9.87608492e-01 -2.66690463e-01 -5.26325703e-01
-2.01991498e-01 -6.32748961e-01 4.58458781e-01 -5.18931627e-01
1.33763444e+00 -2.00605822e+00 -2.22885877e-01 2.29156256e-01
2.02591240e-01 5.69350243e-01 -3.29003870e-01 7.85888731e-02
-3.59824270e-01 3.65871131e-01 -4.38544363e-01 -9.58821177e-01
-2.03764677e-01 4.30557489e-01 -4.74637225e-02 2.11923867e-01
2.58614182e-01 8.58275235e-01 -1.12500191e+00 -1.45502865e-01
-9.36606824e-02 4.49550956e-01 -8.26486647e-02 -1.17715508e-01
-1.21702373e-01 7.00585306e-01 2.75965873e-02 5.13398707e-01
6.96993351e-01 -5.70843637e-01 2.41406143e-01 2.43554071e-01
2.00135931e-01 4.68283057e-01 -1.02885473e+00 1.33657217e+00
-4.43298608e-01 5.71926117e-01 -2.91730851e-01 -1.00749052e+00
1.01973820e+00 4.50282663e-01 7.14552030e-02 -5.69517076e-01
3.60840172e-01 4.84584749e-01 -2.72899300e-01 -3.61977927e-02
3.98219854e-01 -2.80797333e-01 1.79118752e-01 6.66610539e-01
3.93983960e-01 2.64474422e-01 1.36320829e-01 6.53118342e-02
1.00364745e+00 8.00075307e-02 1.83449745e-01 -6.11397587e-02
4.07874584e-01 -3.02905023e-01 7.87090957e-01 1.09523332e+00
-2.66006291e-01 5.79105258e-01 9.97471716e-03 -4.54382479e-01
-7.62273788e-01 -7.22877085e-01 -3.05648088e-01 1.34600508e+00
-1.38868198e-01 -4.56120163e-01 -7.52677977e-01 -9.03697193e-01
-7.48284459e-02 1.09632170e+00 -7.99654782e-01 -3.14591229e-01
-4.05654907e-01 -8.07542562e-01 3.83524567e-01 7.22253680e-01
5.36817074e-01 -1.19262898e+00 -2.49492377e-02 3.53330374e-01
-3.44149023e-01 -6.59287751e-01 -1.00414194e-01 7.25308776e-01
-1.00829637e+00 -7.85855651e-01 -4.59285438e-01 -6.07744277e-01
8.70058537e-01 -4.61872332e-02 1.36399758e+00 6.05857074e-01
2.06088766e-01 1.26778573e-01 -4.70307410e-01 -5.60374141e-01
-8.68370593e-01 2.15142950e-01 1.40296131e-01 -1.43649891e-01
5.66278696e-01 -5.82911134e-01 -2.79056042e-01 1.98417544e-01
-7.30406582e-01 8.72541666e-02 5.90757616e-02 1.09041381e+00
5.82094550e-01 2.55273819e-01 8.29368770e-01 -1.34414685e+00
6.59037471e-01 -5.53143501e-01 -4.30191189e-01 3.11233848e-01
-1.13674653e+00 2.40066364e-01 6.61622763e-01 -3.96603286e-01
-1.15959966e+00 9.20782238e-02 -3.05801243e-01 -1.85050722e-02
-4.95493084e-01 4.96343970e-01 4.65191066e-01 1.38402462e-01
1.02764893e+00 8.05469528e-02 -1.89569265e-01 -7.11087644e-01
1.67638406e-01 6.75312340e-01 5.01861751e-01 -5.96875548e-01
2.71418124e-01 -9.98268556e-03 -2.07336783e-01 6.00734018e-02
-1.44740808e+00 -2.36583397e-01 -6.31424606e-01 -4.93035495e-01
3.80731165e-01 -8.10442686e-01 -4.49241728e-01 8.46118033e-01
-1.18321931e+00 -7.14744925e-01 -4.30757910e-01 2.68309355e-01
-1.66338190e-01 -5.68788610e-02 -9.43355799e-01 -9.79173779e-01
-3.27769488e-01 -1.03070617e+00 7.98281014e-01 3.62261325e-01
-4.72434491e-01 -1.10421526e+00 1.43435240e-01 1.22105643e-01
5.26685774e-01 1.68893382e-01 6.50660753e-01 -9.37458158e-01
-1.51630715e-01 -4.03873354e-01 2.12084148e-02 9.80289757e-01
2.75031142e-02 -1.96230799e-01 -1.31906819e+00 -2.71264315e-01
-8.64130557e-02 -5.52820802e-01 1.35384166e+00 1.78000927e-01
1.21372938e+00 7.22782360e-03 -2.24791557e-01 1.66468769e-01
1.26486504e+00 4.88782600e-02 4.15515959e-01 3.00062150e-01
3.72326344e-01 5.26907444e-01 2.63349533e-01 2.56090879e-01
3.37912261e-01 2.38519639e-01 1.25145659e-01 1.37868464e-01
-1.49247795e-01 -1.82042450e-01 2.11581469e-01 1.04149616e+00
-2.81197160e-01 -2.07621396e-01 -1.03953767e+00 3.41084152e-01
-1.95671630e+00 -7.77943850e-01 -3.39930564e-01 2.13788152e+00
1.31265271e+00 7.89320692e-02 -2.26906836e-01 4.20811862e-01
7.97724724e-01 -2.29897335e-01 -5.73327124e-01 -2.71985292e-01
-2.11837053e-01 4.35449898e-01 4.30747271e-01 6.38343513e-01
-1.24909496e+00 7.48787522e-01 6.85328484e+00 9.55969453e-01
-9.88434315e-01 5.60834169e-01 1.05136204e+00 -6.17741123e-02
-2.45914340e-01 -2.00082153e-01 -8.48435223e-01 6.98898733e-01
1.30173635e+00 2.71699309e-01 2.95072168e-01 7.35734701e-01
-1.56727329e-01 -3.85876745e-01 -9.73594844e-01 6.19211733e-01
-8.33704174e-02 -1.21934092e+00 -4.62510705e-01 -2.66102463e-01
1.26608658e+00 2.79903620e-01 -1.18110338e-02 6.47645235e-01
9.17011559e-01 -1.00119889e+00 6.27477944e-01 7.64916241e-01
6.23556972e-01 -6.38676941e-01 1.25983381e+00 6.69902742e-01
-5.72716296e-01 -1.69733077e-01 -3.04756671e-01 -2.92614460e-01
-6.40999228e-02 1.05779040e+00 -4.48894471e-01 3.19732517e-01
7.41907299e-01 8.11141551e-01 -9.00002599e-01 7.99717665e-01
-5.16577303e-01 1.09665287e+00 -3.57608765e-01 7.31341988e-02
-3.24421190e-02 8.35365728e-02 4.20298949e-02 1.18057632e+00
3.32542062e-01 2.14288235e-01 3.41878682e-02 6.84124649e-01
-3.61697644e-01 -1.49391294e-01 -2.47208431e-01 4.47342396e-01
6.75530970e-01 1.08497119e+00 -7.55845487e-01 -5.92514694e-01
-5.12300022e-02 8.93758953e-01 7.17191398e-01 4.81993288e-01
-6.18252397e-01 8.54922459e-03 9.82143432e-02 -1.54723391e-01
-2.13537421e-02 1.68777518e-02 -7.84179986e-01 -9.11499023e-01
-3.93035077e-02 -7.24040210e-01 3.60038668e-01 -7.49477148e-01
-1.35614789e+00 7.87993729e-01 -2.67621577e-01 -9.00979698e-01
-1.69182897e-01 -4.27240849e-01 -5.31105399e-01 8.86460066e-01
-1.41187239e+00 -5.86683929e-01 -3.95024508e-01 1.77613229e-01
3.77538651e-01 -4.04278934e-02 1.14190865e+00 1.53326631e-01
-6.49701774e-01 7.53656268e-01 5.80276191e-01 -2.99096629e-02
9.28708911e-01 -1.31010759e+00 2.82871157e-01 6.44424379e-01
3.82496789e-02 4.02287602e-01 6.33819878e-01 -6.42157376e-01
-7.22528845e-02 -1.38734138e+00 1.28842497e+00 -7.85855472e-01
3.60965401e-01 -1.62533715e-01 -1.36590421e+00 6.37065351e-01
8.81191194e-02 1.56263262e-01 7.98563898e-01 4.15981680e-01
-5.56675076e-01 -1.04610115e-01 -1.06549776e+00 2.63301432e-01
9.99620736e-01 -3.66183311e-01 -3.15723896e-01 3.04151148e-01
5.19087970e-01 -2.94321656e-01 -6.97707713e-01 6.34570241e-01
3.07896376e-01 -9.53538358e-01 3.89678866e-01 -4.79744315e-01
2.78959990e-01 -1.56530246e-01 -9.17030871e-03 -1.74464643e+00
-4.74425793e-01 -1.49847299e-01 3.57292108e-02 1.24606621e+00
8.36533129e-01 -8.11571836e-01 7.57113993e-01 8.44965160e-01
-1.54827058e-01 -8.18373144e-01 -8.70059490e-01 -7.37487495e-01
2.56043196e-01 -6.04513943e-01 4.31864291e-01 1.09619808e+00
-1.27107367e-01 2.25500301e-01 -4.51187700e-01 -1.59956262e-01
5.03948808e-01 -3.33743423e-01 2.07816765e-01 -1.58747542e+00
7.15433955e-02 -2.23690331e-01 -7.17866495e-02 -5.96005559e-01
5.00648141e-01 -1.10035121e+00 5.21523654e-01 -1.27439427e+00
1.58146217e-01 -6.78019762e-01 -9.36344624e-01 9.65632617e-01
-5.99421382e-01 6.02143109e-01 2.10492313e-01 2.43845731e-01
-1.03029251e+00 4.31262821e-01 8.89965177e-01 4.79760580e-03
-8.01414326e-02 8.42528939e-02 -6.75905526e-01 6.29450202e-01
1.29554474e+00 -9.79961395e-01 -1.15229957e-01 -2.89516896e-01
2.58614928e-01 -4.39502031e-01 2.49184430e-01 -1.01994073e+00
3.07164192e-01 1.26431823e-01 5.07762134e-01 -4.24091280e-01
1.39344260e-01 -5.97104013e-01 3.07463646e-01 3.62625986e-01
-9.03181076e-01 -1.19624496e-01 1.21171921e-01 5.54162562e-01
-1.79339632e-01 -6.47684932e-01 1.03915370e+00 -1.38685107e-01
-5.00639200e-01 -1.38800859e-01 -6.67674482e-01 -1.23436302e-01
5.33972204e-01 9.95587278e-03 -4.16084260e-01 -4.21055913e-01
-1.18134904e+00 3.60497475e-01 3.46673965e-01 2.22643182e-01
2.99543291e-01 -1.39486897e+00 -8.23985279e-01 1.97693616e-01
-9.48772021e-03 5.69173768e-02 2.56048322e-01 7.94142783e-01
2.54892409e-02 1.76312834e-01 2.69488573e-01 -5.18043339e-01
-1.23721051e+00 1.81022286e-01 5.69055796e-01 -4.68960434e-01
-1.49183333e-01 1.12728250e+00 -3.19746137e-01 -8.11051130e-01
3.71057063e-01 1.70748383e-02 -8.67457502e-03 -7.69085363e-02
5.77248394e-01 4.81289327e-01 4.41872865e-01 -4.71663743e-01
-1.22217275e-01 2.66780347e-01 -2.38221556e-01 2.03781933e-01
1.25729525e+00 -1.55738652e-01 -1.55920297e-01 7.56378412e-01
1.11016512e+00 -4.88496661e-01 -1.21384311e+00 -6.73698545e-01
2.61149913e-01 3.68178561e-02 1.56845167e-01 -1.23763299e+00
-9.93966222e-01 7.11986244e-01 7.86250234e-01 1.83223605e-01
1.13888550e+00 -1.52612671e-01 5.41525543e-01 4.63203549e-01
3.35280120e-01 -1.37236547e+00 -4.91628982e-02 9.39149618e-01
5.85663974e-01 -1.47325790e+00 -1.06425487e-01 -8.90340433e-02
-5.46789765e-01 8.78086150e-01 6.98241889e-01 -4.26235199e-02
9.56883907e-01 1.33756593e-01 3.47517461e-01 1.35356769e-01
-1.01874447e+00 -1.22639269e-01 4.61161621e-02 5.37370145e-01
5.33813119e-01 1.54659510e-01 -2.59434521e-01 7.15656519e-01
2.65361015e-02 1.33169606e-01 3.31574231e-01 8.13874662e-01
-4.84006017e-01 -1.13879526e+00 -3.58483106e-01 5.94407320e-01
-4.51891989e-01 -2.21165210e-01 -2.07012981e-01 3.67281079e-01
4.95743901e-01 1.15616333e+00 1.14744492e-01 -5.27818084e-01
2.11973116e-01 8.03498924e-01 1.95894882e-01 -6.23342037e-01
-6.71500742e-01 -1.48607627e-01 1.07102662e-01 -3.38646144e-01
-7.09405899e-01 -5.80340385e-01 -1.12973273e+00 -4.34071630e-01
-6.88509703e-01 2.95473218e-01 5.30813158e-01 9.14322674e-01
5.07641554e-01 5.68716764e-01 5.31475782e-01 -8.45728278e-01
-6.49444461e-01 -1.38323295e+00 -5.30069053e-01 6.46625757e-01
3.50734502e-01 -7.39982069e-01 -6.46776438e-01 8.58046561e-02] | [9.35177230834961, 3.8557381629943848] |
18e0f256-85a2-43c0-b36b-7ce657a00d78 | 2-speed-network-ensemble-for-efficient | 2203.08267 | null | https://arxiv.org/abs/2203.08267v1 | https://arxiv.org/pdf/2203.08267v1.pdf | 2-speed network ensemble for efficient classification of incremental land-use/land-cover satellite image chips | The ever-growing volume of satellite imagery data presents a challenge for industry and governments making data-driven decisions based on the timely analysis of very large data sets. Commonly used deep learning algorithms for automatic classification of satellite images are time and resource-intensive to train. The cost of retraining in the context of Big Data presents a practical challenge when new image data and/or classes are added to a training corpus. Recognizing the need for an adaptable, accurate, and scalable satellite image chip classification scheme, in this research we present an ensemble of: i) a slow to train but high accuracy vision transformer; and ii) a fast to train, low-parameter convolutional neural network. The vision transformer model provides a scalable and accurate foundation model. The high-speed CNN provides an efficient means of incorporating newly labelled data into analysis, at the expense of lower accuracy. To simulate incremental data, the very large (~400,000 images) So2Sat LCZ42 satellite image chip dataset is divided into four intervals, with the high-speed CNN retrained every interval and the vision transformer trained every half interval. This experimental setup mimics an increase in data volume and diversity over time. For the task of automated land-cover/land-use classification, the ensemble models for each data increment outperform each of the component models, with best accuracy of 65% against a holdout test partition of the So2Sat dataset. The proposed ensemble and staggered training schedule provide a scalable and cost-effective satellite image classification scheme that is optimized to process very large volumes of satellite data. | ['Sanjoy Paul', 'Nagesh Shukla', 'Biswajeet Pradhan', 'Subrata Chakraborty', 'Michael James Horry'] | 2022-03-15 | null | null | null | null | ['satellite-image-classification'] | ['computer-vision'] | [ 1.42668813e-01 -4.30211991e-01 6.77987039e-02 -5.12987852e-01
-5.24886250e-01 -5.19867837e-01 2.93719620e-01 -7.16560185e-02
-7.85770595e-01 7.85745323e-01 -3.45721483e-01 -4.36710119e-01
-1.19618796e-01 -1.07273257e+00 -7.43784666e-01 -9.29305792e-01
-3.92345577e-01 6.67374849e-01 2.41191462e-01 -3.35698575e-01
-1.42746910e-01 8.32144916e-01 -2.08991528e+00 -6.34350106e-02
9.55525577e-01 1.32380211e+00 6.52722299e-01 6.33931518e-01
-6.89587146e-02 5.18064976e-01 -3.53999287e-01 5.73682562e-02
6.80764139e-01 5.37611172e-02 -7.01394558e-01 2.77504176e-01
5.16387045e-01 -5.56200504e-01 -1.73952475e-01 9.39286888e-01
6.11079097e-01 -1.78768430e-02 1.24790721e-01 -1.13229990e+00
-1.86895393e-02 5.62025189e-01 -6.68787241e-01 5.08403003e-01
-6.92164481e-01 3.49236995e-01 6.14942253e-01 -6.63984597e-01
3.56022269e-01 7.43343115e-01 7.99939394e-01 7.51782209e-02
-1.19716644e+00 -6.82220042e-01 -8.32699537e-02 2.38769099e-01
-1.64720368e+00 -2.64759153e-01 2.71142274e-01 -4.13830310e-01
1.00976849e+00 2.95839459e-01 7.75537670e-01 5.20495176e-01
2.32192084e-01 3.64404917e-01 1.03465903e+00 -1.47150993e-01
4.97641832e-01 1.37976825e-01 3.84140730e-01 3.56324792e-01
3.81170183e-01 1.59016788e-01 9.63138491e-02 5.17825671e-02
5.86655617e-01 2.63057142e-01 -2.14764878e-01 3.75084803e-02
-7.88497329e-01 7.61323690e-01 8.23280334e-01 5.74693561e-01
-5.94458222e-01 1.01335905e-01 5.50848424e-01 5.39683998e-01
5.02659023e-01 1.63992345e-01 -6.79317772e-01 1.35531157e-01
-1.25420487e+00 1.81077152e-01 3.77665132e-01 6.25379324e-01
1.07127059e+00 4.31169152e-01 2.66418785e-01 7.36608744e-01
-1.58713549e-01 8.30487669e-01 7.18161583e-01 -4.13264751e-01
3.83116364e-01 9.14716065e-01 -9.70521197e-02 -7.88063943e-01
-7.60981679e-01 -9.96264160e-01 -1.45571530e+00 2.89522082e-01
2.07047500e-02 3.89721543e-02 -1.20662570e+00 1.34483886e+00
2.38948062e-01 3.20585780e-02 8.12073797e-02 9.92777348e-01
5.72611272e-01 9.48133767e-01 -2.01911796e-02 2.41567977e-02
1.42218864e+00 -5.60014009e-01 -2.74422377e-01 -4.28336650e-01
6.94306314e-01 -1.75701171e-01 8.71914268e-01 1.88461751e-01
-4.64832395e-01 -9.32289660e-01 -1.19112885e+00 2.12810293e-01
-5.42874575e-01 5.38752437e-01 6.38574421e-01 4.56395864e-01
-1.23702145e+00 5.06950855e-01 -7.79402792e-01 -4.46272463e-01
5.66692114e-01 6.44435823e-01 -4.13491756e-01 -2.05045447e-01
-1.16736019e+00 7.45937765e-01 7.59349763e-01 6.75238252e-01
-7.89533377e-01 -5.88897049e-01 -6.42223656e-01 3.47676337e-01
4.33536805e-02 -2.19084173e-01 1.01519942e+00 -1.68201303e+00
-1.14130831e+00 8.77253413e-01 4.28668827e-01 -8.37723315e-01
3.55381250e-01 1.50375947e-01 -4.07267272e-01 -1.94544896e-01
3.84412073e-02 7.75707424e-01 7.79404581e-01 -8.10556293e-01
-1.05653679e+00 -7.08787680e-01 -2.83926100e-01 8.05406794e-02
-4.28112656e-01 -2.78317869e-01 -2.86015775e-02 -2.70611167e-01
1.10130578e-01 -1.05483139e+00 -3.45724344e-01 -1.98275736e-03
2.74114460e-01 1.34267554e-01 1.00532210e+00 -5.94236016e-01
9.18696165e-01 -2.19564486e+00 -1.57620952e-01 1.28462151e-01
6.15170114e-02 5.53252101e-01 -2.78479308e-01 7.02975690e-02
-2.03200132e-01 5.84082119e-02 -3.34575087e-01 1.07632525e-01
-4.14442867e-01 3.85501474e-01 -3.26448202e-01 3.26821178e-01
3.99839342e-01 6.58307552e-01 -5.69719911e-01 -2.59121150e-01
1.42613053e-01 2.49002203e-01 -1.02697030e-01 1.41328678e-01
-1.83506936e-01 7.14920461e-02 -2.82397211e-01 6.36046112e-01
1.03885031e+00 -3.64402711e-01 1.85028479e-01 -3.20595831e-01
-4.93292093e-01 -3.34125519e-01 -1.12532830e+00 1.31584597e+00
-3.17721158e-01 9.47188437e-01 2.22678825e-01 -1.28900397e+00
1.15100968e+00 5.53382374e-02 2.96972007e-01 -9.55039442e-01
2.21492633e-01 4.08149660e-01 4.31457162e-02 -4.03695226e-01
7.32500255e-01 -3.71445388e-01 -1.33752242e-01 2.13085711e-01
1.69742748e-01 -1.72707706e-03 2.32381299e-01 -2.27502331e-01
8.47222269e-01 -1.92154780e-01 1.77834094e-01 -5.60521245e-01
4.42676634e-01 4.93826002e-01 5.53805768e-01 5.33374190e-01
-1.35985628e-01 1.58526853e-01 -1.19297765e-02 -1.25949180e+00
-1.29992080e+00 -4.13146883e-01 -4.12973672e-01 8.91756296e-01
-1.76525652e-01 2.37095177e-01 -4.22487378e-01 -3.00785363e-01
5.81989288e-02 2.32525244e-01 -5.51089704e-01 1.93076387e-01
-3.40978086e-01 -1.27087188e+00 5.46280801e-01 3.84915620e-01
1.34781468e+00 -7.31190085e-01 -8.22564423e-01 3.25012237e-01
-8.71477127e-02 -9.24180686e-01 2.41859034e-01 4.65870172e-01
-1.15397358e+00 -7.39885449e-01 -5.56423366e-01 -8.76947522e-01
6.19908929e-01 3.22009921e-01 1.05665326e+00 1.71265945e-01
-3.26956570e-01 -1.49025351e-01 -4.04225051e-01 -3.40587050e-01
-2.33816728e-01 4.97625172e-01 -1.03838198e-01 1.10314570e-01
4.42591906e-01 -5.95616579e-01 -5.48708260e-01 2.91371733e-01
-1.18472362e+00 1.51694849e-01 7.91270256e-01 1.07205570e+00
5.52556396e-01 4.60898310e-01 3.33257973e-01 -4.03440207e-01
3.39807943e-02 -5.23251235e-01 -1.11595547e+00 1.20832905e-01
-5.66975415e-01 1.85155302e-01 8.27625573e-01 -1.16143450e-01
-7.37384379e-01 5.11117935e-01 -7.53461793e-02 -2.32364565e-01
-7.91700929e-02 8.79070103e-01 1.15044557e-01 -2.63216466e-01
8.18094075e-01 5.62707961e-01 1.71742424e-01 -4.50727105e-01
-1.21561036e-01 1.16817963e+00 4.26174313e-01 -3.92423756e-02
7.24833429e-01 3.35361809e-01 -1.44554481e-01 -1.03961635e+00
-2.75283486e-01 -3.95711750e-01 -7.42225051e-01 -3.64218980e-01
4.38216448e-01 -1.30038738e+00 -2.67700970e-01 1.01427233e+00
-6.96991265e-01 -5.19140780e-01 -1.56331584e-01 2.51092076e-01
3.98130640e-02 1.15029514e-01 -3.33694309e-01 -5.28844178e-01
-7.60487378e-01 -1.03095269e+00 9.49393749e-01 3.65942061e-01
4.26633686e-01 -5.52579165e-01 -6.29545376e-02 2.18472570e-01
7.62615323e-01 2.36018181e-01 5.46036959e-01 -3.94817024e-01
-8.62756550e-01 -5.04899859e-01 -3.80953491e-01 5.55270970e-01
6.12632930e-02 1.32619426e-01 -1.03098214e+00 -5.57433307e-01
-5.79738691e-02 -5.51866949e-01 1.05207849e+00 3.85741889e-01
1.14317346e+00 -1.95013434e-01 -2.54332334e-01 6.78785682e-01
1.91061163e+00 1.50133520e-01 7.53472626e-01 5.94402492e-01
3.64663363e-01 2.50350267e-01 4.56053346e-01 5.04405200e-01
3.78730506e-01 4.18959022e-01 5.82243323e-01 -3.79959881e-01
3.63822997e-01 4.45486665e-01 8.57190788e-02 5.45093119e-01
-2.31692195e-01 -1.73703238e-01 -1.25872731e+00 5.69448471e-01
-1.68223131e+00 -1.10113096e+00 -1.20763980e-01 2.25577235e+00
6.01657927e-01 1.92266610e-02 -1.98131159e-01 3.33416492e-01
5.90001464e-01 1.17493324e-01 -6.11948848e-01 2.61155143e-02
-2.72570968e-01 2.39661500e-01 9.96626139e-01 1.40874386e-01
-1.33659935e+00 7.87794232e-01 5.71640110e+00 7.53629625e-01
-1.88245702e+00 -1.34096164e-02 8.23824227e-01 -1.82842255e-01
1.56396240e-01 -3.24671447e-01 -8.76218677e-01 6.25580788e-01
1.34943557e+00 7.17571154e-02 2.34767392e-01 1.01391351e+00
2.32799858e-01 -4.60651577e-01 -5.39201975e-01 9.55204427e-01
-1.90421969e-01 -1.47973418e+00 -1.68759078e-02 1.38206765e-01
6.44636571e-01 7.51369238e-01 -1.88247755e-01 4.46244091e-01
2.61671036e-01 -7.66269445e-01 6.12115681e-01 3.31018060e-01
9.31381762e-01 -6.26813173e-01 1.24150085e+00 5.19847333e-01
-1.30338705e+00 -5.28815627e-01 -5.46693623e-01 -2.43204489e-01
-3.18328530e-01 6.19590402e-01 -5.25933087e-01 4.83931869e-01
1.14072287e+00 5.10117173e-01 -7.18805909e-01 9.75708127e-01
5.27428687e-01 6.07343733e-01 -6.21971667e-01 1.73770748e-02
5.82674265e-01 -6.28463849e-02 -4.95340722e-03 8.91873598e-01
5.06975234e-01 2.83467442e-01 1.55776322e-01 3.96727949e-01
1.17527358e-01 -2.13093892e-01 -4.63464737e-01 -5.47922403e-02
3.95069242e-01 1.54693162e+00 -9.12647784e-01 -4.80994612e-01
-2.17449784e-01 7.80600250e-01 2.13507429e-01 4.67755534e-02
-5.80217600e-01 -1.45757467e-01 5.69765031e-01 5.75919403e-03
4.66706425e-01 -2.28877306e-01 -2.20249161e-01 -9.88530040e-01
-7.49890506e-02 -9.01361048e-01 3.54663849e-01 -8.44750464e-01
-8.81751001e-01 9.84500527e-01 -1.96708336e-01 -1.59628630e+00
-2.37610102e-01 -8.15102279e-01 -2.47911379e-01 8.64644825e-01
-1.76767135e+00 -1.28653026e+00 -1.05878961e+00 3.53152871e-01
6.67962611e-01 -3.81680518e-01 8.57412636e-01 4.71808791e-01
-6.56809092e-01 2.14491114e-01 6.08782470e-01 2.31509253e-01
1.91408798e-01 -7.44995594e-01 3.09380919e-01 8.38355780e-01
-3.44102025e-01 -7.77736232e-02 5.06082356e-01 -3.84745002e-01
-1.48037672e+00 -1.48056149e+00 5.49558043e-01 1.32580519e-01
4.70071554e-01 -2.51997888e-01 -1.01822567e+00 5.91453910e-01
-1.94733202e-01 2.90274054e-01 6.12644851e-01 -2.44357288e-01
-2.07985379e-02 -9.64787543e-01 -1.17411804e+00 4.41079363e-02
4.85870898e-01 -2.63293207e-01 -1.84855163e-01 1.23344913e-01
2.82650679e-01 -3.15867424e-01 -6.41858041e-01 3.15105677e-01
5.21923006e-01 -8.71312559e-01 4.97957289e-01 -2.09771261e-01
3.79920810e-01 -4.28834260e-01 -2.77219266e-01 -1.27463531e+00
-6.39565945e-01 1.15383185e-01 5.88393748e-01 7.21035063e-01
2.73078114e-01 -6.82113826e-01 7.67280936e-01 6.13463104e-01
-1.10765778e-01 -3.50238979e-01 -1.07498300e+00 -8.13586116e-01
-1.08597569e-01 -1.36998653e-01 7.76466310e-01 9.43083286e-01
-4.83076066e-01 2.68371403e-01 -1.76981300e-01 4.52941120e-01
6.11102045e-01 2.47490704e-01 7.86134481e-01 -1.45738804e+00
-7.78028667e-02 -2.87398934e-01 -8.99359941e-01 -5.78596890e-01
-3.06684971e-01 -6.30554676e-01 6.28052354e-02 -1.22308815e+00
2.57939160e-01 -6.10406339e-01 -1.67164490e-01 7.33858466e-01
4.34777997e-02 3.92377734e-01 -2.88486052e-02 4.22896534e-01
-7.73742869e-02 5.06880343e-01 6.20746136e-01 -4.69808012e-01
-7.86736161e-02 4.89310594e-03 -2.62036741e-01 1.93963319e-01
8.34174633e-01 -3.83513212e-01 -2.89472938e-01 -6.30638897e-01
2.25511551e-01 -1.16914600e-01 4.80533302e-01 -1.49906254e+00
2.21452534e-01 1.14208281e-01 5.04604697e-01 -8.68974090e-01
-3.35410312e-02 -1.19574285e+00 6.43597364e-01 7.24084437e-01
1.56639561e-01 -2.50273030e-02 6.42037213e-01 2.29543060e-01
-4.03433412e-01 -1.30964264e-01 8.92972052e-01 -3.01020831e-01
-1.29601073e+00 4.45056319e-01 -6.02585077e-01 -5.58599353e-01
1.04028499e+00 -4.57021862e-01 -2.10833728e-01 1.77297089e-02
-3.96240145e-01 4.34150100e-01 2.19084099e-01 4.32469904e-01
2.66030461e-01 -1.19701934e+00 -9.57851112e-01 5.49226105e-01
7.72083476e-02 2.69501537e-01 6.38590753e-01 4.90626186e-01
-8.59896898e-01 3.64694744e-01 -7.94134200e-01 -8.94618392e-01
-1.26793408e+00 8.30844343e-02 8.18678021e-01 -3.30039144e-01
-3.13813865e-01 6.44141436e-01 -2.44716734e-01 -3.94832075e-01
2.22244468e-02 -5.85564852e-01 -9.19061080e-02 3.42991263e-01
7.73027897e-01 1.04375266e-01 4.66957659e-01 -4.79285985e-01
-1.58208668e-01 3.77785563e-01 2.02865787e-02 1.87303290e-01
1.85812044e+00 -1.27346842e-02 -2.15741664e-01 3.37932050e-01
9.11906064e-01 -9.56282198e-01 -1.16668916e+00 -3.31755906e-01
-8.53277370e-02 -3.14677805e-01 7.09374964e-01 -7.80416429e-01
-1.30761492e+00 8.50079179e-01 1.34473932e+00 3.09113443e-01
1.51334751e+00 -4.10826951e-01 4.29326475e-01 5.89222014e-01
5.64422309e-01 -1.18295777e+00 -4.67322111e-01 5.91135979e-01
9.18594301e-01 -1.47007370e+00 -2.75328420e-02 2.86274076e-01
-4.53763515e-01 1.31356847e+00 7.41522312e-01 -1.83161385e-02
6.04106128e-01 4.50726002e-01 8.26729983e-02 -2.49059305e-01
-5.69979906e-01 -3.43420416e-01 -1.68171778e-01 3.95511746e-01
-1.74482120e-03 1.72025785e-01 -5.53383268e-02 3.72901410e-01
-1.76739711e-02 5.58713794e-01 3.43424022e-01 8.63320172e-01
-7.64957607e-01 -6.15144849e-01 -4.82474625e-01 7.73581624e-01
4.25119177e-02 -1.67229474e-01 -1.85128395e-02 7.20365584e-01
2.27789655e-01 3.65810513e-01 7.32969761e-01 -5.78063011e-01
1.54567942e-01 2.27567144e-02 -2.01196261e-02 -5.70858270e-02
-7.00120330e-01 -2.15840608e-01 -2.43580900e-02 -2.90570289e-01
-3.99441123e-01 -4.97806668e-01 -9.52696383e-01 -6.43840730e-01
-3.81719142e-01 1.99766271e-02 9.06633139e-01 8.55819345e-01
5.84801733e-01 1.64481342e-01 8.94954145e-01 -1.24356306e+00
-7.76140273e-01 -1.25912797e+00 -9.13280487e-01 4.21449915e-02
4.06662315e-01 -2.91705936e-01 -3.46195370e-01 1.42853811e-01] | [9.59597110748291, -1.4468575716018677] |
705e4bf8-292f-493b-8d97-9d543ae2f0de | chatgpt-vs-google-a-comparative-study-of | 2307.01135 | null | https://arxiv.org/abs/2307.01135v1 | https://arxiv.org/pdf/2307.01135v1.pdf | ChatGPT vs. Google: A Comparative Study of Search Performance and User Experience | The advent of ChatGPT, a large language model-powered chatbot, has prompted questions about its potential implications for traditional search engines. In this study, we investigate the differences in user behavior when employing search engines and chatbot tools for information-seeking tasks. We carry out a randomized online experiment, dividing participants into two groups: one using a ChatGPT-like tool and the other using a Google Search-like tool. Our findings reveal that the ChatGPT group consistently spends less time on all tasks, with no significant difference in overall task performance between the groups. Notably, ChatGPT levels user search performance across different education levels and excels in answering straightforward questions and providing general solutions but falls short in fact-checking tasks. Users perceive ChatGPT's responses as having higher information quality compared to Google Search, despite displaying a similar level of trust in both tools. Furthermore, participants using ChatGPT report significantly better user experiences in terms of usefulness, enjoyment, and satisfaction, while perceived ease of use remains comparable between the two tools. However, ChatGPT may also lead to overreliance and generate or replicate misinformation, yielding inconsistent results. Our study offers valuable insights for search engine management and highlights opportunities for integrating chatbot technologies into search engine designs. | ['Hailiang Chen', 'Yue Feng', 'Ruiyun Xu'] | 2023-07-03 | null | null | null | null | ['chatbot', 'misinformation', 'management', 'chatbot'] | ['methodology', 'miscellaneous', 'miscellaneous', 'natural-language-processing'] | [-7.36673474e-01 2.15403676e-01 -4.94450003e-01 2.06355408e-01
-6.33448482e-01 -7.02029407e-01 5.79263866e-01 1.90757111e-01
-6.05219483e-01 3.13327700e-01 1.76175207e-01 -9.21163738e-01
-2.83898443e-01 -3.39603931e-01 2.93392956e-01 -9.22557060e-03
5.64370275e-01 2.17568949e-01 2.37692118e-01 -3.42521042e-01
8.84836376e-01 -2.15553343e-01 -1.12117863e+00 9.08751339e-02
1.24317324e+00 5.09001493e-01 7.05418408e-01 4.71007645e-01
-5.38954914e-01 1.08394241e+00 -1.01768363e+00 -8.28877985e-01
-3.90930474e-02 -3.05480033e-01 -1.00298774e+00 -5.52098989e-01
4.58928019e-01 -4.64027435e-01 -2.80350149e-01 5.95736682e-01
5.76987147e-01 2.28359178e-01 1.33586287e-01 -1.24717963e+00
-1.01380312e+00 2.44078979e-01 1.61567867e-01 2.59543240e-01
9.22898948e-01 5.38502753e-01 1.06658137e+00 -3.32441300e-01
7.68280387e-01 9.44246829e-01 1.00963712e+00 2.96621412e-01
-1.28060877e+00 -7.64727652e-01 -4.07614887e-01 -3.15607013e-03
-1.05563807e+00 -5.42305410e-01 1.87968373e-01 -6.06056094e-01
1.28307462e+00 5.79697490e-01 8.85044217e-01 9.42891181e-01
4.91137564e-01 1.80795521e-01 1.30802715e+00 -3.65631223e-01
1.04907140e-01 9.73187208e-01 1.66928232e-01 4.45762664e-01
5.15479207e-01 -4.12953973e-01 -6.84854209e-01 -7.50443220e-01
5.44000506e-01 1.75850555e-01 -9.36781988e-02 3.67052108e-01
-8.56846452e-01 6.28425241e-01 2.92441577e-01 8.03502321e-01
-5.99510252e-01 2.52474025e-02 2.43063316e-01 5.90437353e-01
5.23489177e-01 1.09970403e+00 -1.86428189e-01 -1.05780470e+00
-3.98945302e-01 2.19297111e-01 1.55206323e+00 9.90496278e-01
4.54933941e-01 -4.27958041e-01 -6.10225737e-01 1.19654512e+00
1.28360331e-01 2.15339944e-01 6.60820961e-01 -1.18073893e+00
4.55896467e-01 6.69007540e-01 4.46162373e-01 -1.22243881e+00
6.04653731e-02 -3.17294031e-01 2.91457623e-01 -1.96624990e-03
6.01806402e-01 -2.78332978e-01 4.04077359e-02 1.20183837e+00
-2.81690568e-01 -8.68006229e-01 -7.00022876e-01 6.97910547e-01
5.76787174e-01 6.70130923e-02 5.18251181e-01 1.46025643e-01
1.63941109e+00 -8.34724844e-01 -9.29974616e-01 -5.51802814e-01
9.74668026e-01 -1.14501107e+00 1.71842182e+00 1.42021403e-02
-1.12953925e+00 -2.32065454e-01 -5.00279903e-01 -3.37646276e-01
-6.59952581e-01 -3.44904163e-03 6.02929533e-01 1.43330467e+00
-1.30440474e+00 4.79415596e-01 -2.78840810e-01 -8.80059361e-01
7.45694712e-02 -1.71635360e-01 5.75748682e-02 1.75189115e-02
-9.08262074e-01 1.43081772e+00 -3.70490819e-01 -5.15142560e-01
1.77712604e-01 -6.98438287e-01 -3.88667494e-01 5.57444692e-01
2.10382998e-01 -5.78766167e-01 1.86774623e+00 -4.16546434e-01
-1.50448537e+00 5.35990357e-01 -3.74247469e-02 7.32412338e-02
3.59200299e-01 -4.75140586e-02 1.17961690e-01 -5.99039942e-02
8.92605364e-01 9.07178298e-02 3.31436872e-01 -4.69532937e-01
-3.85959119e-01 -1.58694595e-01 3.19737166e-01 3.73634756e-01
-4.88369673e-01 4.05895144e-01 -1.40842110e-01 -9.03143287e-02
-2.76320398e-01 -5.67639470e-01 4.45829034e-02 3.92868742e-02
-6.04386590e-02 -5.75493574e-01 6.07704997e-01 -8.34555328e-01
1.60102379e+00 -1.75907624e+00 -9.86708939e-01 -6.08537272e-02
5.43561339e-01 1.64593831e-01 2.14783445e-01 1.28079093e+00
7.56685197e-01 9.59137380e-01 9.12819803e-01 -9.45490152e-02
3.20617706e-01 -2.46269256e-01 4.75235045e-01 -7.10666552e-02
-4.35537279e-01 1.03751707e+00 -9.73490894e-01 -6.91543400e-01
-1.73824698e-01 2.01392412e-01 -4.14418995e-01 -6.46532550e-02
1.52835652e-01 4.61988412e-02 -5.49238086e-01 6.31137490e-01
3.34945261e-01 -6.70547903e-01 1.46078408e-01 8.27478647e-01
-7.98353732e-01 1.07364249e+00 -1.63527206e-01 1.25231433e+00
-1.11688113e+00 1.01079011e+00 4.49996352e-01 -6.47869557e-02
4.83683914e-01 5.02931476e-01 7.50623941e-02 -1.12163675e+00
1.27362639e-01 3.04391801e-01 1.63276523e-01 -8.39922309e-01
7.68510461e-01 2.82805175e-01 2.44127378e-01 1.01361561e+00
-1.54208481e-01 -2.85460949e-01 1.96258388e-02 4.13753390e-01
1.53836584e+00 -4.83751565e-01 2.62324184e-01 -4.51051742e-01
-2.90301621e-01 1.89273566e-01 -2.55621225e-01 1.50052845e+00
-3.41510177e-01 -1.22482702e-01 5.30569673e-01 2.71651179e-01
-5.60300291e-01 -4.68533427e-01 1.64236680e-01 1.36877906e+00
7.09495842e-02 -9.20487761e-01 -6.33738577e-01 -4.73687619e-01
9.87836793e-02 1.03630495e+00 3.40360738e-02 -1.73279420e-01
2.56821573e-01 1.89254791e-01 6.51074052e-01 -1.13095539e-02
1.07353127e+00 -8.96536648e-01 -1.01102912e+00 4.29700799e-02
-6.63144171e-01 -6.70952976e-01 -1.15528774e+00 -3.17749828e-01
-8.40662241e-01 -8.22340667e-01 -6.82740808e-01 -6.15679681e-01
1.45564839e-01 1.13739383e+00 1.18693459e+00 9.21251118e-01
-2.94571042e-01 1.04959047e+00 -4.10178065e-01 -3.91519517e-01
-2.90295601e-01 4.38168287e-01 -6.50338113e-01 -9.01093185e-01
4.54599082e-01 -3.35521191e-01 -6.35544002e-01 4.58608359e-01
-2.51202554e-01 -1.53780997e-01 7.08398223e-01 6.09066427e-01
-8.61759841e-01 -2.76624769e-01 5.97714543e-01 -6.73199415e-01
1.74605620e+00 -8.89455378e-01 -2.23177388e-01 9.01162922e-02
-1.30878615e+00 -4.85047936e-01 2.18959466e-01 -4.66042995e-01
-1.22344625e+00 -8.96531284e-01 1.38461173e-01 2.86513358e-01
3.30794394e-01 8.42677236e-01 5.01405478e-01 -5.59443116e-01
1.09203708e+00 -5.65390810e-02 5.81745505e-01 -5.69830656e-01
-9.91286114e-02 1.10851181e+00 -2.65716434e-01 -4.68469739e-01
4.66285169e-01 -1.74625814e-01 -9.92419004e-01 -1.24125767e+00
-1.87714264e-01 -8.91811550e-01 2.31817260e-01 -3.29723120e-01
7.65737891e-01 -4.22385007e-01 -1.71911108e+00 1.76051721e-01
-9.73044813e-01 -7.42544472e-01 2.46338442e-01 4.04488683e-01
-1.07943363e-01 2.26001844e-01 -8.06335330e-01 -1.33549953e+00
-3.30297112e-01 -8.45773935e-01 5.37036479e-01 5.16804874e-01
-7.63122082e-01 -1.10976923e+00 4.36123461e-02 1.00806952e+00
1.22405934e+00 -7.25111127e-01 7.83467889e-01 -8.54716361e-01
-8.80915344e-01 -6.99650109e-01 -3.06229174e-01 -9.31850746e-02
3.44042480e-01 -4.59160000e-01 -5.97005844e-01 6.41978458e-02
1.97695225e-01 -3.26786309e-01 9.80459061e-03 2.92039458e-02
4.12929267e-01 -8.02324772e-01 -4.72074538e-01 -3.52973521e-01
1.06338441e+00 4.65708435e-01 3.21168333e-01 7.11813390e-01
-1.70622900e-01 5.45871019e-01 4.75409031e-01 1.70435444e-01
3.28198016e-01 9.41693664e-01 -6.97186217e-02 6.39438212e-01
5.06204739e-02 -6.43622398e-01 1.89428046e-01 4.08846140e-01
4.86306250e-02 -1.27166733e-01 -8.94337058e-01 5.02936125e-01
-1.52911747e+00 -1.00150371e+00 -2.31838133e-02 2.20135188e+00
5.79411030e-01 -1.14851706e-01 3.32776487e-01 -4.71191645e-01
5.36683202e-01 2.29584565e-03 -2.75760919e-01 -4.14141834e-01
5.86148024e-01 3.47019017e-01 4.02637750e-01 5.60288906e-01
-1.11982785e-02 5.98628938e-01 6.88533354e+00 4.98262256e-01
-8.74882281e-01 5.47138453e-01 3.86471957e-01 1.47163942e-01
-2.31081769e-01 4.20105994e-01 -1.64056510e-01 6.88751459e-01
9.75087941e-01 -7.80794680e-01 6.40718758e-01 1.12327456e+00
3.27516764e-01 -6.94679320e-01 -5.59877038e-01 7.52801538e-01
-2.67234236e-01 -1.38759863e+00 -6.97173357e-01 3.72688562e-01
1.50896445e-01 -2.00446963e-01 3.72882038e-02 6.70181453e-01
2.46652573e-01 -7.69115090e-01 6.40243292e-01 2.16506556e-01
4.78608429e-01 -1.16137536e-02 5.82563758e-01 8.06884646e-01
-6.96754515e-01 -7.95622170e-02 -1.73125073e-01 -1.02874756e+00
-9.28237140e-02 6.40439168e-02 -1.33757794e+00 1.02133460e-01
8.15689385e-01 6.00349829e-02 -6.85286522e-01 1.27294385e+00
2.81926423e-01 5.89323997e-01 -1.72120705e-01 -9.20064509e-01
-1.66515365e-01 -6.07141972e-01 3.99298310e-01 9.06035304e-01
3.74951869e-01 -5.36468737e-02 -2.42996216e-01 1.14107823e+00
1.02623098e-01 8.33160728e-02 -9.39361811e-01 -5.42829871e-01
1.25197649e+00 1.29534185e+00 -7.88798571e-01 -2.95747429e-01
-5.88289380e-01 9.04920578e-01 1.82180718e-01 3.73759598e-01
-3.10443640e-01 -7.98713982e-01 8.00047994e-01 5.59323967e-01
-3.55491966e-01 -2.90151536e-01 -8.15082312e-01 -9.43560958e-01
2.38649726e-01 -8.27240229e-01 4.52015661e-02 -1.11415005e+00
-1.10911536e+00 1.69548005e-01 -1.69581383e-01 -6.80100143e-01
-3.00004154e-01 -1.29693389e-01 -8.79460812e-01 1.34620309e+00
-6.34173512e-01 -3.35045874e-01 -6.52099848e-01 3.97780463e-02
5.38037896e-01 3.16165298e-01 4.24908876e-01 2.27017924e-01
-4.76210602e-02 5.96267283e-01 -1.16471961e-01 -2.27727637e-01
9.65271950e-01 -9.11067307e-01 2.58944213e-01 1.04619458e-01
-3.14017504e-01 1.54399681e+00 5.30350924e-01 -8.24174225e-01
-1.44774044e+00 -1.38651580e-01 1.40534449e+00 -8.98466289e-01
6.11783564e-01 -4.09424901e-01 -5.17751098e-01 6.38850510e-01
7.66688347e-01 -1.00282967e+00 5.54904640e-01 6.11244500e-01
-2.35719234e-01 4.32563633e-01 -1.36462116e+00 8.71890306e-01
1.20757604e+00 -1.12799096e+00 -3.85502666e-01 5.76004326e-01
4.65789199e-01 -1.24549225e-01 -7.49195576e-01 -7.71453500e-01
9.68407035e-01 -1.32443058e+00 7.52540112e-01 -2.50405788e-01
3.31950963e-01 6.31646276e-01 5.51499426e-01 -1.30469680e+00
-5.01659811e-01 -1.15874290e+00 6.65476739e-01 1.20596039e+00
2.97788650e-01 -1.38881290e+00 7.73513317e-01 1.56482661e+00
-1.81454986e-01 -4.15174812e-01 -9.77546334e-01 -8.14779103e-01
-2.47696079e-02 -1.32554591e-01 9.81979668e-02 9.49266553e-01
9.16463315e-01 4.22791243e-01 -4.09761770e-03 -4.98513401e-01
5.76282805e-03 -5.45503557e-01 7.40075231e-01 -1.32161951e+00
-1.80440068e-01 -8.35163057e-01 4.13604733e-03 -1.14338005e+00
-2.40557253e-01 -7.08500803e-01 -1.85407504e-01 -1.70525014e+00
2.30295300e-01 -4.04778570e-01 7.65107036e-01 5.75578928e-01
-2.13406652e-01 -2.75107831e-01 4.07605857e-01 5.07554471e-01
-4.96888667e-01 1.28090277e-01 1.11823487e+00 1.87208384e-01
-5.24746597e-01 4.39521819e-01 -1.47354722e+00 7.25208968e-02
8.00460994e-01 -2.83160269e-01 -6.80182338e-01 -1.86635390e-01
4.38686937e-01 4.10807550e-01 4.21856374e-01 -7.74248481e-01
5.37321031e-01 -2.12527916e-01 -2.63936013e-01 2.58565038e-01
2.97835112e-01 -7.56270468e-01 6.79425448e-02 4.87980783e-01
-3.46877396e-01 3.97133142e-01 6.42708763e-02 1.30401760e-01
1.28532261e-01 -5.67588806e-01 6.34259358e-02 -2.95534372e-01
3.64958227e-01 -4.38426286e-01 -1.39417613e+00 1.42144889e-01
4.23079103e-01 -6.87532187e-01 -7.40624964e-01 -1.26417255e+00
-2.31443904e-02 2.09843144e-01 5.90713978e-01 3.30894381e-01
2.42960658e-02 -9.72764730e-01 1.32066175e-01 -1.42242834e-01
-5.17970650e-03 -6.98489249e-01 1.56836331e-01 1.27842498e+00
-5.05976319e-01 1.02026689e+00 -7.61586502e-02 3.62616032e-03
-1.18724644e+00 -8.60932618e-02 1.30459517e-01 -7.28740320e-02
-2.44124338e-01 5.38310170e-01 -2.39929900e-01 -3.43118191e-01
1.07396975e-01 -1.71183184e-01 2.22311780e-01 -5.75988041e-03
3.47481012e-01 9.11583781e-01 1.57084316e-01 2.34941900e-01
-8.06463659e-02 -2.43713140e-01 -1.09910376e-01 -4.68795329e-01
5.73467374e-01 -2.12403327e-01 -2.40771413e-01 4.36261326e-01
8.85148108e-01 4.26048249e-01 -3.43011498e-01 2.31970713e-01
2.75901347e-01 -1.27358925e+00 -3.11978579e-01 -1.14786685e+00
-3.69999975e-01 3.11383545e-01 4.04511504e-02 9.85996306e-01
3.66878420e-01 1.47889465e-01 4.74604338e-01 8.72386038e-01
6.40822589e-01 -9.94442046e-01 4.17878717e-01 3.91788512e-01
8.20514143e-01 -8.97563517e-01 -3.01720619e-01 -2.99028575e-01
-6.66907787e-01 6.26527369e-01 7.95132160e-01 4.22560662e-01
5.32845736e-01 -3.51683795e-01 1.62686437e-01 -5.85097671e-01
-9.52712357e-01 2.19441555e-03 -2.28457063e-01 7.35233843e-01
1.02206206e+00 -3.36267143e-01 -1.06472230e+00 5.06995916e-01
-5.46692729e-01 2.34793797e-01 6.38520479e-01 1.13088536e+00
-4.54273909e-01 -9.05681074e-01 -2.92206466e-01 8.91491652e-01
-4.76288646e-01 -3.92950952e-01 -9.49088931e-01 1.09604478e+00
-7.57672310e-01 1.49202430e+00 -1.81473449e-01 -4.50228512e-01
2.80894935e-01 6.73305511e-01 -1.29806131e-01 -7.88527071e-01
-1.25604224e+00 -4.04964000e-01 6.21634066e-01 -4.87949610e-01
3.31615359e-01 -5.86540937e-01 -2.42953792e-01 -7.03713119e-01
-7.40088284e-01 8.77694905e-01 7.08550215e-01 5.83794713e-01
1.04975677e+00 -1.96424574e-01 1.25512600e-01 -4.22295511e-01
-8.22522163e-01 -1.52458715e+00 -2.92193800e-01 3.54609378e-02
2.94014961e-02 -6.09513462e-01 -3.58487576e-01 -6.47884548e-01] | [12.203276634216309, 7.763009548187256] |
2d05e106-53f6-49be-bceb-b078b9c89d3b | nextdoor-gpu-based-graph-sampling-for | 2009.06693 | null | https://arxiv.org/abs/2009.06693v4 | https://arxiv.org/pdf/2009.06693v4.pdf | Accelerating Graph Sampling for Graph Machine Learning using GPUs | Representation learning algorithms automatically learn the features of data. Several representation learning algorithms for graph data, such as DeepWalk, node2vec, and GraphSAGE, sample the graph to produce mini-batches that are suitable for training a DNN. However, sampling time can be a significant fraction of training time, and existing systems do not efficiently parallelize sampling. Sampling is an embarrassingly parallel problem and may appear to lend itself to GPU acceleration, but the irregularity of graphs makes it hard to use GPU resources effectively. This paper presents NextDoor, a system designed to effectively perform graph sampling on GPUs. NextDoor employs a new approach to graph sampling that we call transit-parallelism, which allows load balancing and caching of edges. NextDoor provides end-users with a high-level abstraction for writing a variety of graph sampling algorithms. We implement several graph sampling applications, and show that NextDoor runs them orders of magnitude faster than existing systems. | ['Marco Serafini', 'Arjun Guha', 'Sandeep Polisetty', 'Abhinav Jangda'] | 2020-09-14 | null | null | null | null | ['graph-sampling'] | ['graphs'] | [-1.80358559e-01 9.93807986e-02 -5.16400218e-01 -3.94242913e-01
-6.28949344e-01 -6.09129965e-01 4.55747426e-01 5.64099848e-01
-1.77612573e-01 4.22721505e-01 1.81219742e-01 -8.29988301e-01
2.66553015e-01 -1.65547621e+00 -5.51998913e-01 -5.27705491e-01
-3.97193879e-01 8.77969921e-01 1.49103865e-01 -6.36414140e-02
-4.07303721e-02 7.02958167e-01 -1.70082700e+00 2.51540184e-01
2.40744561e-01 4.91916060e-01 -2.76088957e-02 1.17596304e+00
-5.52964568e-01 7.19687104e-01 -3.94650072e-01 -2.27334425e-01
3.39054555e-01 -3.09422523e-01 -8.76159668e-01 1.46599291e-02
8.13270390e-01 -4.99720365e-01 -8.50455880e-01 8.62100482e-01
3.77161026e-01 4.99922305e-01 5.79123259e-01 -1.37026083e+00
-1.67194843e-01 8.33510935e-01 -6.54077172e-01 3.01329583e-01
4.38210547e-01 -3.24529074e-02 1.16758394e+00 -4.71768498e-01
7.81180799e-01 1.18693399e+00 7.48147190e-01 3.32388878e-01
-1.30486131e+00 -4.78750646e-01 2.88029592e-02 -5.40816486e-02
-1.22708035e+00 -1.88133240e-01 4.88475442e-01 -1.90100759e-01
1.20709538e+00 4.87025648e-01 1.18892622e+00 8.69995177e-01
-1.33201359e-02 1.09050500e+00 5.64262092e-01 -4.76403624e-01
3.78254145e-01 -1.66229442e-01 7.24900782e-01 1.15242720e+00
6.66450143e-01 -1.10396244e-01 -3.57689112e-01 -8.91187787e-01
1.04206312e+00 2.42471829e-01 -2.58306935e-02 -4.65942144e-01
-9.00053620e-01 1.14445210e+00 5.30853212e-01 -1.16896830e-01
-2.26397336e-01 7.69736946e-01 1.01274872e+00 4.76434171e-01
5.16752362e-01 1.40331775e-01 -2.81650245e-01 -3.36457282e-01
-9.85038877e-01 3.98825079e-01 1.29247618e+00 1.37584817e+00
1.25590026e+00 2.63696223e-01 -1.00756407e-01 6.68313622e-01
2.01343354e-02 2.21955225e-01 3.15407544e-01 -6.90736055e-01
3.63750637e-01 5.97126961e-01 -5.36629260e-01 -1.13119805e+00
-3.77452821e-01 -1.79410070e-01 -9.64295983e-01 -3.41665745e-02
4.48271662e-01 -2.99143076e-01 -8.54676306e-01 1.18781352e+00
6.13061666e-01 1.39984071e-01 -3.01660001e-01 5.33606648e-01
8.63735437e-01 7.74117470e-01 -1.36763170e-01 1.49924815e-01
1.23660719e+00 -1.07641745e+00 -1.60724506e-01 -2.99833328e-01
1.11858070e+00 -4.31565672e-01 1.22137690e+00 4.96909201e-01
-9.79564488e-01 -1.89744845e-01 -9.60195482e-01 -3.42469007e-01
-4.49652046e-01 -2.37912178e-01 1.75571513e+00 7.92983949e-01
-1.21142268e+00 8.92218828e-01 -1.20266759e+00 -5.40222347e-01
5.22441387e-01 2.17615455e-01 -4.36586499e-01 -4.66743827e-01
-5.02930284e-01 2.25232124e-01 5.03217697e-01 -4.50125635e-01
-7.78348505e-01 -6.39169693e-01 -1.05411780e+00 1.09340049e-01
1.91545591e-01 -8.94089282e-01 1.18554199e+00 -7.25537956e-01
-1.03709924e+00 6.17545366e-01 -2.42294699e-01 -4.83337909e-01
1.74575016e-01 8.98175389e-02 -7.68691301e-02 1.18006743e-01
-2.80464172e-01 1.89885616e-01 7.74618745e-01 -6.72829330e-01
-2.40655571e-01 -4.30775374e-01 1.11239731e-01 1.67617291e-01
-6.84271693e-01 -2.49316916e-01 -6.39056265e-01 -3.80048066e-01
-1.08341180e-01 -7.74626136e-01 -7.75102198e-01 6.73743756e-03
-3.43966544e-01 -3.92500490e-01 7.10645914e-01 -8.45776647e-02
1.28478050e+00 -1.95328259e+00 -2.35079020e-01 5.68332136e-01
8.23352575e-01 1.31770074e-01 -6.31213784e-02 7.89194643e-01
1.72167003e-01 -1.35108933e-01 1.28663510e-01 -1.53225332e-01
-7.60803968e-02 6.59897089e-01 -1.47398517e-01 5.90025604e-01
-3.41792494e-01 6.88650966e-01 -1.32345092e+00 -4.35245693e-01
1.47372127e-01 3.72187227e-01 -9.04163599e-01 1.32777020e-01
-4.13143933e-01 -5.06065547e-01 -5.39455771e-01 3.90969962e-01
8.01434100e-01 -6.05458856e-01 4.88600910e-01 3.86037827e-02
3.52910191e-01 5.31538844e-01 -1.34825945e+00 1.67037570e+00
-5.72557926e-01 7.53519118e-01 -1.14980958e-01 -8.49257112e-01
7.86331236e-01 -1.43962517e-01 1.19521916e-01 -1.03728093e-01
9.78415832e-02 5.19141890e-02 -4.13810074e-01 9.44723189e-03
9.84176397e-01 3.24914992e-01 7.39780813e-02 9.38563049e-01
1.43584862e-01 -2.53182173e-01 6.05250895e-01 6.75187588e-01
1.55466449e+00 -2.42446110e-01 3.73790681e-01 -4.02148128e-01
-2.46748820e-01 3.36148411e-01 3.88540290e-02 9.52706695e-01
4.11349803e-01 4.29219335e-01 8.06073010e-01 -1.03026295e+00
-9.98554409e-01 -8.73806536e-01 3.05270225e-01 1.35572946e+00
-4.20207083e-01 -1.16529679e+00 -7.50624418e-01 -7.80244231e-01
1.81764498e-01 6.29871011e-01 -4.57782835e-01 -3.43136676e-02
-4.39815730e-01 -7.87829876e-01 3.96729976e-01 9.00331497e-01
4.83503863e-02 -6.95059299e-01 -3.15008521e-01 3.44681114e-01
6.49644852e-01 -7.44399548e-01 -6.17446363e-01 3.49414051e-01
-1.23249900e+00 -1.26619363e+00 -2.15206161e-01 -8.81241620e-01
1.13274705e+00 7.53587127e-01 1.65628600e+00 5.99090517e-01
-6.42778993e-01 3.49027276e-01 -1.19298086e-01 -2.03769013e-01
-3.92861873e-01 5.25660515e-01 -3.25103253e-01 -5.80663502e-01
6.55279160e-01 -9.21104491e-01 -4.95770097e-01 -3.95466626e-01
-9.19983089e-01 1.20733880e-01 1.50152966e-01 9.79188204e-01
7.44548678e-01 5.79899028e-02 -4.31071147e-02 -1.65520787e+00
9.43176508e-01 -6.98345840e-01 -8.11865091e-01 -5.12728728e-02
-5.64009309e-01 1.68338880e-01 9.89564002e-01 -4.18497205e-01
-2.07515284e-01 1.66449606e-01 -2.15970963e-01 -5.36175668e-01
1.79089546e-01 6.62946939e-01 3.00325781e-01 -9.62891430e-02
1.02815688e+00 2.37639233e-01 2.77877897e-01 -2.91251808e-01
6.58675194e-01 3.79675150e-01 2.27985717e-02 -8.68721962e-01
5.88448822e-01 3.45173717e-01 1.04661964e-01 -1.05065668e+00
-5.60121298e-01 -5.24945915e-01 -4.56960350e-02 3.58771943e-02
8.35481137e-02 -8.62645864e-01 -6.83684886e-01 7.40001351e-02
-8.03033710e-01 -8.87146771e-01 -5.21982729e-01 2.44942844e-01
-3.57699573e-01 4.34642702e-01 -8.76222372e-01 -5.47366261e-01
-7.61052072e-01 -9.41702843e-01 1.08049202e+00 -2.45221574e-02
-2.76806861e-01 -1.31179249e+00 1.32564172e-01 -3.33420932e-01
4.08974349e-01 3.78656149e-01 1.03042042e+00 -7.12911904e-01
-6.81901753e-01 -6.28845870e-01 -3.10545266e-01 -7.89665524e-03
-1.42390400e-01 1.17966853e-01 -8.23630929e-01 -7.24053502e-01
-6.75593078e-01 -4.02595729e-01 8.29569995e-01 1.45925909e-01
1.65838933e+00 -3.97125602e-01 -5.92470288e-01 8.76576841e-01
1.70788074e+00 -4.62222576e-01 5.93342423e-01 -1.82129890e-01
1.05010605e+00 -6.31364807e-02 1.23385325e-01 6.08037472e-01
4.93123770e-01 1.79588377e-01 2.57860303e-01 -1.80407286e-01
-1.65697232e-01 -5.46626985e-01 4.30757478e-02 1.16569817e+00
2.70390827e-02 -3.02800506e-01 -9.72896338e-01 6.64309084e-01
-1.66643655e+00 -7.38094211e-01 -5.37733734e-01 2.38631463e+00
4.86985117e-01 -6.12823153e-03 5.17764747e-01 1.19690545e-01
3.96602780e-01 2.80362457e-01 -3.12525928e-01 -9.09476399e-01
4.11670774e-01 7.07419813e-01 1.03042221e+00 5.07551908e-01
-7.78172731e-01 1.10110927e+00 7.11714220e+00 1.02620268e+00
-8.70443821e-01 -8.79091248e-02 5.25339901e-01 -7.02654291e-03
-6.86701357e-01 1.70175225e-01 -8.31454158e-01 9.05318931e-02
1.16724801e+00 -6.40266240e-01 8.41380894e-01 1.53652537e+00
-4.09595460e-01 1.88884754e-02 -1.28627157e+00 1.08559716e+00
-4.28151004e-02 -1.63624144e+00 3.46309096e-01 2.90768325e-01
6.21810675e-01 5.27795553e-01 -3.66109520e-01 5.92960238e-01
1.00382364e+00 -1.00354064e+00 -9.77457408e-03 -5.85391410e-02
8.00869107e-01 -1.05052519e+00 3.23933601e-01 1.93544373e-01
-1.47318959e+00 3.44482422e-01 -9.24786925e-01 -2.29755387e-01
-2.22888336e-01 8.55408192e-01 -1.16994870e+00 3.80195141e-01
3.42263788e-01 6.27036572e-01 -6.08245015e-01 9.90849912e-01
-2.78142537e-03 7.94927180e-01 -6.85111105e-01 -5.99720359e-01
3.34440798e-01 -2.68579423e-01 1.84990093e-01 1.41814339e+00
3.31934452e-01 -1.47730455e-01 5.77846587e-01 4.22136128e-01
-3.55472356e-01 3.47475529e-01 -1.22754824e+00 -4.38944101e-01
6.13592744e-01 1.33189201e+00 -1.00489318e+00 -8.12002182e-01
-5.37296772e-01 8.80164802e-01 8.08306277e-01 1.81645051e-01
-5.32444358e-01 -6.87041938e-01 8.14617038e-01 2.20288709e-01
2.84442723e-01 -5.36338687e-01 -4.10491712e-02 -1.22311485e+00
-2.09031880e-01 -1.03702497e+00 6.29621446e-01 -4.08859640e-01
-1.20448351e+00 5.85645139e-01 -1.28033161e-01 -8.57238770e-01
-4.49747056e-01 -6.35290980e-01 -5.35274625e-01 7.13715076e-01
-9.49727297e-01 -8.82016063e-01 -5.48024178e-01 7.27387547e-01
2.38852561e-01 -4.14815657e-02 1.19311678e+00 1.61496535e-01
-2.18381912e-01 7.62864351e-01 1.91580161e-01 1.74280211e-01
4.76961285e-02 -1.44037998e+00 1.30200863e+00 5.33176422e-01
6.02162600e-01 7.83909082e-01 5.95018804e-01 -4.78641987e-01
-2.39590907e+00 -1.31193960e+00 5.98196149e-01 -6.74414029e-03
6.85150325e-01 -6.43546879e-01 -8.03127170e-01 1.14852226e+00
-3.52139138e-02 7.12264001e-01 7.32606709e-01 6.56235278e-01
-6.15996480e-01 -7.41064921e-02 -1.05334604e+00 9.42348063e-01
1.26699817e+00 -6.23276114e-01 4.23036367e-02 9.67157006e-01
6.54329300e-01 -7.34268606e-01 -8.54359806e-01 -4.27831829e-01
3.54082316e-01 -6.69716597e-01 9.35243964e-01 -7.88985729e-01
-5.80698550e-02 -1.29220868e-02 -6.24831468e-02 -1.37861073e+00
-3.36875051e-01 -8.73080850e-01 -6.18399620e-01 7.90121675e-01
2.13410035e-01 -9.16030705e-01 1.34676170e+00 4.31681871e-01
1.51924923e-01 -7.75468826e-01 -2.88768351e-01 -7.41991043e-01
-4.58875857e-02 -6.30377531e-01 1.03803897e+00 1.05973864e+00
1.50634468e-01 4.82881278e-01 4.85500135e-02 -5.95441386e-02
6.65747046e-01 2.63984710e-01 1.45969272e+00 -1.19109750e+00
-6.49431646e-01 -3.31106722e-01 -7.63277233e-01 -1.26990938e+00
1.05876669e-01 -1.58925283e+00 -5.33067524e-01 -1.81579137e+00
2.96822041e-02 -5.21948874e-01 1.50666088e-01 6.22621596e-01
-5.73974811e-02 8.39026347e-02 -2.68451333e-01 -2.55248785e-01
-4.67581987e-01 1.40219346e-01 1.14739609e+00 -9.95562822e-02
-1.43341586e-01 2.08559912e-02 -7.21930861e-01 4.60687876e-01
8.14007401e-01 -4.19334054e-01 -8.41200352e-01 -6.27090216e-01
4.69186127e-01 1.15505062e-01 9.55764577e-02 -9.51837301e-01
3.66134644e-01 3.10944747e-02 3.91104758e-01 -6.40870690e-01
2.41343722e-01 -4.10928577e-01 1.13723136e-01 2.40754381e-01
-2.12276876e-01 3.55413437e-01 3.11058760e-01 6.48288012e-01
6.57053217e-02 -1.24232247e-01 5.04019260e-01 -3.70483160e-01
-3.99778396e-01 8.82861257e-01 -4.95212346e-01 4.83450174e-01
6.78557575e-01 -2.05283076e-01 -2.21703395e-01 -4.37634349e-01
-3.81130755e-01 5.85436411e-02 6.82870865e-01 -8.83330777e-02
5.98066449e-01 -1.30706751e+00 -3.88397604e-01 3.75389367e-01
1.24417581e-01 1.96788296e-01 -1.91262644e-02 3.20302874e-01
-1.08012617e+00 -2.23214686e-01 2.94447392e-01 -3.97333473e-01
-1.31493831e+00 7.98254550e-01 -4.35707979e-02 -2.96216697e-01
-1.28896832e+00 1.06119668e+00 -2.72579104e-01 -5.22373319e-01
1.45840004e-01 -4.55756634e-01 4.07335758e-01 -3.28660272e-02
8.46015632e-01 4.44113791e-01 2.28452131e-01 1.36018649e-01
-1.46145701e-01 3.25163491e-02 -3.92828673e-01 4.24907506e-01
1.41988683e+00 5.95518529e-01 -3.54088336e-01 2.96286792e-01
1.54211295e+00 -1.44746736e-01 -8.47529888e-01 -1.55480936e-01
-2.22870171e-01 -6.61468744e-01 2.91003853e-01 4.71733175e-02
-1.32520545e+00 7.67388701e-01 3.14950831e-02 6.56937063e-01
8.33659172e-01 -2.31120065e-01 1.08208346e+00 7.25973368e-01
8.21666062e-01 -1.01862419e+00 -3.77325445e-01 4.64083314e-01
2.74167269e-01 -8.30466509e-01 4.72119600e-01 -5.47359943e-01
-8.01705495e-02 1.39166403e+00 4.60108131e-01 -7.99831927e-01
7.20708609e-01 5.89263976e-01 -3.53118896e-01 -5.09276271e-01
-1.05992591e+00 -1.68214664e-01 -1.45133942e-01 8.19710851e-01
5.90363503e-01 4.49645996e-01 -1.34112865e-01 -9.15181413e-02
-5.02089918e-01 -9.71726030e-02 6.50360048e-01 9.84862864e-01
-3.76432300e-01 -1.23660767e+00 3.05736884e-02 1.18820930e+00
-3.34763750e-02 -2.06694186e-01 -9.89759192e-02 9.95861530e-01
-6.63231432e-01 4.62242723e-01 3.92064095e-01 -3.51607621e-01
1.06618069e-01 -2.56829292e-01 6.93629801e-01 -8.67493987e-01
-6.88335419e-01 -4.23646241e-01 5.49894750e-01 -7.73463726e-01
4.06115949e-01 -3.89146149e-01 -1.24466503e+00 -1.01148880e+00
-1.64943948e-01 2.61193931e-01 6.17302895e-01 2.88767129e-01
5.00918448e-01 4.22630906e-01 4.50697839e-01 -9.01209533e-01
-3.97890657e-01 -6.32362783e-01 -8.78824770e-01 8.88986215e-02
2.89980918e-02 -2.16184855e-01 -2.69032300e-01 -5.46316981e-01] | [6.988565444946289, 5.783038139343262] |
fe103ec3-8dd1-48bd-b81f-001b0aaeb2d2 | xkd-cross-modal-knowledge-distillation-with | 2211.13929 | null | https://arxiv.org/abs/2211.13929v4 | https://arxiv.org/pdf/2211.13929v4.pdf | XKD: Cross-modal Knowledge Distillation with Domain Alignment for Video Representation Learning | We present XKD, a novel self-supervised framework to learn meaningful representations from unlabelled video clips. XKD is trained with two pseudo tasks. First, masked data reconstruction is performed to learn individual representations from audio and visual streams. Next, self-supervised cross-modal knowledge distillation is performed between the two modalities through teacher-student setups to learn complementary information. To identify the most effective information to transfer and also to tackle the domain gap between audio and visual modalities which could hinder knowledge transfer, we introduce a domain alignment and feature refinement strategy for effective cross-modal knowledge distillation. Lastly, to develop a general-purpose network capable of handling both audio and visual streams, modality-agnostic variants of our proposed framework are introduced, which use the same backbone for both audio and visual modalities. Our proposed cross-modal knowledge distillation improves linear evaluation top-1 accuracy of video action classification by 8.6% on UCF101, 8.2% on HMDB51, 13.9% on Kinetics-Sound, and 15.7% on Kinetics400. Additionally, our modality-agnostic variant shows promising results in developing a general-purpose network capable of learning both data streams for solving different downstream tasks. | ['Ali Etemad', 'Pritam Sarkar'] | 2022-11-25 | null | null | null | null | ['action-classification', 'self-supervised-action-recognition'] | ['computer-vision', 'computer-vision'] | [ 4.48122770e-01 5.60800254e-04 -2.17490584e-01 -2.64423132e-01
-1.19715548e+00 -5.49950957e-01 6.77843153e-01 2.71218698e-02
-6.26685619e-01 7.19529152e-01 2.39129901e-01 1.06381342e-01
-9.61470231e-02 -4.48014289e-01 -1.06520379e+00 -5.80476224e-01
-2.18448088e-01 2.70085961e-01 3.03762197e-01 -1.18729763e-01
-1.63646996e-01 2.12121785e-01 -1.88481987e+00 9.74293232e-01
4.08385694e-01 1.36276436e+00 1.60867035e-01 8.29580128e-01
-3.18945982e-02 1.15476894e+00 -5.14758527e-01 -9.85908806e-02
1.97314054e-01 -5.32762229e-01 -1.21801424e+00 1.72131255e-01
5.93211234e-01 -3.36951107e-01 -3.88916433e-01 5.42992890e-01
7.37839818e-01 3.70258778e-01 7.04792440e-01 -1.40257668e+00
-4.13372278e-01 7.32483149e-01 -4.83544827e-01 3.59228283e-01
5.44455409e-01 4.08035249e-01 8.62606287e-01 -7.98402548e-01
5.20305812e-01 1.11284876e+00 3.86861503e-01 9.36098695e-01
-1.21063066e+00 -8.67312729e-01 1.40286252e-01 6.67096674e-01
-1.22710717e+00 -6.85794830e-01 7.00335681e-01 -5.41745842e-01
9.89415109e-01 1.45580679e-01 4.60822940e-01 1.56498921e+00
-4.88454670e-01 1.05310714e+00 1.10109162e+00 -4.02361304e-01
1.11821152e-01 2.24365443e-01 -1.02823786e-01 4.09423351e-01
-4.12188888e-01 1.39353186e-01 -1.30204511e+00 1.33718103e-01
6.21145844e-01 -1.89978853e-01 -3.30243617e-01 -3.09129149e-01
-1.34777164e+00 4.71678972e-01 3.33130002e-01 1.44875929e-01
-2.31700033e-01 1.21082500e-01 8.10193241e-01 5.46198547e-01
2.75741100e-01 4.76173490e-01 -6.67280614e-01 -4.62855756e-01
-7.41911292e-01 -1.06637277e-01 5.16505837e-01 8.71830225e-01
6.50609434e-01 1.47143707e-01 -3.89258862e-01 8.80218744e-01
1.52021319e-01 4.78083581e-01 6.24387920e-01 -1.08127129e+00
6.88691974e-01 3.98789972e-01 -6.56016991e-02 -6.47651196e-01
-4.07856554e-01 -2.75059432e-01 -8.10589850e-01 4.12807725e-02
4.66649413e-01 -5.30779175e-02 -9.65802372e-01 1.88654196e+00
2.90514618e-01 6.75327420e-01 5.48199713e-01 1.02234125e+00
1.30253124e+00 5.71075141e-01 2.49879792e-01 -1.92485571e-01
1.27410984e+00 -1.05999136e+00 -5.09438276e-01 -2.55793557e-02
4.21941042e-01 -5.24280310e-01 1.12863636e+00 5.37648022e-01
-1.12468696e+00 -8.29799235e-01 -9.01400626e-01 3.77171077e-02
-2.61001348e-01 1.21168882e-01 3.13561857e-01 9.44599658e-02
-8.55603397e-01 4.22253311e-01 -8.21270168e-01 -3.01673472e-01
6.20668709e-01 2.93555379e-01 -7.11032689e-01 -1.32285804e-01
-1.29319000e+00 6.31255686e-01 7.83892334e-01 -2.40572810e-01
-1.46803558e+00 -9.86763120e-01 -8.40304554e-01 -8.02964866e-02
5.77670276e-01 -6.06377602e-01 1.33377159e+00 -1.48206604e+00
-1.73395991e+00 9.16830301e-01 2.57602751e-01 -5.90893209e-01
4.17424411e-01 -4.73527819e-01 -6.64610028e-01 7.23798871e-01
-2.33799051e-02 8.88720751e-01 1.20274127e+00 -1.12427998e+00
-9.00597453e-01 -1.97396621e-01 1.10744104e-01 4.58262503e-01
-5.38106263e-01 -2.49024168e-01 -6.95984423e-01 -7.44509161e-01
-3.93341690e-01 -6.92670584e-01 3.29389066e-01 -6.91384077e-02
-1.33336395e-01 -3.54119986e-02 7.96459854e-01 -6.72789752e-01
8.53528798e-01 -2.35026646e+00 4.25005347e-01 6.68941513e-02
1.45798638e-01 4.16677624e-01 -5.76267958e-01 3.21536690e-01
-3.15086722e-01 -4.30040866e-01 -5.71461692e-02 -2.90413439e-01
-2.17229396e-01 1.72416523e-01 -2.23316193e-01 2.35264912e-01
5.57034314e-01 6.83840275e-01 -1.05263567e+00 -3.20019454e-01
9.30251181e-02 5.23318827e-01 -5.15923083e-01 5.65599859e-01
-3.42848569e-01 6.58188224e-01 9.99693945e-03 5.68597913e-01
3.39511007e-01 -1.88339964e-01 1.21552557e-01 -3.41669559e-01
2.44075164e-01 1.12232842e-01 -1.20062590e+00 2.14620996e+00
-5.55163920e-01 6.39218211e-01 -6.60820752e-02 -1.28076363e+00
6.48768187e-01 5.25568366e-01 6.27138436e-01 -8.02168548e-01
5.52611873e-02 -1.37278497e-01 -4.82412308e-01 -7.05932736e-01
2.08165273e-01 -7.40853176e-02 -4.92203422e-02 3.42339784e-01
8.76982689e-01 2.00501740e-01 1.49938231e-02 2.69552082e-01
1.24918020e+00 2.05636814e-01 7.80907050e-02 2.61823863e-01
6.75792336e-01 -1.43854031e-02 4.53758717e-01 6.70029819e-01
-1.90094665e-01 6.75498962e-01 3.29218000e-01 -2.22054988e-01
-5.39854765e-01 -1.14422417e+00 2.07568005e-01 1.61183822e+00
1.76131874e-01 -4.96170938e-01 -4.34813470e-01 -9.27491665e-01
7.04321489e-02 4.91852820e-01 -7.22444832e-01 -5.71626723e-01
-4.52714190e-02 -2.81773299e-01 8.86764109e-01 8.28127742e-01
6.40232980e-01 -9.47936893e-01 -4.74768847e-01 -4.29092012e-02
-3.58397007e-01 -1.21925259e+00 -1.28740400e-01 4.89146858e-01
-6.77157164e-01 -1.30167699e+00 -6.78745687e-01 -6.67627871e-01
2.92705238e-01 2.27383479e-01 1.00119770e+00 -4.67788547e-01
-1.27714515e-01 1.03077972e+00 -6.30479991e-01 -1.53699547e-01
-3.63924235e-01 1.63357295e-02 1.15123205e-01 3.93374652e-01
2.14026660e-01 -5.86271644e-01 -3.90513718e-01 3.49950999e-01
-9.68259633e-01 7.13462383e-02 6.28353834e-01 9.75256205e-01
6.11080647e-01 -3.77819054e-02 5.61344206e-01 -5.38208246e-01
2.37803176e-01 -6.52111113e-01 -2.34829098e-01 2.40513742e-01
-1.56847790e-01 2.22735286e-01 6.41660154e-01 -7.92145133e-01
-1.24743116e+00 3.40821862e-01 5.78117259e-02 -9.09134626e-01
-5.82688928e-01 4.59741145e-01 -3.24886560e-01 1.50636569e-01
9.48889673e-01 2.74882108e-01 5.95553853e-02 -5.20136416e-01
6.38691127e-01 6.75889552e-01 1.01871741e+00 -5.62923729e-01
6.59843326e-01 4.39154208e-01 -2.92599708e-01 -8.11742544e-01
-8.04702997e-01 -6.38828039e-01 -6.39562309e-01 -3.34428132e-01
1.10663152e+00 -1.32508171e+00 -7.44503915e-01 7.23570168e-01
-9.25175607e-01 -6.03074491e-01 -5.37834048e-01 6.62357152e-01
-8.52488339e-01 1.33723512e-01 -4.79329735e-01 -4.14202869e-01
-1.05261356e-01 -8.81246030e-01 1.11123490e+00 1.25580460e-01
-9.61500034e-02 -7.13466883e-01 1.91648751e-01 8.09434175e-01
1.19816788e-01 5.06610163e-02 5.32190502e-01 -9.69689012e-01
-2.97826797e-01 1.18826754e-01 -2.97824293e-01 7.52999663e-01
1.01717785e-01 -3.45747858e-01 -1.34487104e+00 -3.35176468e-01
-5.16822815e-01 -1.06331551e+00 1.06353295e+00 -5.27202524e-02
1.04027259e+00 -2.11352393e-01 -5.98257743e-02 6.34964347e-01
9.76917922e-01 9.28793754e-03 4.22801614e-01 3.34560603e-01
7.35358953e-01 4.50806409e-01 6.37843430e-01 6.12236679e-01
4.87640500e-01 7.96388566e-01 5.22976696e-01 5.47649376e-02
-3.71843249e-01 -3.38716656e-01 6.61625206e-01 7.39595175e-01
-1.30488023e-01 3.46226431e-02 -8.26913714e-01 5.29855192e-01
-1.91397846e+00 -1.01326287e+00 2.34492332e-01 2.06599832e+00
1.22173882e+00 5.41083366e-02 6.40368879e-01 2.92396337e-01
5.20257711e-01 -1.11918360e-01 -5.70188105e-01 4.69443239e-02
-1.07765153e-01 2.46828288e-01 2.36589491e-01 1.76796570e-01
-1.47216320e+00 9.36263680e-01 5.36040115e+00 9.33918297e-01
-1.26865733e+00 2.29138792e-01 1.72798350e-01 -3.50906223e-01
1.52809590e-01 -3.83311421e-01 -5.69303453e-01 3.12020928e-01
1.12966561e+00 1.00397974e-01 3.33990782e-01 7.10955083e-01
-7.04496056e-02 -1.20303541e-01 -1.31319320e+00 1.47068226e+00
2.22095847e-01 -1.20857739e+00 5.90163283e-02 -5.11766851e-01
6.33375466e-01 -1.39230311e-01 8.01564753e-02 5.86488903e-01
1.08832054e-01 -9.63994682e-01 6.68915570e-01 6.93999827e-01
9.29212630e-01 -8.60640705e-01 5.51875651e-01 2.39015609e-01
-1.08051169e+00 -2.24316418e-01 1.22572668e-02 -2.14738790e-02
-3.03968731e-02 2.08893731e-01 -9.80018973e-01 6.92423284e-01
1.00774086e+00 9.81254458e-01 -6.07701063e-01 9.30776000e-01
-2.23098427e-01 7.48388886e-01 -1.33240148e-01 5.98613799e-01
4.04009484e-02 5.13718903e-01 4.02777165e-01 1.41127491e+00
-4.94197495e-02 -5.02534136e-02 1.77269101e-01 3.88567716e-01
-1.79204270e-01 -4.24940065e-02 -4.88852471e-01 -8.84944275e-02
3.13748389e-01 9.81951594e-01 -3.21328580e-01 -4.53964233e-01
-3.99886787e-01 1.25568867e+00 3.78772974e-01 4.93786573e-01
-9.01613653e-01 -3.05946231e-01 7.15190351e-01 -7.07608089e-02
3.87243658e-01 2.31269803e-02 2.28893042e-01 -1.29532576e+00
-2.00703785e-01 -1.10806513e+00 8.21528018e-01 -8.18196833e-01
-1.28518319e+00 5.18665373e-01 1.56299531e-01 -1.45051086e+00
-4.26553696e-01 -4.41373110e-01 -1.67367920e-01 5.63130975e-01
-1.57529020e+00 -1.15841579e+00 -4.80253488e-01 1.27789962e+00
5.39345980e-01 -5.60610712e-01 9.55575466e-01 5.28312802e-01
-4.59428817e-01 9.09294367e-01 -5.48559837e-02 2.53740400e-01
1.10701787e+00 -1.15430868e+00 -2.53991008e-01 5.33653021e-01
2.58128315e-01 1.11451082e-01 3.98189068e-01 -2.82413781e-01
-1.51627111e+00 -1.40584981e+00 3.02089453e-01 -3.54690224e-01
6.09141052e-01 -3.00226718e-01 -9.41714406e-01 4.76348251e-01
1.54109940e-01 2.59716332e-01 8.43113720e-01 3.77507843e-02
-8.65036190e-01 -4.35485423e-01 -8.83419812e-01 2.91951686e-01
1.12402439e+00 -9.32167530e-01 -7.46681154e-01 1.64437458e-01
7.91484833e-01 -4.04947072e-01 -9.47564304e-01 4.28134412e-01
4.68839198e-01 -7.77836382e-01 1.02650297e+00 -1.10482526e+00
5.82512498e-01 -2.55150884e-01 -3.04476529e-01 -1.33590257e+00
-7.56612569e-02 -6.59864366e-01 -5.27914464e-01 1.40703857e+00
2.53950208e-01 -1.74670175e-01 6.26434803e-01 8.97780955e-02
-7.08124489e-02 -3.24819952e-01 -9.31751192e-01 -9.75235164e-01
-2.45113268e-01 -8.81060004e-01 1.49121046e-01 1.11205685e+00
1.87446401e-01 6.66192055e-01 -6.13046825e-01 1.15498252e-01
4.38671529e-01 -1.34382024e-01 9.43005860e-01 -9.99445617e-01
-5.90078950e-01 -1.27056822e-01 -6.68650031e-01 -1.06258619e+00
3.06766242e-01 -9.40311253e-01 1.90409943e-02 -1.03133035e+00
1.71890661e-01 -9.36611556e-03 -6.07515514e-01 8.70359361e-01
1.88756399e-02 4.32303816e-01 3.35420877e-01 6.80766581e-03
-1.10317731e+00 7.03458607e-01 9.88698542e-01 -3.02395463e-01
-3.76128495e-01 -6.69211373e-02 -5.32307565e-01 5.17828703e-01
5.67386210e-01 -2.85368979e-01 -7.75663495e-01 -4.24711585e-01
-1.17126461e-02 2.46175215e-01 6.08027041e-01 -1.13610768e+00
1.80523023e-01 -3.61367501e-02 3.77559096e-01 -3.64814460e-01
5.96776545e-01 -1.00552809e+00 -3.71810980e-02 6.67175278e-02
-7.21297085e-01 -4.17545527e-01 5.18455207e-01 8.13966632e-01
-5.30560791e-01 2.10884556e-01 7.49627113e-01 5.16653247e-02
-1.17415547e+00 -1.32295059e-03 -3.99123758e-01 3.52195144e-01
1.14733326e+00 -6.74323142e-02 -2.76504368e-01 -5.82529604e-01
-1.23706675e+00 3.16848993e-01 -7.51573741e-02 6.88861012e-01
7.71416545e-01 -1.56457734e+00 -6.22601569e-01 1.97248399e-01
4.45245236e-01 -1.78799063e-01 5.49374044e-01 8.78661156e-01
-8.91972259e-02 2.59151191e-01 -5.39391041e-01 -8.03650200e-01
-1.39503574e+00 6.01183772e-01 1.30915985e-01 -7.25822225e-02
-3.89121294e-01 1.12854874e+00 1.16992526e-01 -4.17791039e-01
8.28273118e-01 -1.07950233e-01 -2.87413567e-01 4.48468536e-01
7.49396205e-01 4.53398436e-01 7.39415362e-02 -7.16149569e-01
-5.14721751e-01 2.54088432e-01 6.54118583e-02 -2.30830789e-01
1.41842258e+00 -1.01450138e-01 4.11592394e-01 6.13291860e-01
1.38999701e+00 -5.21297932e-01 -1.51821172e+00 -5.42538881e-01
-2.17386097e-01 -1.97197929e-01 -2.17723288e-02 -1.08120298e+00
-1.22106326e+00 9.29820240e-01 8.12828064e-01 -1.12748928e-01
1.60814261e+00 1.06966823e-01 5.44485390e-01 3.91187489e-01
-2.77834088e-02 -1.15113902e+00 6.11841381e-01 5.54927766e-01
9.91780996e-01 -1.38302803e+00 -2.95597821e-01 -1.22783728e-01
-1.01525259e+00 1.12680793e+00 8.40486825e-01 2.94638157e-01
4.84242320e-01 9.63002536e-03 1.40933439e-01 -1.20315135e-01
-9.77619708e-01 -4.69496638e-01 6.31383419e-01 8.61642897e-01
7.73163885e-02 -3.35489541e-01 3.21061730e-01 9.35794413e-01
2.68974662e-01 2.16092214e-01 2.08581805e-01 1.07776129e+00
-1.22129746e-01 -8.60781848e-01 -3.85276914e-01 1.94773331e-01
-2.69952923e-01 4.05039191e-02 -4.09495592e-01 7.20580339e-01
1.56805977e-01 9.26938951e-01 1.76218431e-02 -7.77232647e-01
4.96781737e-01 2.70198673e-01 5.20508468e-01 -5.98906815e-01
-5.19794106e-01 4.18822616e-02 2.68911034e-01 -8.14112246e-01
-7.89543390e-01 -4.68738854e-01 -1.10563827e+00 9.78868827e-02
-3.10252048e-02 2.41650105e-03 2.75626421e-01 1.01303208e+00
5.25915384e-01 6.14620745e-01 5.58472812e-01 -9.09717500e-01
-5.01860380e-01 -7.33137250e-01 -4.59284514e-01 5.72436988e-01
4.61275607e-01 -8.49358916e-01 -2.09021434e-01 5.03783941e-01] | [9.720733642578125, 1.048330545425415] |
6f2cf0d1-8976-4730-8fdb-917fc129e5c7 | self-organization-map-based-texture-feature | 1408.4143 | null | http://arxiv.org/abs/1408.4143v1 | http://arxiv.org/pdf/1408.4143v1.pdf | Self Organization Map based Texture Feature Extraction for Efficient Medical Image Categorization | Texture is one of the most important properties of visual surface that helps
in discriminating one object from another or an object from background. The
self-organizing map (SOM) is an excellent tool in exploratory phase of data
mining. It projects its input space on prototypes of a low-dimensional regular
grid that can be effectively utilized to visualize and explore properties of
the data. This paper proposes an enhancement extraction method for accurate
extracting features for efficient image representation it based on SOM neural
network. In this approach, we apply three different partitioning approaches as
a region of interested (ROI) selection methods for extracting different
accurate textural features from medical image as a primary step of our
extraction method. Fisherfaces feature selection is used, for selecting
discriminated features form extracted textural features. Experimental result
showed the high accuracy of medical image categorization with our proposed
extraction method. Experiments held on Mammographic Image Analysis Society
(MIAS) dataset. | ['Mohammed M. Abdelsamea', 'Marghny H. Mohamed'] | 2014-07-14 | null | null | null | null | ['image-categorization'] | ['computer-vision'] | [ 2.61412740e-01 -9.50248837e-02 -2.60111243e-01 -5.11223733e-01
2.60224212e-02 -2.83918619e-01 4.86415923e-01 7.31121480e-01
-3.68271291e-01 3.40854019e-01 4.33915198e-01 -9.67966095e-02
-7.12706625e-01 -1.02551234e+00 2.09135208e-02 -9.08386707e-01
-3.23500007e-01 6.46759510e-01 5.44823825e-01 -6.45532608e-02
8.68983686e-01 8.76807690e-01 -2.26601529e+00 8.77317488e-01
5.31963348e-01 1.03657734e+00 4.54386175e-01 6.73423946e-01
-6.19558215e-01 9.90137875e-01 -3.69694322e-01 7.53625393e-01
2.46065572e-01 -2.65421748e-01 -8.90226841e-01 3.89622003e-01
-1.99325442e-01 1.16534986e-01 3.24065924e-01 9.87031460e-01
2.68779159e-01 1.41333610e-01 1.51742709e+00 -1.00596380e+00
-4.57689166e-01 1.36173457e-01 -8.15437376e-01 7.50955880e-01
-1.01394281e-01 -6.17742002e-01 1.14516735e-01 -9.99116242e-01
7.51200438e-01 1.08968401e+00 2.45303467e-01 5.60943224e-02
-9.92570817e-01 -1.68124318e-01 -7.01665640e-01 5.96862018e-01
-1.24735761e+00 -3.22438210e-01 8.36862206e-01 -7.15841353e-01
8.64462852e-01 8.50219548e-01 5.57929337e-01 1.20293893e-01
7.37116933e-01 4.65379804e-01 1.64299715e+00 -7.58655667e-01
2.83897996e-01 6.66799188e-01 7.33758450e-01 6.09076500e-01
2.01621756e-01 -7.99338445e-02 -4.34752405e-01 -2.57899046e-01
4.84830081e-01 3.67450476e-01 3.40188712e-01 -2.33173564e-01
-7.53222585e-01 7.97887444e-01 2.55661309e-01 8.73165548e-01
-5.72079241e-01 -5.56878686e-01 3.64435405e-01 2.72167921e-01
1.83684736e-01 1.29413396e-01 7.69004226e-02 2.17017338e-01
-9.79208052e-01 -1.88209176e-01 2.18215525e-01 4.92355436e-01
5.33838212e-01 -2.70970434e-01 -1.26799300e-01 1.02220666e+00
4.55090046e-01 2.39775524e-01 1.07287228e+00 -3.83586317e-01
-6.18519038e-02 1.31341553e+00 -1.39760450e-01 -1.66755879e+00
-7.01393902e-01 5.60807530e-03 -7.22784817e-01 6.88335419e-01
-1.20073296e-01 4.05847937e-01 -1.28061700e+00 4.56215948e-01
5.15706062e-01 -6.87390625e-01 5.18790595e-02 6.54530227e-01
1.12956142e+00 8.42675567e-01 5.44848628e-02 -1.16016693e-01
1.77976143e+00 -4.75152314e-01 -6.25696123e-01 2.96818793e-01
-3.31234373e-02 -8.87920439e-01 6.29185140e-01 5.69431841e-01
-5.97254515e-01 -6.66597605e-01 -1.34745193e+00 1.95096999e-01
-7.61413753e-01 3.75179350e-01 6.60694540e-01 5.00530660e-01
-8.94444942e-01 5.77361047e-01 -9.68691468e-01 -7.15697646e-01
2.68094271e-01 5.71469367e-01 -8.01098824e-01 4.37569529e-01
-3.92577469e-01 7.39523709e-01 7.12442040e-01 -6.40290156e-02
-2.12742686e-01 1.72377720e-01 -5.72488308e-01 3.20198275e-02
-8.54940712e-02 -4.09284271e-02 3.97165686e-01 -1.05256546e+00
-9.52621400e-01 1.07430065e+00 -2.85598516e-01 -3.31306964e-01
1.32826731e-01 5.10758042e-01 -4.72206414e-01 5.73894382e-01
2.27354199e-01 4.09799129e-01 9.45754349e-01 -1.03725147e+00
-7.50923276e-01 -8.93972754e-01 -8.95748198e-01 3.54527086e-01
-6.51365042e-01 2.06753463e-01 1.64159819e-01 -5.97329497e-01
9.94595051e-01 -5.64579427e-01 3.55866179e-03 -5.25333285e-01
-3.60104084e-01 -3.09465557e-01 1.26131189e+00 -7.62328625e-01
1.24433970e+00 -2.27261424e+00 -2.42767379e-01 9.57231522e-01
2.98987478e-01 -1.40605256e-01 7.19066679e-01 4.96271729e-01
-8.26075375e-02 2.92581111e-01 -7.51068667e-02 5.75679421e-01
-5.57968915e-01 -8.16365480e-02 2.22735256e-01 2.44103536e-01
2.05626875e-01 1.09716617e-01 -3.00420374e-01 -1.23808718e+00
2.75563002e-01 3.61203790e-01 1.39712825e-01 -1.32981971e-01
5.76613784e-01 2.65458286e-01 -7.69831061e-01 8.98356140e-01
6.09367788e-01 -2.10130541e-03 -1.67350296e-03 -3.53974819e-01
-3.37001622e-01 -3.58704269e-01 -1.27508175e+00 7.47515738e-01
1.47437736e-01 8.69962454e-01 -4.68542963e-01 -1.11229134e+00
1.38836873e+00 2.34664127e-01 7.19053149e-01 -7.40207851e-01
3.94658238e-01 9.11612809e-02 2.62874980e-02 -1.02909923e+00
3.58720094e-01 -1.04982376e-01 4.91924107e-01 4.67946857e-01
9.30685103e-02 7.05991328e-01 1.79698959e-01 -2.29922667e-01
6.66399658e-01 -2.46446207e-01 6.21289611e-01 -9.48559344e-01
5.91405213e-01 4.69710082e-01 3.82087737e-01 4.63025659e-01
-7.54193291e-02 3.64042073e-01 3.34516257e-01 -7.65517116e-01
-1.10126913e+00 -7.74932384e-01 -9.23606396e-01 9.04654026e-01
-1.51941450e-02 7.89917633e-02 -6.48482144e-01 -4.06331122e-01
1.04775079e-01 1.71753034e-01 -1.12556648e+00 3.69168341e-01
-3.98893923e-01 -9.98588085e-01 -2.45333649e-02 2.83000171e-01
7.85277903e-01 -1.31810617e+00 -1.13661790e+00 5.11870086e-02
1.79663137e-01 -6.00174032e-02 3.91858280e-01 3.83499891e-01
-1.17187858e+00 -1.10160553e+00 -5.10862768e-01 -1.20431316e+00
1.25142515e+00 2.84115106e-01 6.09269083e-01 1.09934345e-01
-8.13871145e-01 -3.19461524e-02 -4.78047431e-01 -1.01150417e+00
-3.93902212e-01 -1.25329629e-01 -1.55491710e-01 8.46068040e-02
8.54151547e-01 -4.04012948e-01 -7.08689034e-01 3.97251487e-01
-8.65678608e-01 7.52630085e-02 5.75570464e-01 6.76656842e-01
7.56351054e-01 8.97912085e-01 3.24595690e-01 -1.12225676e+00
6.31508827e-01 -5.40753782e-01 -2.71678627e-01 1.03139363e-01
-5.73229909e-01 2.24752784e-01 4.27690268e-01 4.49463874e-02
-9.19513166e-01 -8.26107115e-02 4.54727203e-01 2.19576731e-01
-4.89934236e-01 4.98236358e-01 1.41644657e-01 -7.36126602e-02
1.09078944e+00 5.62549710e-01 2.11602703e-01 -5.15199602e-01
-5.44997811e-01 1.36592543e+00 2.67151684e-01 -1.94201946e-01
2.60053009e-01 7.39875019e-01 2.41128415e-01 -1.14329183e+00
7.23135173e-02 -9.34808791e-01 -8.08145344e-01 -3.73279512e-01
1.03821087e+00 -9.44308937e-02 -6.14571929e-01 7.29438961e-02
-4.61916775e-01 4.38946456e-01 1.95001900e-01 4.83486354e-01
-3.09656501e-01 8.02958533e-02 -2.27631077e-01 -1.18113887e+00
-6.33423686e-01 -8.25155437e-01 5.29791176e-01 3.59515071e-01
-1.40898734e-01 -6.95335448e-01 -6.55887052e-02 1.88896760e-01
4.18716103e-01 7.43230581e-01 1.16373610e+00 -6.62855446e-01
5.01188897e-02 -3.38023245e-01 -8.76808390e-02 4.34219427e-02
5.47462344e-01 7.84616694e-02 -8.42335343e-01 6.44676611e-02
4.09669966e-01 3.30786854e-01 9.88453269e-01 3.76966834e-01
1.10378289e+00 -5.75468898e-01 -6.14367485e-01 2.18225196e-01
1.78895891e+00 9.26492929e-01 6.55564129e-01 9.09276426e-01
3.28996181e-01 8.05372059e-01 9.81382132e-01 1.83732659e-01
-2.47550085e-01 1.59889638e-01 -4.99195196e-02 -2.05983892e-01
2.25196511e-01 2.63055682e-01 -2.37669691e-01 5.97873151e-01
-4.74073440e-01 2.81420976e-01 -1.29823124e+00 4.74602968e-01
-1.65401709e+00 -9.83487487e-01 -1.39806077e-01 2.07900000e+00
5.09338558e-01 1.40640691e-01 4.53163981e-01 7.61794984e-01
8.45472991e-01 -3.70607316e-01 -9.33367088e-02 -6.06888533e-01
-1.24754356e-02 2.16806710e-01 6.84503794e-01 2.82719463e-01
-1.34378266e+00 4.35643852e-01 5.28140259e+00 6.71901286e-01
-1.41466630e+00 -1.08958013e-01 7.88448632e-01 3.42912167e-01
2.10414767e-01 -1.69885829e-01 -4.75303531e-01 5.85154235e-01
5.21577358e-01 -1.14132345e-01 -4.81734388e-02 9.28843319e-01
3.56749475e-01 -6.87032223e-01 -5.01433551e-01 9.68793333e-01
1.18032917e-02 -1.21187818e+00 3.59304070e-01 1.40343949e-01
4.77147430e-01 -4.26398426e-01 7.29409978e-02 -4.20552939e-01
-3.30776751e-01 -1.15083969e+00 3.18200618e-01 8.03143024e-01
4.30536777e-01 -1.07627940e+00 9.35040236e-01 1.83684662e-01
-1.02509511e+00 -2.81533092e-01 -8.00425708e-01 1.30060658e-01
-6.17453992e-01 1.60090297e-01 -1.32441950e+00 1.68444052e-01
1.13033867e+00 3.26927900e-01 -7.76362598e-01 1.16095674e+00
6.69830263e-01 5.56381166e-01 -2.04962865e-01 -3.68684530e-01
1.78774416e-01 -1.23407774e-01 5.75367928e-01 1.30347705e+00
2.23895967e-01 1.28030792e-01 -1.59676209e-01 4.11842674e-01
6.86564326e-01 9.47973013e-01 -8.24096024e-01 2.53959037e-02
5.17917931e-01 1.23711586e+00 -1.65765178e+00 -4.84130055e-01
2.53926277e-01 3.92941862e-01 -2.40402341e-01 -7.25206435e-02
-1.22840822e-01 -9.33527708e-01 -4.47613776e-01 6.87147617e-01
4.56011780e-02 -3.59581150e-02 -6.24543488e-01 -4.24006402e-01
-5.76242767e-02 -6.91380084e-01 6.55810416e-01 -4.84471649e-01
-8.75694096e-01 8.03989410e-01 8.81897956e-02 -1.59034908e+00
1.34192675e-01 -7.06034482e-01 -4.92943436e-01 8.10721338e-01
-8.35807681e-01 -1.09712410e+00 -5.16187847e-01 4.28070456e-01
6.81951046e-01 -8.35964918e-01 8.88846815e-01 -1.54573843e-01
-6.48651719e-02 -8.04895610e-02 5.10516703e-01 1.82232738e-01
4.52783465e-01 -1.47636425e+00 -5.11288226e-01 5.37788332e-01
-1.88977420e-02 8.02840292e-01 6.89698339e-01 -8.58098447e-01
-8.70359719e-01 -6.48212373e-01 7.01327205e-01 -2.28237614e-01
9.65377018e-02 2.54989173e-02 -7.37052381e-01 1.96683899e-01
9.32234898e-02 -2.91300863e-01 1.11293030e+00 -1.83270648e-01
4.66578662e-01 -1.28193617e-01 -1.41077566e+00 3.37134600e-01
1.34541139e-01 4.38719578e-02 -7.40132213e-01 1.30099818e-01
-3.81646276e-01 4.13567685e-02 -1.02178049e+00 2.61650354e-01
8.22350860e-01 -1.33857751e+00 7.61674643e-01 -7.34784722e-01
3.92515212e-01 -5.55413008e-01 -9.71409231e-02 -6.56812310e-01
-6.64955139e-01 9.57222432e-02 4.00787115e-01 1.00025868e+00
3.20409626e-01 -5.14841557e-01 9.77183342e-01 2.79802263e-01
2.99893379e-01 -7.47686148e-01 -4.58341509e-01 -3.81060272e-01
-5.15734315e-01 2.10441992e-01 3.48934233e-01 1.20212805e+00
2.29775190e-01 2.10156411e-01 1.01026960e-01 -1.28497094e-01
8.28578591e-01 2.84255669e-03 3.30854774e-01 -1.65601683e+00
-1.60098493e-01 -3.15740794e-01 -1.34803796e+00 3.97737026e-01
-6.60972297e-01 -9.14610803e-01 -3.67724866e-01 -1.81373942e+00
5.80188513e-01 -5.02261341e-01 -6.79928064e-01 4.88331705e-01
8.34178403e-02 3.60499978e-01 -1.47037283e-02 7.44432032e-01
-3.46835400e-03 -2.29371205e-01 9.00323689e-01 -1.84823245e-01
-5.19837201e-01 3.97663051e-03 -5.69748044e-01 6.84870958e-01
9.33148503e-01 -6.94493890e-01 -5.23518562e-01 1.25852540e-01
-8.71097296e-02 -7.68740848e-02 5.53645790e-02 -1.14774573e+00
1.62218779e-01 -2.93546796e-01 1.13982725e+00 -8.01764250e-01
-1.99086845e-01 -8.99646223e-01 2.73261636e-01 4.87955987e-01
-3.12708527e-01 -2.16253474e-02 3.66336226e-01 3.18366230e-01
-4.42172021e-01 -4.55386221e-01 7.48104334e-01 -3.70026469e-01
-8.52257371e-01 -3.61355305e-01 -5.97712994e-01 -7.22482622e-01
1.11752784e+00 -1.02788627e+00 -9.65998322e-02 1.80511221e-01
-1.18435466e+00 -1.42375067e-01 3.49602878e-01 1.95489213e-01
7.40711510e-01 -1.42421401e+00 -6.24722481e-01 2.75582224e-01
2.71652877e-01 -5.21995008e-01 2.81191856e-01 9.30496991e-01
-1.31796348e+00 3.52364957e-01 -1.17558897e+00 -7.25915790e-01
-1.93878174e+00 5.25610328e-01 1.24164037e-01 -5.67991287e-02
-6.92425728e-01 2.85774738e-01 5.62013173e-03 1.93725854e-01
-4.47928831e-02 -2.53373682e-02 -1.49261975e+00 2.12932423e-01
7.43114769e-01 7.55293071e-01 3.11036289e-01 -7.91388273e-01
-3.41652304e-01 7.44683266e-01 -1.58770323e-01 -1.71695739e-01
1.41154408e+00 4.45077717e-02 -5.72878122e-01 8.42202783e-01
1.12506926e+00 1.79807339e-02 -3.44175398e-01 6.49902150e-02
5.49188256e-01 -4.98742819e-01 2.38498628e-01 -6.73838317e-01
-5.52602649e-01 7.59882212e-01 1.34856558e+00 6.04347289e-01
1.19698000e+00 -3.50083768e-01 6.46721795e-02 5.37107110e-01
2.11316094e-01 -1.54409862e+00 -2.95564175e-01 -2.28659183e-01
1.01763511e+00 -1.33472264e+00 1.71987966e-01 -4.04607713e-01
-6.24455333e-01 1.65057778e+00 2.03175947e-01 -3.15212816e-01
1.02996409e+00 3.16895753e-01 2.91917235e-01 -6.40467703e-01
-2.68949330e-01 9.28115249e-02 5.64026654e-01 5.63769579e-01
5.57838261e-01 1.46862611e-01 -7.71928310e-01 4.78863001e-01
-2.97844589e-01 -6.39327541e-02 1.63802981e-01 1.50452626e+00
-1.22651768e+00 -7.12298632e-01 -8.50637138e-01 1.12899601e+00
-7.40224898e-01 2.97661275e-01 -5.34606993e-01 6.80980742e-01
1.34547293e-01 8.88550222e-01 2.45906055e-01 -4.62258518e-01
1.18836146e-02 -4.87751365e-02 2.44524017e-01 -4.12393868e-01
-4.91157949e-01 2.65940875e-01 -1.26915470e-01 -1.65901780e-01
-3.69452298e-01 -5.80721438e-01 -1.41450953e+00 1.21794090e-01
-7.56670237e-02 5.55368364e-01 1.05782819e+00 5.52686870e-01
1.62474811e-01 3.67774576e-01 7.48113811e-01 -5.86019814e-01
2.00193435e-01 -1.11728525e+00 -8.97489965e-01 4.23437059e-01
1.80516750e-01 -9.94475126e-01 1.54598095e-02 4.45518196e-01] | [14.988771438598633, -2.674238681793213] |
db378c1c-8d24-4ead-9e78-ca6f09b273cb | the-ebible-corpus-data-and-model-benchmarks | 2304.09919 | null | https://arxiv.org/abs/2304.09919v1 | https://arxiv.org/pdf/2304.09919v1.pdf | The eBible Corpus: Data and Model Benchmarks for Bible Translation for Low-Resource Languages | Efficiently and accurately translating a corpus into a low-resource language remains a challenge, regardless of the strategies employed, whether manual, automated, or a combination of the two. Many Christian organizations are dedicated to the task of translating the Holy Bible into languages that lack a modern translation. Bible translation (BT) work is currently underway for over 3000 extremely low resource languages. We introduce the eBible corpus: a dataset containing 1009 translations of portions of the Bible with data in 833 different languages across 75 language families. In addition to a BT benchmarking dataset, we introduce model performance benchmarks built on the No Language Left Behind (NLLB) neural machine translation (NMT) models. Finally, we describe several problems specific to the domain of BT and consider how the established data and model benchmarks might be used for future translation efforts. For a BT task trained with NLLB, Austronesian and Trans-New Guinea language families achieve 35.1 and 31.6 BLEU scores respectively, which spurs future innovations for NMT for low-resource languages in Papua New Guinea. | ['Marcus Schwarting', 'Jonathan Robie', 'Joel Mathew', 'Michael Martin', 'Colin Leong', 'Taeho Jang', 'Ulf Hermjakob', 'Damien Daspit', 'David Baines', 'Vesa Akerman'] | 2023-04-19 | null | null | null | null | ['nmt'] | ['computer-code'] | [ 1.65643513e-01 -1.14957444e-01 -4.56858307e-01 -4.67684925e-01
-1.39976788e+00 -9.49976802e-01 8.23072851e-01 -2.38429904e-01
-5.40738881e-01 1.33226502e+00 3.91562343e-01 -9.01539743e-01
3.78819972e-01 -7.45301008e-01 -6.61660314e-01 -4.53266621e-01
4.46825802e-01 1.41287053e+00 -3.91166210e-01 -7.68540621e-01
1.43433750e-01 1.74138516e-01 -5.78642786e-01 4.69361931e-01
9.26502645e-01 2.51272559e-01 -1.41110616e-02 7.54517376e-01
-1.59372047e-01 4.30274725e-01 -5.68260670e-01 -8.29757154e-01
4.55658317e-01 -7.76608706e-01 -1.25383162e+00 -6.18998170e-01
5.88506103e-01 -1.19323708e-01 1.45031378e-01 5.71481705e-01
6.52583361e-01 -3.26207101e-01 6.66654587e-01 -7.05486596e-01
-9.50943291e-01 1.00510931e+00 -1.53946400e-01 2.35423192e-01
1.41251266e-01 -1.03828339e-02 1.04784727e+00 -1.11837363e+00
8.16956758e-01 1.23964000e+00 8.75586867e-01 6.36976302e-01
-1.25375068e+00 -6.36510074e-01 -7.30356216e-01 -2.67396923e-02
-1.13174558e+00 -8.57936680e-01 1.59585491e-01 -3.73325765e-01
1.40832520e+00 3.90338808e-01 5.70636749e-01 1.11094260e+00
4.51422423e-01 5.27534306e-01 1.35737300e+00 -7.78534889e-01
-2.22221717e-01 1.06125623e-01 -3.91325951e-01 4.70755219e-01
1.53381109e-01 -1.22987824e-02 -8.19366515e-01 -2.98850507e-01
4.27872598e-01 -7.57740557e-01 1.26263097e-01 4.27056760e-01
-1.71917701e+00 8.28625083e-01 1.19473383e-01 6.06941581e-01
-1.27258971e-01 8.08248073e-02 5.05646765e-01 7.49725938e-01
7.82857060e-01 5.90927720e-01 -7.45677948e-01 -4.86908525e-01
-1.33044958e+00 2.88412094e-01 9.98197377e-01 1.13450408e+00
7.71173835e-01 2.16195896e-01 -4.93377335e-02 1.05252326e+00
-7.57030994e-02 8.29570174e-01 3.02480161e-01 -7.23777890e-01
1.06911325e+00 2.39237368e-01 1.62270829e-01 -5.28683782e-01
-2.40534291e-01 -2.05093294e-01 -7.07323968e-01 -4.43500996e-01
6.46581471e-01 -2.43826613e-01 -7.99555182e-01 1.45317364e+00
6.93018660e-02 -8.71646523e-01 2.17416808e-01 7.44892538e-01
6.59319222e-01 8.87117624e-01 -1.84678406e-01 -2.02230871e-01
1.08722222e+00 -1.11115837e+00 -4.00936276e-01 -4.05627698e-01
8.15328360e-01 -1.57715261e+00 1.08644724e+00 7.80243650e-02
-1.49476373e+00 -2.64353007e-01 -7.73091674e-01 -4.78467643e-01
-5.90625107e-01 2.48785853e-01 5.13967037e-01 6.28771484e-01
-1.49394381e+00 5.00964284e-01 -8.51948380e-01 -8.38348985e-01
4.12871502e-02 5.79940319e-01 -3.56695563e-01 -2.09757239e-02
-1.23006058e+00 1.48186624e+00 4.85386163e-01 1.25753894e-01
-7.14028776e-01 -4.28475440e-01 -4.88390923e-01 -3.43952745e-01
-4.38121289e-01 -6.66554928e-01 1.33320594e+00 -1.11806655e+00
-1.44447899e+00 1.24880135e+00 -2.17501536e-01 -3.19816589e-01
7.21410990e-01 -6.42132536e-02 -4.52726126e-01 -2.68965602e-01
4.97566611e-01 8.36643696e-01 2.28228301e-01 -6.72557652e-01
-6.84599698e-01 -1.97077110e-01 -3.51510435e-01 1.16797075e-01
-2.59516925e-01 6.85366929e-01 -1.60374135e-01 -6.95044637e-01
1.63614638e-02 -1.19404900e+00 4.98100109e-02 -4.88905758e-01
-2.97530115e-01 -6.00064993e-02 2.29838744e-01 -1.37847400e+00
1.06028128e+00 -1.40731883e+00 2.60174990e-01 -1.38510540e-01
-3.74322742e-01 1.90384150e-01 -3.27096194e-01 9.61373985e-01
3.43396723e-01 3.76362652e-01 -3.34256440e-01 -2.30932638e-01
2.94239279e-02 3.13041240e-01 -2.83247173e-01 3.96660417e-01
2.01750278e-01 1.26702738e+00 -8.37008238e-01 -5.73357046e-01
-3.06277871e-01 3.19733977e-01 -2.59585977e-01 -1.03659935e-01
-2.01332420e-01 6.72111034e-01 -1.37469545e-01 1.01685727e+00
4.13689464e-01 1.57730341e-01 1.78104401e-01 2.63519943e-01
-3.66859257e-01 7.95582235e-01 8.79042819e-02 1.86752117e+00
-5.81361532e-01 7.75880158e-01 -1.03080578e-01 -5.72224081e-01
1.13418865e+00 4.51793611e-01 1.60864711e-01 -9.04428601e-01
-1.31471846e-02 1.22476375e+00 2.84888089e-01 -1.41427174e-01
8.96272004e-01 -4.93556827e-01 -1.97307363e-01 7.63299882e-01
1.80847824e-01 -2.45468289e-01 4.50834274e-01 -2.37013280e-01
9.47470963e-01 4.27104801e-01 2.82999396e-01 -6.73602045e-01
2.75551319e-01 5.85307002e-01 5.04016101e-01 5.43949366e-01
-7.98368901e-02 6.08563125e-01 -7.41584599e-02 -8.89899552e-01
-1.78353798e+00 -9.25810814e-01 -7.39523396e-02 1.33662188e+00
-6.39258504e-01 -2.46480495e-01 -7.26021349e-01 -3.32458347e-01
-4.00542051e-01 7.87274599e-01 -3.14468652e-01 8.01624432e-02
-1.32804906e+00 -9.28039432e-01 1.25139260e+00 1.61627516e-01
5.78646839e-01 -1.05060136e+00 -2.99149394e-01 5.55823743e-01
-8.89674067e-01 -1.00165689e+00 -5.14271021e-01 1.80073618e-03
-9.24175918e-01 -4.15703833e-01 -1.00291920e+00 -1.12545884e+00
2.81543434e-01 -2.19132259e-01 1.59108102e+00 -1.42892495e-01
2.93557137e-01 -2.36141011e-01 -3.02297235e-01 -3.04299891e-01
-1.14277780e+00 8.14090014e-01 1.63574353e-01 -6.45492494e-01
6.36078179e-01 -4.09218311e-01 -1.65893778e-01 3.51446390e-01
-4.05256182e-01 4.76351500e-01 6.00482941e-01 9.05225813e-01
2.66566485e-01 -9.04213965e-01 6.73710227e-01 -6.81804717e-01
5.24759352e-01 -5.06927669e-01 -4.63319749e-01 6.41813695e-01
-4.82760131e-01 -2.06551328e-01 7.48219490e-01 -2.73201048e-01
-9.47862744e-01 -2.31577292e-01 -1.90434039e-01 3.15566301e-01
4.15964216e-01 5.15888155e-01 2.58114457e-01 5.61612770e-02
8.49820733e-01 5.28423905e-01 -3.65024745e-01 -5.42558134e-01
2.66635269e-01 1.04709136e+00 5.30382514e-01 -9.88618851e-01
7.18130410e-01 5.32454140e-02 -1.67250648e-01 -5.79001188e-01
-5.26120722e-01 -1.01344101e-02 -9.16761160e-01 1.15184691e-02
8.19727123e-01 -8.16147387e-01 -2.93669645e-02 1.57503814e-01
-1.44252789e+00 -6.56803608e-01 1.61541745e-01 4.48051691e-01
-8.57699037e-01 -9.82088521e-02 -9.95505750e-01 -4.63893861e-01
-1.05020845e+00 -9.87014055e-01 1.14990079e+00 -1.35212585e-01
-6.52052462e-01 -1.17854142e+00 4.74816203e-01 6.91288471e-01
6.98055089e-01 1.84553310e-01 1.39229417e+00 -6.72201693e-01
-2.89974362e-01 1.22723714e-01 -7.42707402e-02 3.18081379e-01
3.68718743e-01 -1.54585302e-01 -5.08019865e-01 -6.35864139e-01
-1.56746343e-01 -4.86875713e-01 4.43665415e-01 -7.30122030e-02
-4.63270433e-02 -6.62585080e-01 3.24299112e-02 5.13945520e-01
1.31662548e+00 1.39463276e-01 3.46917242e-01 7.35731184e-01
4.99385983e-01 4.65376198e-01 5.58584034e-01 -7.96969384e-02
5.92751384e-01 6.88853145e-01 -3.89732778e-01 -1.99442551e-01
-1.84798062e-01 -3.80916923e-01 7.91833103e-01 1.65451062e+00
-4.71215665e-01 -1.83755577e-01 -1.64855182e+00 9.09513056e-01
-1.52861953e+00 -6.80168092e-01 -2.16471761e-01 2.21887326e+00
1.39280462e+00 -1.94435328e-01 1.03951603e-01 -3.04993063e-01
5.68191230e-01 -2.10781053e-01 -1.06660664e-01 -1.14329374e+00
-4.06190753e-01 5.86003780e-01 5.83271563e-01 6.18858516e-01
-7.16199934e-01 1.50575721e+00 6.90496397e+00 7.60596931e-01
-1.21699297e+00 3.40148777e-01 6.94460213e-01 -1.41698718e-01
-3.26296031e-01 3.20762783e-01 -7.91984737e-01 4.01548773e-01
1.47638738e+00 -3.96581084e-01 1.01790440e+00 1.93236098e-01
3.02124918e-01 4.24113750e-01 -1.28258944e+00 5.71405470e-01
4.24017832e-02 -1.46312320e+00 2.32364610e-01 1.47794738e-01
1.19078481e+00 7.15924859e-01 -8.48740861e-02 4.49567229e-01
4.20966029e-01 -1.22264683e+00 9.56748903e-01 2.56962806e-01
1.18901134e+00 -6.43204749e-01 5.91928601e-01 5.50143600e-01
-7.16355801e-01 3.68589073e-01 -6.53073132e-01 -1.69679776e-01
1.51064157e-01 1.47452876e-01 -1.33002293e+00 6.44624293e-01
6.36859536e-01 5.63247144e-01 -5.75756133e-01 3.98711860e-01
-4.83298488e-02 1.08358991e+00 -4.33746815e-01 -5.89632131e-02
6.14390492e-01 -3.97920579e-01 4.62913483e-01 1.56388259e+00
5.98931372e-01 -3.06976616e-01 -4.85339314e-02 7.68364489e-01
-1.84184477e-01 5.57391465e-01 -5.90467632e-01 -3.67987663e-01
4.04086262e-01 9.96775031e-01 -5.84725857e-01 -3.39645743e-01
-3.73266309e-01 1.04083943e+00 3.35987985e-01 3.16316366e-01
-5.99158645e-01 -9.87226367e-02 3.00308138e-01 9.15434491e-03
-2.25286767e-01 -3.56044710e-01 -4.94938493e-01 -1.18768644e+00
1.56811655e-01 -1.36229479e+00 1.22635588e-01 -6.33907795e-01
-1.20021105e+00 7.55191982e-01 -1.93118066e-01 -1.13642049e+00
-5.73920667e-01 -3.87710094e-01 -3.66320938e-01 1.24606967e+00
-1.24873567e+00 -1.86801434e+00 4.38871831e-01 1.38499901e-01
7.67893493e-01 -5.31511962e-01 1.11578894e+00 5.73017716e-01
-8.09010267e-02 6.89887285e-01 5.18737197e-01 2.56609350e-01
9.41501677e-01 -1.06262827e+00 1.16042233e+00 5.97698569e-01
1.94890469e-01 7.73933232e-01 5.02805710e-01 -7.04789400e-01
-1.32483792e+00 -1.17735171e+00 2.07232523e+00 -7.77147472e-01
6.97746873e-01 -5.36340475e-01 -5.26194155e-01 1.03858018e+00
5.79547107e-01 -7.54406869e-01 7.19994724e-01 2.28494294e-02
-1.98748022e-01 1.46693304e-01 -1.04380250e+00 7.68670201e-01
9.01641011e-01 -5.97043395e-01 -5.23190618e-01 6.62146270e-01
6.39526725e-01 -2.78871238e-01 -1.12898993e+00 3.22099715e-01
8.88984799e-01 -5.06556153e-01 6.78548694e-01 -9.25220013e-01
8.44445884e-01 -4.50457074e-03 -5.00964403e-01 -1.34316170e+00
-6.31469265e-02 -9.87757206e-01 4.86564189e-01 1.42836046e+00
8.65835965e-01 -6.35311604e-01 5.99478066e-01 1.87131613e-01
-1.25262707e-01 -6.14423931e-01 -1.38755858e+00 -8.45338762e-01
1.10225797e+00 -6.68058172e-02 6.85298324e-01 1.09737003e+00
-1.30540147e-01 7.99122512e-01 -6.12463236e-01 -5.65191150e-01
2.30472893e-01 1.61134198e-01 9.17421877e-01 -7.67322123e-01
-2.18209743e-01 -4.61332142e-01 -1.29481703e-02 -7.34795868e-01
5.78107834e-02 -1.40414667e+00 2.16585293e-01 -1.54993188e+00
3.10259312e-01 -5.40385485e-01 1.90835670e-01 7.51035690e-01
1.10276796e-01 6.96639895e-01 2.55038589e-01 6.75675631e-01
9.15953442e-02 2.59694606e-01 1.20640540e+00 -2.86783606e-01
5.47393002e-02 -1.31818727e-01 -4.70180899e-01 4.10002202e-01
1.08476138e+00 -7.63081312e-01 1.07507110e-01 -1.19872880e+00
4.52379435e-01 1.48517787e-01 -2.22135365e-01 -6.53476357e-01
6.83469400e-02 -3.61662984e-01 2.87692517e-01 -5.34792960e-01
2.12549448e-01 -4.41409796e-01 3.78218979e-01 4.46106106e-01
-2.77341276e-01 6.52722299e-01 9.04493034e-02 -3.63970071e-01
-1.23091877e-01 8.02005306e-02 7.88222373e-01 -4.51315314e-01
-1.80909820e-02 2.45875921e-02 -3.98557425e-01 3.02567840e-01
4.22586352e-01 -9.88792628e-02 -5.29004037e-01 -2.57270128e-01
-3.39890897e-01 4.84233387e-02 6.94691777e-01 4.86202538e-01
9.93582383e-02 -1.43680513e+00 -1.57029307e+00 -4.07242253e-02
6.09500781e-02 -4.49378669e-01 -6.83963120e-01 9.05794442e-01
-1.15974760e+00 7.57945538e-01 -4.84200746e-01 -4.84457701e-01
-9.57542777e-01 8.43516923e-03 2.56156743e-01 -4.33838725e-01
-1.90597862e-01 5.24915695e-01 -3.87024492e-01 -1.22034597e+00
-5.07499576e-01 -3.81908417e-02 3.94886971e-01 -2.82558829e-01
1.49656773e-01 4.77524042e-01 3.57372642e-01 -1.09961915e+00
-2.47547716e-01 4.87286448e-01 -2.22868603e-02 -5.98793387e-01
1.21273208e+00 -2.89073512e-02 -6.76935315e-01 5.95642149e-01
1.09107232e+00 5.48810735e-02 -1.92715660e-01 -1.53123155e-01
3.03068399e-01 -1.92092165e-01 -5.57016909e-01 -1.33279943e+00
-4.36489612e-01 9.36441839e-01 2.20220372e-01 -3.89594525e-01
9.43943620e-01 -2.26780638e-01 1.10188782e+00 6.97542906e-01
7.21438885e-01 -1.18611217e+00 -6.71854019e-01 9.59387600e-01
9.41541791e-01 -1.04334116e+00 -1.90244988e-01 2.52061963e-01
-3.69870931e-01 1.21809769e+00 2.18750030e-01 2.20041543e-01
4.59212922e-02 6.76749423e-02 5.29189289e-01 2.59735972e-01
-8.29083562e-01 2.66800433e-01 9.30883139e-02 4.13511097e-01
9.72932637e-01 3.09961110e-01 -9.62494433e-01 1.56785339e-01
-1.08338690e+00 -7.29784891e-02 4.28346515e-01 8.51797819e-01
-2.51900077e-01 -1.53758216e+00 -4.36347544e-01 3.73872221e-01
-7.68491387e-01 -6.34963155e-01 -9.24340129e-01 8.84399354e-01
1.38728738e-01 1.06760705e+00 -1.54504761e-01 -2.93731630e-01
2.28343960e-02 3.16257209e-01 5.80233335e-01 -5.73348641e-01
-1.21407223e+00 1.54681697e-01 5.10006011e-01 5.19708060e-02
-2.35897213e-01 -5.98691940e-01 -9.10866618e-01 -9.05562758e-01
-2.24214301e-01 4.23365593e-01 8.86988699e-01 9.72679317e-01
-5.35192527e-02 -2.96190977e-01 3.21876496e-01 -7.09249139e-01
-5.35809040e-01 -1.32204902e+00 4.69914787e-02 -7.59518966e-02
9.01592448e-02 1.72972322e-01 5.73573224e-02 2.15046689e-01] | [11.559547424316406, 10.396551132202148] |
62582aab-da69-4272-883d-7e47273f602b | fisheyeex-polar-outpainting-for-extending-the | 2206.05844 | null | https://arxiv.org/abs/2206.05844v1 | https://arxiv.org/pdf/2206.05844v1.pdf | FisheyeEX: Polar Outpainting for Extending the FoV of Fisheye Lens | Fisheye lens gains increasing applications in computational photography and assisted driving because of its wide field of view (FoV). However, the fisheye image generally contains invalid black regions induced by its imaging model. In this paper, we present a FisheyeEX method that extends the FoV of the fisheye lens by outpainting the invalid regions, improving the integrity of captured scenes. Compared with the rectangle and undistorted image, there are two challenges for fisheye image outpainting: irregular painting regions and distortion synthesis. Observing the radial symmetry of the fisheye image, we first propose a polar outpainting strategy to extrapolate the coherent semantics from the center to the outside region. Such an outpainting manner considers the distribution pattern of radial distortion and the circle boundary, boosting a more reasonable completion direction. For the distortion synthesis, we propose a spiral distortion-aware perception module, in which the learning path keeps consistent with the distortion prior of the fisheye image. Subsequently, a scene revision module rearranges the generated pixels with the estimated distortion to match the fisheye image, thus extending the FoV. In the experiment, we evaluate the proposed FisheyeEX on three popular outdoor datasets: Cityscapes, BDD100k, and KITTI, and one real-world fisheye image dataset. The results demonstrate that our approach significantly outperforms the state-of-the-art methods, gaining around 27% more content beyond the original fisheye image. | ['Yao Zhao', 'Yunchao Wei', 'Chunyu Lin', 'Kang Liao'] | 2022-06-12 | null | null | null | null | ['image-outpainting'] | ['computer-vision'] | [ 2.25938603e-01 5.53979464e-02 1.93116844e-01 -3.56114209e-01
-7.03790411e-02 -4.63794827e-01 4.50410903e-01 -7.00398147e-01
-2.18072310e-01 5.80150723e-01 1.03898667e-01 -6.91432878e-02
1.20516464e-01 -8.37646961e-01 -9.98941481e-01 -7.96356618e-01
6.52112305e-01 -3.16427827e-01 6.69392288e-01 -3.34455281e-01
5.93481243e-01 5.00645459e-01 -1.34170723e+00 5.29774688e-02
9.90981460e-01 9.10230100e-01 5.75649083e-01 4.74247575e-01
1.88151106e-01 7.48351872e-01 -5.08733153e-01 -3.48318338e-01
5.10184586e-01 -2.87477881e-01 -2.91742552e-02 5.38638055e-01
7.43280053e-01 -1.08321059e+00 -6.57619417e-01 1.09596694e+00
1.06002897e-01 2.53255904e-01 2.78917640e-01 -1.25417292e+00
-7.01170146e-01 -1.80932134e-01 -8.89098108e-01 4.56906185e-02
2.40565807e-01 2.82148570e-01 3.97164762e-01 -9.09782887e-01
7.44945168e-01 1.31316841e+00 3.72060746e-01 1.63069502e-01
-5.17324328e-01 -9.61049736e-01 2.80718237e-01 4.90521848e-01
-1.36865067e+00 -3.85067374e-01 1.08403015e+00 -1.23382725e-01
3.30021918e-01 2.95524690e-02 6.82414711e-01 6.12041593e-01
7.47317791e-01 4.84747946e-01 1.20832467e+00 -3.52327764e-01
4.58415709e-02 1.99171558e-01 -3.00898671e-01 7.11417079e-01
9.00105089e-02 5.09633601e-01 -3.69929612e-01 4.17092592e-01
8.55592906e-01 4.76153672e-01 -6.54397249e-01 -5.83196521e-01
-8.89278591e-01 4.00932580e-01 3.94795924e-01 -2.83833176e-01
3.74833532e-02 -1.98666919e-02 -1.83153942e-01 1.37586929e-02
5.39054751e-01 2.76800096e-01 -1.13722332e-01 1.66225582e-01
-8.99624288e-01 4.39526975e-01 3.06986719e-01 1.40391743e+00
9.53347206e-01 -6.24341480e-02 2.70778239e-01 7.04972804e-01
3.69080007e-01 8.28034401e-01 -9.67283994e-02 -1.18945980e+00
7.74399161e-01 4.89244580e-01 4.54707265e-01 -1.42858529e+00
-1.07059158e-01 -6.48925155e-02 -6.76040351e-01 6.57904565e-01
3.50885540e-01 -1.06521130e-01 -6.05404854e-01 1.08953178e+00
4.62546200e-01 1.38185784e-01 5.43207712e-02 1.08435333e+00
6.67030752e-01 1.06929004e+00 -6.69563890e-01 -2.75863081e-01
1.11770642e+00 -1.29620492e+00 -9.47026551e-01 -3.64048421e-01
3.08307856e-01 -9.00926888e-01 9.88280714e-01 7.34728575e-01
-1.06227899e+00 -5.84375024e-01 -1.33379591e+00 -5.19240141e-01
1.56604797e-02 3.73244673e-01 -8.99334401e-02 4.69908953e-01
-6.25302374e-01 8.90926868e-02 -3.48346651e-01 7.82139320e-03
1.86068669e-01 -4.06597018e-01 -2.94283450e-01 -7.14542150e-01
-9.92780387e-01 9.80036139e-01 2.86990196e-01 1.65939674e-01
-7.32025683e-01 -9.70097959e-01 -9.43406940e-01 1.97061986e-01
7.53434956e-01 -1.58157557e-01 8.26739788e-01 -7.31146991e-01
-1.85645270e+00 4.76026952e-01 -1.48163857e-02 -3.48020911e-01
5.63994229e-01 -4.43869174e-01 -3.96948129e-01 2.79235691e-01
-2.21688196e-01 8.22065115e-01 1.07661152e+00 -1.44927359e+00
-9.07245159e-01 -3.47445697e-01 2.36977160e-01 5.69396377e-01
-1.11795455e-01 -3.26473534e-01 -7.03104079e-01 -6.06869221e-01
1.06913850e-01 -9.67422843e-01 1.02131866e-01 5.86864293e-01
-4.29153740e-01 1.20088376e-01 1.31991005e+00 -6.62448287e-01
1.26750493e+00 -2.55371094e+00 1.56967882e-02 -1.03525087e-01
2.09331974e-01 1.39942124e-01 1.91720501e-01 3.46447468e-01
1.73852593e-01 -3.39948177e-01 -3.56193364e-01 -3.33311170e-01
-2.82577246e-01 1.75457582e-01 -7.70595670e-01 6.52171075e-01
-1.26674905e-01 5.15796542e-01 -8.93129289e-01 -4.65643734e-01
6.67687774e-01 2.51285523e-01 -5.33866227e-01 4.04489666e-01
-4.16364074e-02 2.64190763e-01 -1.05245672e-01 4.82575923e-01
1.53622794e+00 3.72976005e-01 -1.29556879e-01 -3.99419546e-01
-6.58932209e-01 -3.29531431e-01 -1.10775006e+00 1.63066804e+00
-4.86241430e-01 1.03597379e+00 5.52866645e-02 -3.15177232e-01
1.34938669e+00 -5.86733878e-01 4.09467518e-02 -7.89609313e-01
-5.27289137e-02 5.72109642e-03 -4.33391958e-01 -7.23147631e-01
7.99979925e-01 8.41147825e-02 1.93648208e-02 2.29480758e-01
-3.92015457e-01 -8.26105297e-01 -1.20309554e-01 1.16673201e-01
4.96593833e-01 3.06646138e-01 1.30775794e-01 -5.44375479e-02
6.06174588e-01 -8.69491994e-02 5.10554552e-01 2.95786679e-01
-3.06407902e-02 9.46761608e-01 4.12540555e-01 -5.57457566e-01
-1.24551666e+00 -9.57037449e-01 -9.24006626e-02 5.23446381e-01
1.03303444e+00 -3.22999090e-01 -9.03681457e-01 -4.19622332e-01
-3.73479843e-01 9.98086572e-01 -4.90932763e-01 -2.72215009e-01
-6.70040071e-01 -2.73173228e-02 2.96795487e-01 1.16016157e-01
1.35403192e+00 -6.53466165e-01 -1.05861199e+00 -2.16215491e-01
-2.15880960e-01 -1.21744180e+00 -8.97061408e-01 -5.67363262e-01
-6.08549953e-01 -1.21951926e+00 -7.49079525e-01 -4.85296488e-01
6.67495251e-01 1.10935187e+00 6.60460055e-01 -3.58066335e-02
3.95819955e-02 7.75986239e-02 -3.07788402e-01 -3.69619370e-01
-2.56307214e-01 -4.46515620e-01 -3.62429291e-01 8.06655139e-02
-2.76241433e-02 -3.36670339e-01 -9.67760742e-01 7.32056499e-01
-1.13711166e+00 4.88450795e-01 7.94925213e-01 6.89765334e-01
4.24103856e-01 4.03820902e-01 -2.05734104e-01 -6.46824598e-01
-2.98361131e-03 -3.91934663e-01 -1.01944947e+00 1.57539576e-01
-7.52910316e-01 -2.45171815e-01 6.87588751e-01 -2.90050507e-01
-1.56439185e+00 5.29613122e-02 2.65778422e-01 -7.77641296e-01
-9.27905217e-02 -3.02351087e-01 -4.60965216e-01 -3.47430147e-02
3.07291806e-01 4.77196604e-01 2.34936737e-02 -2.03512654e-01
5.03905654e-01 6.94184065e-01 7.29976356e-01 -3.95243764e-02
9.79181647e-01 8.89373183e-01 5.25891110e-02 -1.04635322e+00
-7.33461440e-01 -2.01169029e-01 -4.69167739e-01 -4.57917601e-01
8.79902661e-01 -8.23408663e-01 -4.51186091e-01 8.05716813e-01
-1.37161517e+00 -2.00987101e-01 -7.28026405e-03 3.49553764e-01
-3.78745198e-01 6.89330876e-01 -4.40139249e-02 -5.22258818e-01
6.90241903e-03 -1.32597101e+00 1.15706336e+00 4.60964799e-01
4.41924959e-01 -6.95354283e-01 -1.52024075e-01 3.53987724e-01
6.57025501e-02 1.28100276e-01 8.16854954e-01 3.04510266e-01
-1.03985786e+00 2.53433168e-01 -3.81123424e-01 5.35171747e-01
-6.11574128e-02 1.89516306e-01 -7.77284563e-01 -6.10362925e-02
1.98134273e-01 1.14573799e-02 6.93948030e-01 2.70222604e-01
1.15890956e+00 -2.29406372e-01 -2.06853762e-01 1.10825980e+00
1.31807876e+00 4.62744862e-01 1.18106902e+00 4.54099298e-01
5.87937295e-01 7.65971482e-01 1.21270466e+00 3.80773216e-01
5.26085019e-01 8.01567614e-01 6.80635512e-01 8.48518568e-04
-2.28491813e-01 -5.45187831e-01 5.39100170e-01 1.74362212e-01
1.96994722e-01 -5.46320617e-01 -4.07842338e-01 2.29808271e-01
-1.40528703e+00 -9.70299900e-01 -2.16273919e-01 2.21556449e+00
5.93270421e-01 -1.63813811e-02 -3.47782046e-01 -4.16727066e-02
6.38426721e-01 4.61330414e-01 -6.58537745e-01 -2.97358364e-01
-1.79926574e-01 -4.95426714e-01 7.18344569e-01 7.74424672e-01
-7.11208701e-01 8.43637228e-01 5.16911983e+00 9.18863177e-01
-1.26603746e+00 -1.29015177e-01 5.72245896e-01 -5.42413369e-02
-4.32994783e-01 1.44992933e-01 -1.02803314e+00 7.94103861e-01
2.02456743e-01 6.60247430e-02 4.98719186e-01 6.61361098e-01
4.80503082e-01 -6.29970670e-01 -7.72174478e-01 1.13538098e+00
5.26605129e-01 -1.35543716e+00 -1.04105070e-01 4.37610075e-02
8.79473746e-01 -4.26424772e-01 2.20406383e-01 -1.55168518e-01
-2.16904432e-01 -6.81997538e-01 9.53703284e-01 7.42744565e-01
1.02392268e+00 -8.39819908e-01 3.58523399e-01 5.02500296e-01
-8.75449061e-01 -2.65231788e-01 -6.90669715e-01 1.03170969e-01
2.15104789e-01 5.60053706e-01 -6.77564323e-01 4.22732919e-01
8.81711483e-01 1.00004852e+00 -6.34669960e-01 6.93112671e-01
-3.53510231e-01 8.75480250e-02 -1.31740108e-01 3.62071782e-01
3.23911041e-01 -6.06107056e-01 6.55407488e-01 7.38761485e-01
6.82450414e-01 4.63561326e-01 -2.54199833e-01 9.99948680e-01
4.35752273e-02 -2.34158278e-01 -8.51391017e-01 6.69830620e-01
8.31067920e-01 1.14757538e+00 -3.47527236e-01 -2.80446917e-01
-5.52884698e-01 1.14275181e+00 -1.41022295e-01 4.58896756e-01
-1.15762293e+00 -7.14908481e-01 2.91375309e-01 4.64781642e-01
4.54957306e-01 -1.54551283e-01 -1.55674323e-01 -9.76409376e-01
1.31039590e-01 -5.71355164e-01 -2.49630526e-01 -1.47328842e+00
-4.59902376e-01 4.41926718e-01 3.65643352e-01 -1.69904017e+00
1.38453498e-01 -3.96433294e-01 -6.38227880e-01 6.74921274e-01
-1.90216029e+00 -1.08317268e+00 -1.01163042e+00 5.35090744e-01
9.68202531e-01 4.69619967e-03 -1.14733167e-02 1.30298078e-01
-3.85401726e-01 3.20528865e-01 3.90604913e-01 -3.79326910e-01
1.15785980e+00 -8.02378178e-01 5.25379293e-02 1.12340581e+00
-4.88229424e-01 3.15893680e-01 6.49988890e-01 -5.19832313e-01
-1.39757800e+00 -1.28453469e+00 3.76257122e-01 -2.45286837e-01
1.49974644e-01 -2.06250072e-01 -7.64887512e-01 5.37716806e-01
4.12758768e-01 9.41934511e-02 -5.67330830e-02 -9.09693837e-01
-1.71750426e-01 -5.20638883e-01 -1.17893982e+00 6.54327929e-01
9.76217270e-01 -1.11613981e-01 -4.54941213e-01 8.34244415e-02
7.20238328e-01 -7.72039056e-01 -5.18935204e-01 8.57115537e-02
7.56959438e-01 -1.52969003e+00 9.63627398e-01 2.94087142e-01
1.02471030e+00 -6.34973943e-01 -8.91120359e-02 -1.47787428e+00
-7.59218037e-02 -6.99490607e-01 9.66978148e-02 1.15154850e+00
-2.19600171e-01 -5.40117145e-01 4.85084981e-01 3.77036750e-01
-6.27764165e-01 -7.91520238e-01 -6.49817705e-01 -4.13502812e-01
-1.13710500e-01 2.47943681e-03 6.59666836e-01 4.89527911e-01
-3.51914525e-01 8.26829001e-02 -7.73924232e-01 4.10259038e-01
7.54223108e-01 2.76888639e-01 1.18653083e+00 -7.08308697e-01
-1.94066361e-01 6.43548965e-02 -1.25830308e-01 -1.78001952e+00
-3.57862264e-02 -1.00424819e-01 2.59662926e-01 -1.03500378e+00
-1.22338392e-01 -4.10077065e-01 4.95505333e-01 -1.61000058e-01
-1.90529048e-01 2.58949041e-01 3.94901335e-01 2.99325466e-01
-3.71252745e-01 7.22062945e-01 1.78933287e+00 -1.27138257e-01
-2.92307973e-01 -1.10918075e-01 -4.73248810e-01 8.41778040e-01
5.24515986e-01 -2.18160182e-01 -8.98405969e-01 -7.80617416e-01
2.03722686e-01 1.71834677e-01 3.90540749e-01 -8.83659542e-01
3.91090572e-01 -3.63093585e-01 4.32864875e-01 -1.08028042e+00
4.90665644e-01 -9.78470623e-01 1.18795663e-01 2.70505458e-01
-8.59495923e-02 5.42583130e-02 -1.51106529e-02 7.61140645e-01
-1.70304894e-01 -2.94792652e-01 1.12058246e+00 8.74497071e-02
-9.18281555e-01 1.27207398e-01 -2.04314277e-01 2.10911385e-03
1.37854111e+00 -5.46167016e-01 -6.19190574e-01 -4.22148943e-01
1.20683677e-01 1.87860534e-01 9.78721082e-01 3.29599977e-01
1.25465310e+00 -1.11219120e+00 -5.15250862e-01 7.12922037e-01
1.04569815e-01 4.61140513e-01 6.43764138e-01 7.36036777e-01
-9.16463971e-01 2.78141111e-01 -3.78178209e-01 -5.53812265e-01
-1.19535434e+00 6.68592036e-01 3.26244920e-01 1.70378521e-01
-1.01475620e+00 4.81370151e-01 7.65795767e-01 -7.13844448e-02
-1.82423107e-02 -5.46537817e-01 -1.65017977e-01 -3.75821233e-01
7.20955431e-01 7.15947926e-01 -2.32478619e-01 -4.64842975e-01
-7.36329556e-02 9.07722414e-01 -8.13860893e-02 -5.65194106e-03
1.11662614e+00 -8.02158356e-01 4.42032143e-02 -3.19061689e-02
9.75037158e-01 4.70550269e-01 -1.92988241e+00 -2.56238654e-02
-7.90898383e-01 -1.16984820e+00 1.33939207e-01 -4.85631198e-01
-1.06457543e+00 1.12601173e+00 5.42302847e-01 -1.86741486e-01
1.31036019e+00 -4.00997728e-01 1.16736710e+00 3.78139317e-01
1.12388261e-01 -9.54175711e-01 1.00398608e-01 3.12027395e-01
1.07433879e+00 -9.50425565e-01 3.45541328e-01 -6.93318903e-01
-7.45994568e-01 1.45409870e+00 8.56060803e-01 -3.84799600e-01
4.70712960e-01 1.13544971e-01 -6.23799972e-02 1.02012465e-03
-4.49256450e-01 4.83563393e-01 2.09968220e-02 6.27373219e-01
-4.37236726e-01 -4.50006008e-01 -7.13028684e-02 3.92800272e-01
-1.34909362e-01 -3.38084176e-02 1.17422545e+00 4.85517025e-01
-6.46170735e-01 -5.22826135e-01 -7.23524034e-01 -1.19019359e-01
1.86095446e-01 -3.98141779e-02 -8.07125270e-02 9.50356603e-01
5.00027716e-01 1.03419125e+00 2.69444942e-01 -2.21567109e-01
4.21463311e-01 -5.81985772e-01 4.94553089e-01 -3.07093084e-01
2.93731898e-01 9.79003161e-02 -1.87360108e-01 -7.69050419e-01
-1.81313306e-01 -3.76855403e-01 -1.13126099e+00 -2.92183667e-01
-3.59101802e-01 -1.62126288e-01 5.07475972e-01 7.88700104e-01
3.72379303e-01 2.67975062e-01 1.14682221e+00 -9.79678392e-01
-4.56792295e-01 -6.78740382e-01 -6.61695182e-01 1.75701588e-01
4.29069191e-01 -9.36729729e-01 -5.45909107e-01 2.53003180e-01] | [10.185526847839355, -2.5118086338043213] |
5e80f980-d627-4779-bed0-49d75b0f9d59 | neural-frailty-machine-beyond-proportional | 2303.10358 | null | https://arxiv.org/abs/2303.10358v1 | https://arxiv.org/pdf/2303.10358v1.pdf | Neural Frailty Machine: Beyond proportional hazard assumption in neural survival regressions | We present neural frailty machine (NFM), a powerful and flexible neural modeling framework for survival regressions. The NFM framework utilizes the classical idea of multiplicative frailty in survival analysis to capture unobserved heterogeneity among individuals, at the same time being able to leverage the strong approximation power of neural architectures for handling nonlinear covariate dependence. Two concrete models are derived under the framework that extends neural proportional hazard models and nonparametric hazard regression models. Both models allow efficient training under the likelihood objective. Theoretically, for both proposed models, we establish statistical guarantees of neural function approximation with respect to nonparametric components via characterizing their rate of convergence. Empirically, we provide synthetic experiments that verify our theoretical statements. We also conduct experimental evaluations over $6$ benchmark datasets of different scales, showing that the proposed NFM models outperform state-of-the-art survival models in terms of predictive performance. Our code is publicly availabel at https://github.com/Rorschach1989/nfm | ['Weiqiang Wang', 'Tianyi Zhang', 'Tengfei Liu', 'Ming Zheng', 'Wen Yu', 'Mingzhe Wu', 'Jiawei Qiao', 'Ruofan Wu'] | 2023-03-18 | null | null | null | null | ['survival-analysis'] | ['miscellaneous'] | [-3.68446231e-01 4.38248143e-02 -5.36067426e-01 -5.67437887e-01
-7.88896918e-01 -3.65853421e-02 2.15442404e-01 3.69950049e-02
-2.76647747e-01 1.08393848e+00 3.27006638e-01 -5.37749588e-01
-3.61045599e-01 -7.23770201e-01 -7.37292171e-01 -8.30206931e-01
-7.32646942e-01 4.34003949e-01 -2.68039197e-01 2.90954430e-02
-3.05092931e-01 1.97211936e-01 -1.07518911e+00 -4.00955349e-01
8.28958869e-01 9.94947493e-01 -5.27416468e-01 5.97113371e-01
4.37218696e-01 1.05151546e+00 -1.52557999e-01 -5.23845375e-01
-4.60348465e-03 4.94071357e-02 -2.24753246e-01 -7.79866576e-01
1.87111974e-01 -6.06726050e-01 -9.23244953e-01 7.06956863e-01
5.10745943e-01 1.53628603e-01 1.16684425e+00 -1.53089416e+00
-9.84064877e-01 8.02919030e-01 -4.21367049e-01 1.52091831e-01
-1.76438823e-01 1.18622612e-02 7.30944037e-01 -8.20800781e-01
-2.54532814e-01 1.25775754e+00 1.33758640e+00 7.50109553e-01
-1.20251286e+00 -8.87075663e-01 -1.39605984e-01 -3.52545440e-01
-1.52525544e+00 -4.88149405e-01 2.87411898e-01 -5.62516093e-01
7.44788527e-01 4.54538837e-02 7.16968328e-02 1.45726132e+00
6.15167320e-01 7.70464122e-01 7.91250944e-01 -1.27075806e-01
2.82558650e-01 -1.86112925e-01 8.97945404e-01 6.27253890e-01
4.44519997e-01 6.81672454e-01 -3.90092552e-01 -5.72880507e-01
1.14392459e+00 4.84298170e-01 -2.46501312e-01 -2.12131754e-01
-7.06606448e-01 1.00031281e+00 4.14783478e-01 -4.40815873e-02
-4.98246551e-01 8.67697477e-01 3.68183225e-01 2.84171313e-01
5.61616480e-01 -4.78371620e-01 -4.41283196e-01 -3.81087884e-02
-1.04583514e+00 2.62217700e-01 8.31027269e-01 1.01115227e+00
6.91255480e-02 3.45568955e-01 -5.27263820e-01 6.45904303e-01
3.15375507e-01 4.82071906e-01 3.11381757e-01 -7.77672589e-01
1.38365462e-01 3.09292138e-01 1.19240418e-01 -4.60588455e-01
-7.78217316e-01 -6.92795575e-01 -1.55892634e+00 8.65474716e-02
5.89689732e-01 -1.84904963e-01 -9.08141017e-01 2.31534290e+00
-1.20197542e-01 5.01030803e-01 1.35753483e-01 3.82503361e-01
6.07047141e-01 4.97383356e-01 6.10265672e-01 -1.05761074e-01
1.17780733e+00 -5.74203432e-01 -4.06524897e-01 2.54054785e-01
5.11895359e-01 8.02345723e-02 9.56299961e-01 2.76700199e-01
-1.20995927e+00 -3.02084088e-01 -9.02544737e-01 -2.22961791e-02
5.84662929e-02 -4.67424048e-03 1.00397301e+00 9.01573777e-01
-1.25145066e+00 7.97182322e-01 -1.20178211e+00 -1.61823958e-01
5.81103683e-01 5.28371513e-01 -8.04690048e-02 -2.02440303e-02
-1.40979528e+00 4.89849120e-01 2.36916617e-01 1.09815881e-01
-1.36559296e+00 -8.18213582e-01 -7.98260331e-01 5.20057976e-01
-2.95918919e-02 -1.19036555e+00 1.34163654e+00 -7.10056603e-01
-1.04461336e+00 3.97662580e-01 7.97952116e-02 -8.98832679e-01
6.81529284e-01 -3.59297603e-01 -3.03259045e-01 -2.11851314e-01
-2.37446591e-01 2.85494030e-01 4.89380479e-01 -8.18584979e-01
-3.17252517e-01 -1.46708339e-01 -1.91697687e-01 -4.51183319e-01
-6.76602840e-01 -3.70935909e-02 -1.55073807e-01 -9.22650993e-01
-5.03636301e-01 -6.11529410e-01 -3.77664715e-01 7.72303864e-02
-3.23285013e-01 -2.60442495e-01 2.30298806e-02 -6.67194605e-01
1.56541288e+00 -1.96585155e+00 -2.50666708e-01 1.67484358e-01
4.36951250e-01 -2.43069082e-01 -2.65704412e-02 3.19118738e-01
-1.69220805e-01 -3.57738286e-02 -5.46987891e-01 -7.64279187e-01
2.60119706e-01 7.03122839e-02 -3.49752039e-01 6.74521029e-01
-1.42513305e-01 1.09080172e+00 -5.27423143e-01 -3.13337862e-01
-2.87528336e-01 8.51595700e-01 -3.81489724e-01 1.56513229e-01
2.02444553e-01 2.75001794e-01 -2.85172284e-01 9.94418919e-01
5.06169081e-01 -4.58546758e-01 -7.88120627e-02 5.52585363e-01
2.39592403e-01 -1.61889851e-01 -6.80309892e-01 1.27210402e+00
-2.52004117e-01 6.92294762e-02 -1.48962632e-01 -1.05426013e+00
8.98685634e-01 5.33989429e-01 3.80772948e-01 -2.64697582e-01
5.10910153e-01 3.01033407e-01 -5.19284725e-01 1.00531252e-02
3.31324995e-01 -4.37101722e-01 -3.87854874e-01 2.04863608e-01
2.31037021e-01 1.02343059e+00 -1.68874115e-01 -6.18144609e-02
1.19370604e+00 5.63369282e-02 4.80608433e-01 -5.49816489e-01
2.23130882e-01 -5.09003401e-01 6.51443958e-01 1.27258122e+00
-4.28977728e-01 1.82243153e-01 5.66767871e-01 -6.50966167e-01
-7.74784565e-01 -1.65780580e+00 -4.58131701e-01 1.17469203e+00
-3.07967544e-01 1.05821684e-01 -5.53392708e-01 -3.97736579e-01
2.82853544e-01 6.45921409e-01 -1.14521229e+00 -3.61306489e-01
-3.56629729e-01 -1.15675509e+00 1.13128805e+00 1.08014631e+00
-1.06497630e-01 -9.86894965e-01 -3.76946181e-01 9.67992470e-02
5.44131957e-02 -2.79504687e-01 -3.18704069e-01 5.55226266e-01
-1.20080900e+00 -8.93802643e-01 -1.21414006e+00 -6.25688910e-01
3.50405276e-01 -1.85122833e-01 1.42962849e+00 3.45703155e-01
-3.17958333e-02 2.68315941e-01 3.87662873e-02 -8.00079182e-02
-4.26908404e-01 1.00901559e-01 4.07382816e-01 -3.26326638e-01
3.90029311e-01 -1.07579768e+00 -7.57797241e-01 2.90427357e-01
-9.57677603e-01 -2.73932755e-01 7.08055854e-01 8.94679844e-01
4.27704155e-01 -4.18794453e-02 1.05737579e+00 -6.50021493e-01
5.36907434e-01 -1.17218792e+00 -6.00793719e-01 2.59117216e-01
-8.32076728e-01 1.01902589e-01 5.06765544e-01 -6.57501280e-01
-7.60467470e-01 -3.75691980e-01 -2.83833500e-03 -5.03711998e-01
-1.90646928e-02 6.54442310e-01 -3.69443037e-02 3.72899592e-01
5.40491879e-01 1.79495856e-01 -6.43653283e-03 -5.55862427e-01
1.03115559e-01 3.63205791e-01 9.45649266e-01 -8.90568256e-01
6.32217526e-01 4.40128595e-01 3.32306772e-01 -1.76666886e-01
-5.85129142e-01 -2.54910231e-01 -4.21889067e-01 -2.98236366e-02
5.53539515e-01 -1.11012268e+00 -1.05051863e+00 7.40884840e-01
-6.58219934e-01 -6.93932772e-01 -1.55555740e-01 4.27389294e-01
-8.70863020e-01 1.35650069e-01 -1.09363127e+00 -1.28449428e+00
-7.68552721e-01 -5.98216176e-01 7.01723635e-01 3.18083137e-01
-4.57203537e-02 -1.35528016e+00 3.86466622e-01 -2.26410747e-01
5.60387671e-01 5.74240804e-01 1.08965373e+00 -6.13155723e-01
-1.32739022e-01 -5.37474930e-01 -1.16506942e-01 2.49039367e-01
-2.65890658e-01 -2.18237698e-01 -9.01092470e-01 -5.72257638e-01
-1.64958730e-01 -2.62242496e-01 1.30990076e+00 1.07027626e+00
1.07273889e+00 -3.91533822e-01 -4.07047123e-01 8.38764787e-01
1.49272633e+00 -8.23926553e-03 8.40426028e-01 1.35771856e-01
3.96378517e-01 4.24620807e-01 4.84326258e-02 6.25799656e-01
5.83591580e-01 1.83376491e-01 3.92175972e-01 -3.71571770e-03
3.15822065e-01 -3.58007044e-01 5.83741248e-01 4.21668649e-01
-1.94987491e-01 -4.23472911e-01 -9.19886172e-01 5.22245109e-01
-2.17333841e+00 -9.68020022e-01 -2.06052244e-01 2.54954600e+00
7.73929596e-01 2.53588229e-01 6.08489752e-01 -1.32211745e-01
7.34891415e-01 -3.29179466e-01 -6.67111814e-01 -9.78655443e-02
-2.43508726e-01 1.72638774e-01 7.47959673e-01 4.12711173e-01
-1.22945654e+00 3.70911479e-01 6.60532236e+00 7.44711459e-01
-5.60283005e-01 2.43831292e-01 1.11716449e+00 -3.67978454e-01
-1.37151122e-01 -2.42692754e-01 -7.81333923e-01 5.36324322e-01
1.53441405e+00 -2.33885631e-01 2.70818561e-01 9.45230246e-01
-2.24670116e-02 3.70330572e-01 -1.11182237e+00 7.56442666e-01
-3.70502889e-01 -9.26409781e-01 -2.41846487e-01 1.93337634e-01
4.90356177e-01 2.28547119e-02 3.91194075e-01 9.85456228e-01
7.00602055e-01 -1.46469486e+00 8.00942361e-01 1.20592153e+00
9.40204859e-01 -1.08244717e+00 8.28973055e-01 3.71803135e-01
-9.63579655e-01 -3.29646468e-01 -4.35642421e-01 -1.67224422e-01
2.43893534e-01 6.34722412e-01 -2.65887767e-01 4.44134891e-01
8.02034020e-01 4.12130177e-01 -5.71295440e-01 1.13470137e+00
7.71330446e-02 1.04050839e+00 -2.67858684e-01 2.53549010e-01
-3.75603698e-02 1.58383489e-01 2.98274636e-01 1.18554807e+00
6.55767620e-01 -1.77218050e-01 -7.92926997e-02 8.88147175e-01
-2.16893479e-01 -1.48928046e-01 -2.91740447e-01 8.54665786e-02
4.83824462e-01 9.96318519e-01 -4.79529500e-01 -1.84163898e-01
-4.72238004e-01 6.09502852e-01 4.95062023e-01 4.38147575e-01
-1.17748058e+00 -3.55467312e-02 5.63540518e-01 1.33288532e-01
7.85262883e-02 -7.59694725e-02 -3.93787146e-01 -1.14825618e+00
-2.07402095e-01 -3.11767161e-01 9.44828808e-01 -3.94676656e-01
-1.82469380e+00 5.52403748e-01 2.86241435e-02 -1.01820982e+00
-3.37467194e-01 -6.47413433e-01 -6.43074930e-01 9.71023858e-01
-1.38156891e+00 -1.36067307e+00 -1.61343843e-01 7.12156057e-01
1.21499295e-03 -8.21338594e-02 9.54203188e-01 3.96795809e-01
-7.97367394e-01 1.22844219e+00 6.16768777e-01 7.22634718e-02
5.47427714e-01 -1.29875493e+00 6.17133856e-01 7.12705135e-01
-3.85149240e-01 9.37033057e-01 5.14979899e-01 -7.51205981e-01
-9.25172031e-01 -1.23430526e+00 5.31592607e-01 -6.18943870e-01
6.12329364e-01 -3.42699409e-01 -1.08742511e+00 7.90548265e-01
-2.40613744e-01 -1.46852508e-01 1.10178220e+00 4.43412095e-01
-6.10948741e-01 1.84794351e-01 -1.14318621e+00 4.32268441e-01
8.04650128e-01 -8.71338621e-02 -2.80766606e-01 -9.51691642e-02
7.66931355e-01 4.95180115e-03 -1.10958207e+00 5.18472493e-01
1.06471956e+00 -9.62716222e-01 1.13025725e+00 -9.31765974e-01
5.23302138e-01 1.08740024e-01 -4.11296993e-01 -7.51902103e-01
-6.70821249e-01 -7.44127095e-01 -8.88675511e-01 1.26521218e+00
3.74796152e-01 -8.76335442e-01 6.42189026e-01 9.05412912e-01
-3.07991598e-02 -1.05537033e+00 -1.24753964e+00 -1.25805259e+00
8.43061805e-01 -4.87008274e-01 7.24912703e-01 7.57803559e-01
-1.92334026e-01 -1.82728887e-01 -9.80401754e-01 2.56329685e-01
1.03000128e+00 -2.27105364e-01 4.36896503e-01 -1.63472140e+00
-6.47816598e-01 -5.94469726e-01 -2.75732309e-01 -7.02375114e-01
3.40683132e-01 -7.99137354e-01 1.78152937e-02 -1.08247554e+00
7.06332386e-01 -3.90127301e-01 -1.17833126e+00 6.99238896e-01
-3.09003741e-01 2.40043297e-01 -2.59191304e-01 3.80020380e-01
-5.05380929e-01 7.70393193e-01 4.03782010e-01 1.59509957e-01
-1.23872720e-01 3.14243019e-01 -1.04195118e+00 6.26037240e-01
9.75557268e-01 -6.15049362e-01 -1.68571889e-01 -9.16731060e-02
3.39019373e-02 5.31132221e-01 8.73965144e-01 -1.07569814e+00
1.14009753e-02 -4.30001728e-02 5.24608374e-01 -4.50262219e-01
1.44544855e-01 -5.75767517e-01 3.24027926e-01 6.82339907e-01
-3.02907467e-01 1.55286938e-01 2.12217450e-01 8.44802260e-01
3.13940525e-01 1.09298728e-01 7.89597154e-01 4.32017148e-01
-1.30537093e-01 7.14268923e-01 -2.36809239e-01 4.97024618e-02
6.53513312e-01 2.41430886e-02 -4.82919186e-01 -6.20350897e-01
-7.14243293e-01 4.05225515e-01 4.93553847e-01 3.12556505e-01
6.08461499e-01 -1.51461148e+00 -7.70728767e-01 -3.11280554e-03
6.02253154e-02 -3.44955534e-01 5.66667855e-01 1.19617712e+00
-1.07044525e-01 4.58095163e-01 -9.68633145e-02 -1.71448782e-01
-6.93512261e-01 9.19470191e-01 4.49768603e-01 -5.05278230e-01
-6.12640023e-01 7.01746523e-01 6.55534506e-01 -2.63974905e-01
5.91823101e-01 -4.10914272e-01 1.09357029e-01 -4.32291448e-01
7.48711526e-01 7.15876400e-01 -3.50217640e-01 -3.80596876e-01
-2.90120244e-01 -9.83031690e-02 5.74950650e-02 9.23178717e-03
1.49981594e+00 -6.47030994e-02 1.63505480e-01 6.18826747e-01
9.83631909e-01 -5.30500293e-01 -1.48755038e+00 -2.70712167e-01
-1.18645104e-02 1.17172137e-01 -6.58582672e-02 -9.71526086e-01
-8.87188256e-01 7.02068627e-01 6.47371352e-01 -4.95945103e-02
1.29873288e+00 -1.16073549e-01 8.07967663e-01 1.65475354e-01
4.04182047e-01 -3.59445870e-01 -3.90467912e-01 3.28360975e-01
5.55083871e-01 -8.77573609e-01 -3.32887918e-01 1.31991595e-01
-4.05871391e-01 9.66335118e-01 2.61816949e-01 -3.45531076e-01
8.53736639e-01 4.23340440e-01 -2.13825852e-01 -4.94564921e-02
-8.10934126e-01 2.66250074e-01 2.24078104e-01 6.12522840e-01
5.40569246e-01 3.31604451e-01 -3.93179655e-02 1.53664935e+00
-3.56043465e-02 3.49041283e-01 2.82182723e-01 6.15073383e-01
-3.18231791e-01 -8.00039649e-01 -2.87569582e-01 5.43489695e-01
-7.98809290e-01 -4.44657683e-01 2.06741452e-01 8.46469581e-01
-5.16990840e-01 6.92865193e-01 -4.86399494e-02 -1.35722056e-01
5.73583785e-03 2.13086471e-01 2.58967280e-01 -3.84421647e-02
-3.31875265e-01 -1.43981725e-01 -3.10981542e-01 -2.77562261e-01
1.22096566e-02 -6.01409733e-01 -1.11739361e+00 -6.36376500e-01
2.66063549e-02 -5.03370771e-03 1.37571692e-01 5.32792330e-01
1.57508567e-01 4.78067964e-01 3.87031406e-01 -5.37171543e-01
-1.06809545e+00 -1.09338832e+00 -9.64624107e-01 4.52515371e-02
5.54550886e-01 -9.70164478e-01 -4.49724466e-01 -1.62439719e-02] | [7.7844367027282715, 5.591602325439453] |
facbf9f6-dfe7-4af0-864f-d52e7006920a | undeepvo-monocular-visual-odometry-through | 1709.06841 | null | http://arxiv.org/abs/1709.06841v2 | http://arxiv.org/pdf/1709.06841v2.pdf | UnDeepVO: Monocular Visual Odometry through Unsupervised Deep Learning | We propose a novel monocular visual odometry (VO) system called UnDeepVO in
this paper. UnDeepVO is able to estimate the 6-DoF pose of a monocular camera
and the depth of its view by using deep neural networks. There are two salient
features of the proposed UnDeepVO: one is the unsupervised deep learning
scheme, and the other is the absolute scale recovery. Specifically, we train
UnDeepVO by using stereo image pairs to recover the scale but test it by using
consecutive monocular images. Thus, UnDeepVO is a monocular system. The loss
function defined for training the networks is based on spatial and temporal
dense information. A system overview is shown in Fig. 1. The experiments on
KITTI dataset show our UnDeepVO achieves good performance in terms of pose
accuracy. | ['Sen Wang', 'Dongbing Gu', 'Zhiqiang Long', 'Ruihao Li'] | 2017-09-20 | null | null | null | null | ['monocular-visual-odometry'] | ['robots'] | [-4.77661550e-01 -1.39126286e-01 -1.69282913e-01 -2.56381005e-01
1.13926098e-01 -3.21016133e-01 6.13402009e-01 -8.12649071e-01
-4.62776691e-01 6.00225627e-01 4.97725010e-02 1.21946819e-01
1.53095424e-01 -5.53056955e-01 -9.36292827e-01 -5.28131127e-01
2.65315026e-01 6.44911885e-01 2.06916884e-01 -2.21929811e-02
1.11101925e-01 7.16642439e-01 -1.46507275e+00 -3.26339990e-01
4.77761149e-01 1.23877490e+00 4.22750443e-01 5.87215245e-01
4.37981248e-01 8.48934293e-01 -1.81325004e-01 3.72127965e-02
6.94174945e-01 -1.17887795e-01 -6.76825404e-01 1.38976812e-01
7.26575077e-01 -7.51375437e-01 -9.66078341e-01 1.12428904e+00
5.33536255e-01 -1.73554286e-01 4.24502850e-01 -1.23135197e+00
-4.99739766e-01 -2.33655944e-01 -3.66807163e-01 2.34050099e-02
4.82138157e-01 1.30569234e-01 8.72737706e-01 -1.10559046e+00
1.06208944e+00 1.23144913e+00 5.69295824e-01 3.34749758e-01
-8.95019352e-01 -3.71922106e-01 -1.91728219e-01 4.64013577e-01
-1.56836045e+00 -3.12649816e-01 7.06723690e-01 -7.70033777e-01
8.75549853e-01 -2.08734363e-01 6.26964152e-01 7.28011787e-01
6.28244579e-01 5.23858666e-01 1.13606060e+00 -1.75860733e-01
2.09647894e-01 -1.54501408e-01 -2.29695275e-01 7.52489984e-01
2.17574909e-01 5.08659661e-01 -6.94327056e-01 3.14376354e-01
1.19832861e+00 3.03608418e-01 -3.22354555e-01 -1.24283659e+00
-1.06980586e+00 6.07782900e-01 9.26247716e-01 2.62513594e-03
-2.19775856e-01 2.48131558e-01 1.45086884e-01 4.46827471e-01
2.54244685e-01 3.54744196e-01 -4.11102980e-01 -2.22871210e-02
-6.12890482e-01 7.76284784e-02 5.18933475e-01 1.09382641e+00
9.14723158e-01 1.99992999e-01 3.58161330e-01 6.72979295e-01
4.66057301e-01 6.98678792e-01 7.06255019e-01 -1.13934183e+00
3.55734080e-01 4.89237368e-01 1.56137645e-01 -1.11831689e+00
-6.10164881e-01 -3.24880689e-01 -7.64331222e-01 6.16354704e-01
5.23321610e-03 -1.69850186e-01 -1.09822929e+00 1.59609675e+00
2.32399821e-01 2.49934811e-02 -1.12713553e-01 1.49784029e+00
9.67172265e-01 2.89342046e-01 -6.81730449e-01 1.44341126e-01
8.63350809e-01 -8.30284357e-01 -5.95637262e-01 -7.52114236e-01
1.40365943e-01 -5.56095123e-01 5.82411766e-01 3.56148958e-01
-8.45991075e-01 -6.81599379e-01 -1.56093752e+00 -3.00466657e-01
-8.98175985e-02 4.76853162e-01 2.78433770e-01 1.16462581e-01
-1.17333722e+00 4.13378716e-01 -9.57083583e-01 -4.09682661e-01
-2.35980779e-01 4.48781699e-01 -6.76844537e-01 -1.18491411e-01
-1.06825364e+00 9.47665691e-01 3.59964401e-01 1.64316237e-01
-9.39285159e-01 -1.69021681e-01 -1.37612557e+00 -7.62302652e-02
1.55817240e-01 -8.47487032e-01 1.19531596e+00 -6.74838722e-01
-1.74372005e+00 1.20255566e+00 -1.71692014e-01 -5.09600759e-01
7.66818762e-01 -4.94920909e-01 -7.28758052e-02 3.06080520e-01
2.43914187e-01 7.84007847e-01 7.72331715e-01 -1.10006213e+00
-4.09398019e-01 -7.33515918e-01 1.01332650e-01 5.61744153e-01
3.26969206e-01 -6.22151732e-01 -8.11867654e-01 -6.95331842e-02
9.29474235e-01 -1.18572116e+00 3.67291607e-02 3.52713555e-01
-4.01369125e-01 3.32265943e-01 7.27585316e-01 -5.12514412e-01
6.54911578e-01 -2.01923084e+00 3.78077835e-01 -1.34322271e-01
5.01473784e-01 1.54367670e-01 2.40577057e-01 3.23332638e-01
5.59555192e-04 -6.42805398e-01 2.37167567e-01 -4.54553813e-01
-1.68099195e-01 2.83709288e-01 -1.78390682e-01 9.77152526e-01
-1.01703346e-01 9.29291308e-01 -6.93019032e-01 -6.84560984e-02
5.97516835e-01 4.15894568e-01 -4.19258982e-01 3.39879990e-01
8.43944475e-02 6.67168558e-01 1.39723951e-02 5.23758650e-01
9.45975482e-01 -2.63473749e-01 1.03924975e-01 -2.59865791e-01
-3.46124291e-01 4.32587236e-01 -1.27373767e+00 1.83444154e+00
-4.70796764e-01 9.67659891e-01 9.23310444e-02 -4.31000531e-01
1.07663894e+00 3.44522223e-02 3.71041238e-01 -1.00087035e+00
4.48260486e-01 3.20599407e-01 -4.29420888e-01 -2.35607862e-01
5.39380133e-01 -2.63597906e-01 8.69558603e-02 -1.67840347e-01
2.68389702e-01 -3.65902245e-01 -2.10443954e-03 -1.29146680e-01
7.52364814e-01 4.45567012e-01 6.57000065e-01 -9.84101817e-02
5.40156066e-01 -1.16610229e-01 9.41373587e-01 3.42074871e-01
-4.80339825e-01 8.45770836e-01 2.12232322e-01 -6.52677536e-01
-1.20073140e+00 -1.28203082e+00 -2.56174356e-01 2.90549658e-02
7.88367271e-01 -2.27379892e-02 -1.17536187e-01 -3.43742400e-01
3.05323571e-01 -8.04820582e-02 -4.77485150e-01 2.37394962e-03
-5.58521688e-01 6.28389493e-02 6.28484366e-03 6.32003248e-01
8.81010830e-01 -6.95164144e-01 -7.94318855e-01 -1.43624395e-01
-8.66218433e-02 -1.45820069e+00 -5.19520700e-01 1.42946810e-01
-8.92922521e-01 -1.12210429e+00 -7.09300756e-01 -9.25269842e-01
4.06176955e-01 6.16352677e-01 9.41258311e-01 -4.61866528e-01
-4.93630283e-02 1.63489342e-01 1.47717029e-01 -1.62359625e-01
1.26465872e-01 6.47609879e-04 4.40869570e-01 -3.92016843e-02
3.98220539e-01 -8.12413454e-01 -7.75664330e-01 5.75533986e-01
-5.38079739e-01 1.33017853e-01 6.22499406e-01 8.99319947e-01
7.06441045e-01 -5.59074283e-01 -3.57434526e-02 -3.38119686e-01
-5.39247803e-02 -2.42871374e-01 -1.12024736e+00 -4.22778189e-01
-4.95843977e-01 1.67236373e-01 4.29897755e-01 7.69822001e-02
-7.15055525e-01 4.97322023e-01 -2.10253954e-01 -8.61104786e-01
-1.00408569e-01 3.19623590e-01 -3.88771296e-02 -2.23329738e-01
6.51855528e-01 2.35500589e-01 9.26216692e-02 -4.99069124e-01
8.12124088e-02 5.69220185e-01 7.91926444e-01 5.65242209e-03
9.70417857e-01 9.89865303e-01 2.71010578e-01 -8.22759271e-01
-8.58061790e-01 -8.28381181e-01 -1.07541597e+00 -1.42802104e-01
9.22108591e-01 -1.53756452e+00 -1.06158817e+00 5.98151922e-01
-1.15791297e+00 -1.99612975e-01 -1.16208322e-01 9.29760993e-01
-8.29399347e-01 4.15593058e-01 -7.13259816e-01 -3.87326270e-01
-2.01060072e-01 -1.17832088e+00 1.30945432e+00 1.06329344e-01
1.23636208e-01 -7.89603412e-01 6.17851675e-01 2.96979621e-02
-1.13436624e-01 2.70111948e-01 1.44434988e-01 1.69842690e-01
-9.43598688e-01 -1.17981359e-01 -4.62771386e-01 3.64122987e-01
-5.37186377e-02 -5.18186629e-01 -1.08679461e+00 -6.70135617e-01
2.53494024e-01 -5.27787626e-01 5.71810603e-01 5.70770264e-01
5.18622160e-01 1.01849064e-01 -1.09074101e-01 1.23325229e+00
1.78652954e+00 2.77114213e-01 5.67960203e-01 6.10087335e-01
9.50757504e-01 1.37105048e-01 6.53297305e-01 3.98522347e-01
5.01388669e-01 1.08228183e+00 9.05776978e-01 -1.26450015e-02
3.41258496e-02 -5.09717226e-01 3.36682558e-01 9.30500031e-01
2.76000202e-01 2.77980357e-01 -8.50549936e-01 6.00213647e-01
-1.83382499e+00 -7.11193323e-01 4.98209298e-02 2.20210361e+00
3.74668837e-01 8.93203095e-02 -2.49260232e-01 -8.56480971e-02
4.87709820e-01 3.63084584e-01 -7.65567958e-01 -3.07141721e-01
-1.28978699e-01 -1.25413552e-01 7.94977725e-01 6.69106960e-01
-1.18806314e+00 8.29085588e-01 6.06537914e+00 -8.13191757e-02
-1.61392558e+00 -1.08258262e-01 -3.33331851e-03 -1.01295017e-01
3.27732980e-01 -1.15428343e-02 -1.02675390e+00 1.87940091e-01
3.22665542e-01 -8.05769488e-02 4.29846644e-01 1.14816630e+00
2.23229025e-02 -1.87511548e-01 -1.10476100e+00 1.46552610e+00
3.29261392e-01 -1.21580768e+00 -1.53138697e-01 1.46029055e-01
9.25134540e-01 6.58894241e-01 -5.47986217e-02 1.02111541e-01
3.49003404e-01 -8.09058726e-01 9.12662745e-01 3.03308576e-01
1.01861334e+00 -5.38869321e-01 9.05246735e-01 5.52663267e-01
-1.30992854e+00 -7.02973902e-02 -6.93573236e-01 -4.87222940e-01
1.73549682e-01 5.82124949e-01 -8.43050957e-01 7.39369094e-01
8.24935257e-01 1.16010165e+00 -3.44907284e-01 1.32202208e+00
-5.71805477e-01 -2.95397043e-01 -1.42037988e-01 3.93825084e-01
2.48172879e-01 -2.68363178e-01 6.17439330e-01 4.77480114e-01
3.64984035e-01 -2.56069332e-01 2.66517788e-01 7.39362478e-01
-1.54521033e-01 -3.59848469e-01 -1.01206851e+00 5.54085195e-01
3.12830240e-01 9.36621487e-01 1.35343090e-01 -2.14310102e-02
-4.06533360e-01 1.13235569e+00 4.54053372e-01 1.75379351e-01
-4.85791892e-01 -3.10373306e-01 8.98997068e-01 -3.92716900e-02
4.66338038e-01 -5.62592089e-01 -3.24542135e-01 -1.55147302e+00
2.58468539e-01 -4.76575822e-01 1.50532387e-02 -1.21990907e+00
-9.11666989e-01 7.05276787e-01 -2.55882084e-01 -1.65729690e+00
-4.31499869e-01 -1.03433990e+00 -2.96258867e-01 8.45671654e-01
-1.68679750e+00 -7.99769759e-01 -9.03786421e-01 5.60712755e-01
3.68844450e-01 -6.54751388e-03 2.40760013e-01 3.58257681e-01
-2.00405970e-01 1.42253891e-01 1.42963007e-01 2.04303414e-01
7.79262841e-01 -1.33347130e+00 6.20831966e-01 8.59756172e-01
7.33821094e-02 3.85444134e-01 7.73766220e-01 -4.15869147e-01
-1.41848803e+00 -9.91407990e-01 9.33549345e-01 -5.34780681e-01
2.93543607e-01 -3.07250619e-01 -3.64145905e-01 1.02600324e+00
6.46849256e-03 1.76725417e-01 -2.96944588e-01 -2.89033473e-01
-2.28475347e-01 -3.24832857e-01 -1.00393939e+00 4.97971684e-01
1.06792855e+00 -8.01278412e-01 -6.68871164e-01 5.78896254e-02
6.98608279e-01 -9.90892053e-01 -5.52448332e-01 4.68536288e-01
7.27979004e-01 -1.40371931e+00 9.20442879e-01 -4.53427359e-02
3.68046701e-01 -5.04028499e-01 -2.24138796e-01 -1.40270627e+00
-2.66876578e-01 -2.89804816e-01 -1.43482283e-01 4.22034234e-01
-2.42020667e-01 -8.13759983e-01 1.01411283e+00 -8.94744415e-03
-7.92374238e-02 -5.31398237e-01 -1.08795190e+00 -1.02930617e+00
-1.50728121e-01 -1.33984923e-01 3.00770372e-01 7.30103254e-01
-2.09324792e-01 4.90588099e-01 -6.46993876e-01 4.77422625e-01
7.16710806e-01 1.32956043e-01 1.14486897e+00 -1.31628585e+00
-4.58694935e-01 2.39772961e-01 -9.91766930e-01 -1.88575053e+00
3.56782577e-04 -6.03149295e-01 2.02353731e-01 -1.44140792e+00
1.20517708e-01 1.52798623e-01 1.23484731e-01 -9.81822833e-02
4.62409317e-01 3.13525796e-01 2.10331768e-01 4.55992669e-01
-3.01226914e-01 7.01012075e-01 1.37446821e+00 6.55532852e-02
-2.20963120e-01 -4.26052921e-02 2.10978221e-02 8.65704536e-01
6.12035275e-01 -2.59235352e-01 -3.59712601e-01 -6.48525238e-01
2.71477342e-01 3.05033624e-01 5.60729146e-01 -1.28502905e+00
3.77353370e-01 -4.13133716e-03 5.42059898e-01 -1.07649350e+00
6.61211133e-01 -7.87126601e-01 1.66763335e-01 7.06938207e-01
1.81021735e-01 2.49196738e-01 -3.01812193e-03 4.47373182e-01
-5.12399495e-01 1.12115212e-01 1.09569013e+00 -9.72879604e-02
-1.09063339e+00 4.13431793e-01 8.85283723e-02 4.87991497e-02
7.92989552e-01 -2.37630397e-01 -3.98573905e-01 -6.24567449e-01
-6.80743933e-01 8.86845812e-02 9.15575981e-01 4.29146498e-01
7.70563364e-01 -1.68328428e+00 -1.72050759e-01 5.56632459e-01
3.93472373e-01 5.05831763e-02 1.48956120e-01 7.51313388e-01
-1.06874478e+00 1.00327110e+00 -5.44532061e-01 -1.04272974e+00
-1.21671295e+00 5.56556582e-01 7.39716530e-01 -2.87473679e-01
-6.60043001e-01 4.63769823e-01 5.68983674e-01 -8.39909613e-01
2.06472158e-01 -3.54274273e-01 -8.98237899e-02 -4.72995460e-01
2.41977513e-01 2.69430637e-01 9.10064504e-02 -8.40110004e-01
-4.80760247e-01 9.25280035e-01 2.01485693e-01 -3.08010727e-01
1.07876265e+00 -4.84777361e-01 8.10156316e-02 3.61570865e-01
1.49150801e+00 -1.78879902e-01 -1.69632030e+00 -5.44819474e-01
-2.91010112e-01 -6.63698494e-01 2.07069471e-01 -3.31508666e-01
-1.05387163e+00 1.02529883e+00 7.78549492e-01 -4.95885491e-01
9.63850617e-01 -1.89408883e-01 6.44486189e-01 5.65061212e-01
6.02283657e-01 -9.03779387e-01 1.00278035e-01 1.06251872e+00
9.85241234e-01 -1.37403226e+00 1.18103608e-01 -2.26174101e-01
-4.18908417e-01 9.91881967e-01 7.99749970e-01 -4.90552127e-01
7.16287911e-01 -2.13527605e-01 3.83008331e-01 -3.99511069e-01
-4.90142643e-01 -2.82598138e-01 4.56002295e-01 4.23074812e-01
6.44436032e-02 -1.40955985e-01 -1.91918492e-01 -2.21981257e-01
-2.51658261e-01 1.15180843e-01 3.75833958e-01 9.59271967e-01
-4.38365310e-01 -6.54372692e-01 -3.38265240e-01 -2.14175209e-01
-3.45685817e-02 2.66965389e-01 -5.34766436e-01 7.79584229e-01
3.55320387e-02 5.77580392e-01 1.69669151e-01 -5.23805380e-01
5.52199781e-01 -4.11208034e-01 5.01126289e-01 -5.83702624e-01
9.29889549e-03 -1.81783944e-01 -1.08315565e-01 -9.78103757e-01
-1.93310037e-01 -2.97026604e-01 -9.95185077e-01 -3.10941488e-01
1.65887445e-01 -2.51948655e-01 8.57922018e-01 9.79910195e-01
4.10940260e-01 1.24179721e-01 9.83911693e-01 -1.14530456e+00
-6.47806883e-01 -6.61957443e-01 -7.08794594e-01 3.29582453e-01
7.27057815e-01 -9.46763396e-01 -3.98865402e-01 -2.72188216e-01] | [8.05415153503418, -2.1975905895233154] |
13455ebe-aa26-4987-a914-61de0e66779b | schema-guided-user-satisfaction-modeling-for | 2305.16798 | null | https://arxiv.org/abs/2305.16798v1 | https://arxiv.org/pdf/2305.16798v1.pdf | Schema-Guided User Satisfaction Modeling for Task-Oriented Dialogues | User Satisfaction Modeling (USM) is one of the popular choices for task-oriented dialogue systems evaluation, where user satisfaction typically depends on whether the user's task goals were fulfilled by the system. Task-oriented dialogue systems use task schema, which is a set of task attributes, to encode the user's task goals. Existing studies on USM neglect explicitly modeling the user's task goals fulfillment using the task schema. In this paper, we propose SG-USM, a novel schema-guided user satisfaction modeling framework. It explicitly models the degree to which the user's preferences regarding the task attributes are fulfilled by the system for predicting the user's satisfaction level. SG-USM employs a pre-trained language model for encoding dialogue context and task attributes. Further, it employs a fulfillment representation layer for learning how many task attributes have been fulfilled in the dialogue, an importance predictor component for calculating the importance of task attributes. Finally, it predicts the user satisfaction based on task attribute fulfillment and task attribute importance. Experimental results on benchmark datasets (i.e. MWOZ, SGD, ReDial, and JDDC) show that SG-USM consistently outperforms competitive existing methods. Our extensive analysis demonstrates that SG-USM can improve the interpretability of user satisfaction modeling, has good scalability as it can effectively deal with unseen tasks and can also effectively work in low-resource settings by leveraging unlabeled data. | ['Gabriella Kazai', 'Emine Yilmaz', 'Nikolaos Aletras', 'Animesh Prasad', 'Yunlong Jiao', 'Yue Feng'] | 2023-05-26 | null | null | null | null | ['task-oriented-dialogue-systems'] | ['natural-language-processing'] | [ 0.1683778 0.26042747 -0.34057957 -0.9541179 -0.5202768 -0.24036759
0.51764125 0.20284894 -0.51210976 0.58183867 0.551256 -0.06851896
-0.1070813 -0.37660313 0.19238245 -0.18547675 0.41735533 1.1922768
-0.03222709 -0.82043874 0.3824455 -0.39319494 -1.4137475 0.6352698
1.0910239 1.1650611 0.48888832 0.51080054 -0.3766466 0.73953027
-0.673533 -0.5597137 -0.25241095 -0.15885186 -1.4757938 0.47664645
-0.24790226 -0.2604933 0.04733011 0.749835 0.40208632 0.46619982
0.78672934 -1.3341513 -0.388709 0.35286754 0.17707738 -0.11534373
0.8139118 0.0349497 1.3061179 -0.9291263 0.33791023 1.426822
0.32184014 0.80633825 -1.0533926 -0.0781497 0.1195762 0.19787343
-0.73888326 -0.48986244 0.7096797 -0.43816206 1.1959211 0.5864829
0.1944252 0.97201467 -0.0731292 1.0494151 1.0331631 -0.39422014
0.18332471 0.464417 0.6856805 0.49867973 -0.617869 -0.50559473
-0.65883756 -0.45501116 0.3592238 -0.1700171 -0.22228447 -0.25461358
-1.0425148 0.92835975 -0.07065621 0.3078575 -0.40161386 -0.519988
0.88552344 0.6247301 0.7570332 0.8573896 -1.0646747 -0.5771097
-0.1543645 0.14552379 1.1118475 1.321747 0.62310666 -0.19902223
-0.7998916 1.5130368 0.24157238 0.09963121 0.7121715 -1.1258755
0.39823058 1.119427 0.38254398 -0.5345057 -0.5948117 -0.18147829
-0.6175864 -0.59217775 0.10994028 -0.2109726 -0.43145743 1.8394569
0.01797049 -0.34241858 0.5468449 1.012921 1.2375957 0.45111027
0.38792482 -0.54369414 1.6300324 -0.9041164 -1.0314535 -0.466424
1.0061573 -0.7687562 1.6632825 0.25930515 -1.0612484 -0.55070263
-0.40216804 -0.06431052 -0.21952866 0.27965152 0.88120246 0.5057288
-0.92140526 0.20404594 -0.07179298 -0.5570984 -0.18155019 0.48183143
-0.09558178 -0.00872616 -1.621484 1.2213119 0.4075579 -0.2679104
-0.6202376 -0.25681725 -1.2339244 0.22129028 0.4809941 -0.7537797
1.7439011 -0.682052 -1.4317178 0.9401589 -0.48451945 -0.09225152
0.10184769 0.11325202 -0.41430393 -0.40361977 0.17146067 0.3878166
0.42950308 -1.0335788 -0.91708905 -0.54753715 0.42809266 0.9083852
-0.6451713 0.04900555 -0.74229306 -0.04251955 0.11202684 -0.6594932
-0.34758896 -0.8046978 -0.18594792 -1.1295036 0.55762273 -0.23386234
1.5024202 -1.9356586 0.25254333 -0.13952155 0.11079093 0.369215
-0.16068068 0.49940398 0.31358206 -0.110334 -0.15627564 -0.6647572
0.29760233 0.5129929 0.20603304 -0.22803734 0.10344531 0.8494249
-1.0424273 -0.46776605 0.21808578 0.02922902 -0.62554497 0.97219193
-0.33655858 0.34760147 -0.56169784 0.33531606 0.21847565 -0.27982792
0.39717478 -0.339805 0.29192647 0.6826902 -0.7195333 1.6837515
-0.8613135 0.13836141 0.06746142 -0.9156422 1.2424022 0.5743175
0.48758778 -0.9940452 0.26021567 0.10180256 -0.11614269 -0.9072968
0.7996656 -0.03839516 -0.64727145 0.5665639 0.29074314 -0.14750502
0.21587946 0.37253577 0.7555546 -0.2105175 0.5204167 -0.3378496
0.876249 -0.03511795 0.5665003 0.48901638 -0.39792624 0.04478098
0.5727614 -0.30552047 -0.6417395 -0.33749142 -0.1265356 1.9236146
0.21709056 -0.65632945 -0.72127813 -0.94001955 -0.2685538 1.00272
-0.49574384 -0.53209734 -0.16062021 -0.58612233 0.09685493 0.36244574
0.577012 -1.2261336 -0.3331235 0.3272868 -1.0218787 -1.220027
-0.6085432 0.14700648 -0.6362329 -0.9261625 -0.20455909 -0.86674255
0.5622766 0.32565063 1.5275236 0.18920657 0.27043906 0.564656
-0.5056707 -0.2773664 -0.40261972 0.08895347 0.23602375 0.07369763
0.8587698 -0.04603069 -0.25061354 0.85157794 -0.59086967 0.22520967
0.07824457 1.0908405 0.15940213 0.08318023 0.9595439 -1.4073347
1.320825 -0.57383996 0.24334563 0.33173817 -0.9616614 -0.02164757
0.32397684 -0.10628041 -1.345418 -0.16708633 -0.4750887 0.15604351
-0.3062189 0.706087 -0.33719742 0.45222104 0.54875636 0.15056863
0.05751373 -0.42678535 0.1054831 1.2624414 0.33521575 -0.826863
-0.02063148 -0.17833807 -0.5856632 -0.6905427 -1.2109363 -1.2063106
-0.5345859 -0.41827002 0.72036564 -0.6457492 -1.1626314 0.28452212
-1.155609 -0.262203 0.05250029 0.17459854 -0.8302833 0.3667781
-0.65448445 -1.1846511 -0.5562771 -1.2766627 1.1314979 0.02127817
-0.7852733 -1.4002665 -0.5288214 1.0084522 0.5007633 -0.36623234
1.1866271 -1.0415381 0.39838248 -0.08376551 -0.12352843 0.29184556
0.2700065 -0.85016495 -0.8887329 -0.36460623 0.48720825 -0.7896747
0.43159053 0.28677702 1.1183193 -0.546993 0.09150856 -0.07213641
0.81241584 0.20536414 0.5061275 0.05267848 0.36743528 1.0868102
1.5266186 0.7524774 0.89398277 0.94258195 0.41519973 -0.22454308
0.2623222 0.03562914 0.3633492 0.80441284 0.02253606 -0.22677669
-0.6412096 0.26917386 -2.1777327 -0.48824114 -0.45920426 2.1322033
1.1235249 0.17991787 0.2004116 0.095736 0.42494914 0.02745073
-0.54572135 -0.80284595 0.1399062 -0.20514421 -0.2178473 0.80516976
-0.95267695 1.3161949 5.6226854 0.6183232 -0.49107167 0.2824064
0.6560955 0.37922245 -0.2930918 -0.32636988 -0.72284204 0.21975958
0.67338794 -0.30072677 0.15881093 0.87337536 0.2564351 -0.0962977
-1.2831062 0.8010403 0.19934316 -0.5942681 -0.06905729 -0.21426448
0.18752989 -0.50227934 -0.11823766 0.9709803 0.3482615 -0.76157445
0.11138336 0.2873478 0.91316813 -0.6165404 1.2071677 0.9288936
-0.8440158 -0.02765776 -0.4999046 -0.28954387 0.10136856 0.1555514
-1.4139354 0.33626097 0.3678872 0.6294858 -0.38979664 0.21387663
-0.041892 0.46572542 0.27641883 -0.19369803 0.2675839 -0.1266819
0.38812062 1.4071416 -0.07981084 0.40314585 0.64901674 0.5156344
0.15192696 0.36941487 -0.4872619 0.19282468 0.41882604 1.3378215
0.12919551 -0.36719358 -0.30862212 1.099057 0.3349718 0.25984386
-0.48724845 0.03878405 0.7593489 -0.21331008 -0.5011134 0.01692327
-0.3857361 -1.0229485 -0.21271668 -0.9275996 0.79234976 -0.7377045
-1.2502531 0.7952015 -0.36766434 -1.1199461 -0.38214684 -0.41005293
-0.4328997 1.1338844 -1.4967059 -1.0895176 -0.3493202 0.7780539
1.3156203 -0.39982724 1.3504387 0.0086381 -0.64170945 0.5152362
-0.5865534 -0.20891958 0.9353118 -1.4908172 0.08600561 0.03610707
-0.3639927 0.48308223 0.8490829 -0.56527454 -1.2645216 -0.847297
1.5187621 -0.5686855 0.14653806 -0.23669294 -1.0307177 0.47938105
0.3508168 -0.7322019 1.1276306 0.7871438 -0.05332954 0.24224296
-1.2402296 0.23239651 0.9335919 -0.34307697 -0.81969404 0.678806
0.8047203 -0.4447308 -1.1687 0.48427418 0.10538986 -0.7466524
0.8242502 -1.247018 0.53477997 0.21450241 -0.39329064 -1.5931683
-0.6369058 -0.3579539 -0.10876695 1.2997439 0.5811525 -0.32145455
0.5341585 1.4903125 -0.49298742 -0.9744902 -0.655408 -0.26609448
-0.45609146 -0.4141855 0.686118 1.2417383 0.6360264 1.0977135
-0.6260312 -0.12475882 0.27126363 -0.01967996 0.6777326 -1.5139632
-0.1069497 -0.4052309 0.1899844 -1.2374982 0.46085677 -0.90003043
0.07112747 -1.8021832 0.26186728 -0.6334192 -0.27675954 0.6438987
-0.6565171 -0.2720784 -0.22777276 0.26519677 -1.1703112 0.5794433
1.2887582 -0.01654452 -0.3638818 0.4724394 -0.80216384 0.75861937
0.8808426 0.01093249 -0.5998811 -0.38054886 0.02746362 0.5663264
-0.2612995 -0.45742527 0.23644514 -0.4947206 -0.13977443 -0.1804595
0.6876426 -0.8622824 -0.4730449 0.23820189 -0.94271713 -0.14367053
-0.14770049 0.22824086 -0.20664404 -0.48860252 0.5918228 -0.10431797
-1.0385796 0.282656 -0.5108207 0.19200706 0.729435 0.06145779
-0.11534582 -0.70135105 -0.8757986 0.86133343 -0.00768803 0.7234812
0.77235365 -1.3369805 -0.74530077 0.15278791 0.7139973 -0.2091795
0.2719299 0.6072756 0.52673733 0.6088005 -0.06355825 -0.6408549
-1.6334884 0.17265108 0.13982423 -0.49702856 -0.01810123 0.7850122
0.30044913 -0.93396634 0.50229573 0.21483351 -0.9592004 0.14569134
0.21893711 0.13667375 0.14799091 -0.8476288 -0.06062482 -0.03526251
-0.1299712 0.038293 1.1924875 -0.4520575 -0.12820718 0.63864857
0.9304651 -0.5893812 -0.8092293 -0.9445036 0.22194034 -0.5295416
0.04000594 -1.2101355 -0.7777358 0.8444604 0.16762958 0.55739844
1.2505808 0.08485048 0.7989514 0.48112264 0.58017635 -1.4604249
0.4518213 1.1116852 1.0978054 -1.5821898 -0.5665693 -0.5823404
-1.5466523 0.80723345 1.2656381 0.76713973 0.28546315 -0.12688753
0.18434763 -0.4030242 -1.2007489 -0.3805347 0.53175277 0.43581453
0.9633441 0.4015617 -0.64112884 1.1407465 -0.17622757 -0.3487459
0.21788853 0.6205529 -0.73038405 -1.3795373 0.16980326 0.8107091
-0.15415306 -0.10070518 -0.6636886 0.05830452 -0.22263156 1.45379
-0.31532514 -0.6784997 1.0137771 0.4239681 -0.03940851 -1.1336157
-1.0244768 -0.08157641 0.7680283 -0.49466625 -0.25259262 -0.4362205
-1.2757162 -0.17578182 -0.4440829 0.61637175 0.5139121 0.9978019
0.3722259 0.4922851 0.9677422 -0.1544234 -0.73799187 -1.3723756
-0.43579495 1.0784918 -0.13298126 -0.74032176 -0.06869528 -0.1361922 ] | [12.75547981262207, 7.942605018615723] |
c5e53ccd-cc5e-4e27-8430-5fb54dc25de1 | single-stage-visual-query-localization-in | 2306.09324 | null | https://arxiv.org/abs/2306.09324v1 | https://arxiv.org/pdf/2306.09324v1.pdf | Single-Stage Visual Query Localization in Egocentric Videos | Visual Query Localization on long-form egocentric videos requires spatio-temporal search and localization of visually specified objects and is vital to build episodic memory systems. Prior work develops complex multi-stage pipelines that leverage well-established object detection and tracking methods to perform VQL. However, each stage is independently trained and the complexity of the pipeline results in slow inference speeds. We propose VQLoC, a novel single-stage VQL framework that is end-to-end trainable. Our key idea is to first build a holistic understanding of the query-video relationship and then perform spatio-temporal localization in a single shot manner. Specifically, we establish the query-video relationship by jointly considering query-to-frame correspondences between the query and each video frame and frame-to-frame correspondences between nearby video frames. Our experiments demonstrate that our approach outperforms prior VQL methods by 20% accuracy while obtaining a 10x improvement in inference speed. VQLoC is also the top entry on the Ego4D VQ2D challenge leaderboard. Project page: https://hwjiang1510.github.io/VQLoC/ | ['Kristen Grauman', 'Santhosh Kumar Ramakrishnan', 'Hanwen Jiang'] | 2023-06-15 | null | null | null | null | ['temporal-localization'] | ['computer-vision'] | [-7.37362206e-01 -5.04747331e-01 -5.93213797e-01 -2.91926235e-01
-8.05505872e-01 -6.65861487e-01 5.28961599e-01 6.27771989e-02
-4.82271522e-01 3.67037207e-01 3.80495846e-01 1.16314486e-01
6.49950802e-02 -4.64306295e-01 -9.66588259e-01 -5.49966916e-02
-2.57161379e-01 3.87985140e-01 6.64356232e-01 3.25947315e-01
1.57208636e-01 4.09714848e-01 -1.66253924e+00 2.45167643e-01
1.98416501e-01 1.06103742e+00 5.17641366e-01 1.06368780e+00
1.68955222e-01 1.16735816e+00 -1.46205291e-01 -1.20803393e-01
4.43109497e-02 -1.27069876e-01 -9.91638601e-01 -1.18046723e-01
9.97826457e-01 -7.31697023e-01 -1.08635020e+00 8.77865732e-01
6.17381096e-01 3.31854582e-01 -2.74653994e-02 -1.41888404e+00
-6.52752519e-01 1.80887505e-01 -2.38692313e-01 8.26566100e-01
5.59235096e-01 3.46776664e-01 1.08541775e+00 -1.38514805e+00
1.10199785e+00 1.15697718e+00 5.49591839e-01 3.02287817e-01
-1.09285152e+00 -4.94629681e-01 2.35149980e-01 8.04836571e-01
-1.87374914e+00 -8.69153440e-01 3.67171466e-01 -4.66459006e-01
1.38487959e+00 -1.45036235e-01 9.75113094e-01 8.13537598e-01
6.78552911e-02 1.39651167e+00 4.09657121e-01 1.71949461e-01
1.44446969e-01 -3.89151067e-01 3.21473107e-02 9.90026891e-01
-1.21885359e-01 -2.90342257e-03 -1.21243954e+00 1.40909374e-01
1.06358969e+00 1.93694066e-02 -1.46705195e-01 -7.27166295e-01
-1.56372643e+00 5.53029060e-01 6.65788293e-01 6.51019216e-02
-4.33002621e-01 1.01472127e+00 4.12340581e-01 2.13378251e-01
2.11572766e-01 -1.32839587e-02 -1.36172727e-01 -4.19214100e-01
-1.25048268e+00 6.17825210e-01 4.53993171e-01 1.38601589e+00
7.88753271e-01 -1.02150701e-01 -5.00562608e-01 3.09165061e-01
3.83532286e-01 5.76628208e-01 8.66853148e-02 -1.45295262e+00
3.52194220e-01 3.27514231e-01 3.80783767e-01 -9.17224824e-01
-2.09035724e-01 -2.57612258e-01 -3.97376418e-02 -1.23628311e-01
2.25084215e-01 2.83006132e-01 -7.63156116e-01 1.71446550e+00
6.23979807e-01 6.41593993e-01 -1.74087331e-01 1.20189357e+00
9.75467920e-01 3.98286104e-01 2.58034348e-01 1.95256367e-01
1.40254724e+00 -1.20973980e+00 -6.86623812e-01 -2.67721504e-01
5.23442805e-01 -6.02657735e-01 9.41429436e-01 -1.41828120e-01
-1.39907384e+00 -6.81508422e-01 -8.62249613e-01 -6.29022837e-01
-2.26887286e-01 2.45190009e-01 5.82198858e-01 -6.72283769e-02
-1.41517627e+00 9.85776037e-02 -1.16629195e+00 -4.67388302e-01
5.18697262e-01 1.74842313e-01 -4.60544109e-01 -2.16973156e-01
-1.08662570e+00 6.43455625e-01 3.73961478e-01 -8.30497667e-02
-1.60333753e+00 -8.36422563e-01 -9.36333239e-01 3.53163644e-03
5.33548534e-01 -9.52811599e-01 1.50032294e+00 -3.72987509e-01
-8.76145124e-01 9.21529353e-01 -6.54635966e-01 -6.32665515e-01
4.95419562e-01 -5.51808774e-01 -1.35418892e-01 6.99171782e-01
3.83317739e-01 1.00177908e+00 7.13489950e-01 -6.90227985e-01
-8.55245054e-01 -3.25793803e-01 2.33699501e-01 3.70286673e-01
6.74854815e-02 1.64186805e-02 -1.39419854e+00 -4.39899355e-01
2.56257027e-01 -8.59943688e-01 3.45292240e-01 5.86113155e-01
-2.26351954e-02 -5.08814275e-01 1.03113317e+00 -5.34473121e-01
1.15470266e+00 -2.13971901e+00 3.71995755e-02 -1.38074100e-01
4.73958313e-01 -2.80732531e-02 5.86043932e-02 3.77698243e-01
4.07145828e-01 -3.53276998e-01 3.62585098e-01 -7.31154025e-01
1.70565128e-01 4.94616106e-02 -4.13238525e-01 7.16229737e-01
-3.75735015e-02 1.51431990e+00 -1.30844700e+00 -8.61663282e-01
3.64600778e-01 6.57437742e-01 -6.45670354e-01 2.62009591e-01
-3.98840994e-01 2.09795073e-01 -4.46665168e-01 1.02281630e+00
2.70104319e-01 -6.02081716e-01 -1.06327631e-01 -4.04716402e-01
-1.61763519e-01 3.48857760e-01 -9.95971501e-01 2.38511777e+00
-6.81820586e-02 1.02490747e+00 1.13152139e-01 -7.18369484e-01
4.21415925e-01 3.13796878e-01 6.02759600e-01 -7.68248618e-01
-1.44030541e-01 -4.07905281e-02 -7.58451283e-01 -6.14793003e-01
6.75278008e-01 5.19120097e-01 3.68265323e-02 2.79590636e-01
4.83708680e-01 2.28921711e-01 2.82212675e-01 6.36759698e-01
1.13700151e+00 5.53240180e-01 8.56476128e-02 -6.83093444e-02
1.72674283e-01 1.99757338e-01 4.79573816e-01 9.01441574e-01
-6.01443768e-01 5.78070760e-01 3.03389937e-01 -4.18672919e-01
-1.00697505e+00 -1.37564516e+00 6.18828572e-02 1.26627696e+00
5.30944943e-01 -7.00432420e-01 -4.38323319e-01 -4.22630876e-01
1.61109850e-01 4.40974474e-01 -5.62137485e-01 3.11453473e-02
-5.08868039e-01 -1.31080020e-02 7.14555979e-01 8.36301088e-01
7.06566453e-01 -1.06671238e+00 -9.87554073e-01 2.46013135e-01
-4.94031399e-01 -1.38723409e+00 -8.22985590e-01 -2.78555840e-01
-7.23040342e-01 -1.26088142e+00 -6.78698242e-01 -7.98075676e-01
2.61171460e-01 6.40264034e-01 1.39534485e+00 3.04483566e-02
-3.51998657e-01 9.87164915e-01 -1.54313669e-01 -3.24487500e-02
4.11414415e-01 -8.64839181e-02 1.83139205e-01 -1.67205647e-01
6.21131063e-01 -3.58580440e-01 -1.15510738e+00 3.04456323e-01
-4.47959870e-01 -7.43830577e-02 2.77892411e-01 5.00829577e-01
1.12467623e+00 -5.63370943e-01 2.68119812e-01 -1.58458769e-01
7.92873353e-02 -5.56118131e-01 -7.73777306e-01 3.37715596e-01
-3.54858249e-01 -1.41998529e-01 -2.25883141e-01 -2.18647525e-01
-6.88198864e-01 3.20663899e-01 1.27287343e-01 -1.18669963e+00
9.80958268e-02 3.49132448e-01 1.74681824e-02 1.03070671e-02
4.01674718e-01 5.89158416e-01 -2.00965226e-01 -3.55749488e-01
5.96245944e-01 4.25281674e-02 1.04720235e+00 -3.27825516e-01
5.44637084e-01 7.84364343e-01 -3.95061433e-01 -7.57212222e-01
-7.64940500e-01 -8.96802068e-01 -7.41316915e-01 -4.51651186e-01
1.21774459e+00 -1.54262221e+00 -1.02059102e+00 2.11990952e-01
-1.10626173e+00 -6.71802700e-01 -7.11490065e-02 7.00103760e-01
-7.76024640e-01 2.65111536e-01 -6.78830504e-01 -3.71379405e-01
-3.37890565e-01 -1.03872621e+00 1.45055842e+00 1.55208513e-01
-7.69298077e-02 -9.00871992e-01 2.85178840e-01 2.37374619e-01
2.09176749e-01 -1.17739864e-01 1.93557173e-01 -1.12726606e-01
-1.29394317e+00 -1.94951788e-01 -4.49714422e-01 -2.83888578e-01
-4.15466756e-01 -2.39513248e-01 -8.76718044e-01 -5.08734882e-01
-2.65659124e-01 -4.88078505e-01 1.01104879e+00 5.00617921e-01
1.03270745e+00 -6.37177937e-03 -5.09936512e-01 9.82041717e-01
1.38981164e+00 -2.78704286e-01 4.79174286e-01 3.20912123e-01
7.73453414e-01 1.24354713e-01 8.60474169e-01 4.09481257e-01
9.24556613e-01 9.17516112e-01 5.22131085e-01 2.52121061e-01
-4.41784620e-01 -5.92973709e-01 4.32575166e-01 3.37745816e-01
1.19365551e-01 -1.04599573e-01 -9.04281437e-01 9.97299135e-01
-2.05225611e+00 -1.37123299e+00 1.35623410e-01 2.03396082e+00
5.25599360e-01 -9.18969586e-02 2.19460160e-01 -5.90877652e-01
5.32416224e-01 4.37325388e-01 -8.02411437e-01 4.21080947e-01
-1.03587970e-01 -1.03085689e-01 4.69858259e-01 5.82294762e-01
-1.33168519e+00 1.35449195e+00 6.27698755e+00 4.02454764e-01
-1.02772391e+00 3.60420585e-01 1.54860402e-02 -7.98537552e-01
7.60448575e-02 1.38488695e-01 -1.00069332e+00 2.59434700e-01
6.58722997e-01 -3.13963979e-01 4.34170634e-01 1.05643404e+00
2.81809986e-01 -2.66562790e-01 -1.27862048e+00 1.56003034e+00
1.97226197e-01 -1.67354190e+00 -2.08676547e-01 -7.27949068e-02
4.63929743e-01 7.37211168e-01 -2.96140704e-02 2.87913173e-01
1.09031923e-01 -7.81500041e-01 1.03504038e+00 7.41521835e-01
7.59113193e-01 -5.11073768e-01 2.99477518e-01 3.26230656e-03
-1.76427972e+00 1.00512326e-01 -5.53332567e-01 1.59902140e-01
4.27970320e-01 1.25576809e-01 -6.85083091e-01 7.71626309e-02
1.19338405e+00 1.02591372e+00 -7.80460358e-01 1.30146098e+00
-2.25647986e-01 3.20570558e-01 -3.11531305e-01 1.75324261e-01
3.37849915e-01 3.22896004e-01 6.78086936e-01 1.24506426e+00
3.09266001e-01 2.70962387e-01 3.13299090e-01 8.23077142e-01
-1.81990981e-01 -2.16882110e-01 -6.53328001e-01 -8.02321453e-03
8.74153078e-01 1.01341832e+00 -5.56467593e-01 -6.86182916e-01
-5.59381902e-01 1.17834377e+00 6.04196429e-01 5.43807864e-01
-1.12225854e+00 -2.21540228e-01 1.01166773e+00 1.25879109e-01
8.42984200e-01 -5.48303545e-01 2.54786670e-01 -1.34426630e+00
1.23383880e-01 -4.27147716e-01 4.46840912e-01 -1.07689512e+00
-7.62721419e-01 2.22919270e-01 5.62121347e-03 -1.09915066e+00
-2.81997979e-01 -6.74909055e-02 -3.81267667e-01 5.13059318e-01
-1.35390270e+00 -1.27649069e+00 -8.28716040e-01 1.12617326e+00
6.28437877e-01 9.46109667e-02 5.48148036e-01 5.33450127e-01
-2.86565036e-01 5.98205984e-01 -2.38504540e-02 3.24090332e-01
7.71474898e-01 -1.08408237e+00 7.08527148e-01 8.82921100e-01
5.13371468e-01 6.51293099e-01 4.59452689e-01 -7.91870832e-01
-1.88544667e+00 -1.19614553e+00 1.00697732e+00 -9.47216511e-01
6.10677421e-01 -5.19936264e-01 -8.05261254e-01 1.03365123e+00
1.01113953e-01 5.58549464e-01 2.65647084e-01 -6.73065707e-02
-4.06224191e-01 -1.81043916e-03 -6.04347527e-01 4.43543196e-01
1.42963612e+00 -1.16267717e+00 -5.53966999e-01 3.87513191e-01
7.50380993e-01 -6.94625616e-01 -8.63614261e-01 -2.36646663e-02
6.85369134e-01 -9.68664408e-01 1.34634340e+00 -4.97988582e-01
-2.93811155e-03 -7.60857344e-01 -2.88623661e-01 -5.32886922e-01
-3.44391316e-01 -4.57587063e-01 -7.99078047e-01 8.40233088e-01
-4.87609990e-02 -6.04311340e-02 9.49722528e-01 5.40450394e-01
-7.45021477e-02 -5.46493828e-01 -9.92700696e-01 -7.65969157e-01
-6.64969623e-01 -6.16564989e-01 2.00831756e-01 6.65437043e-01
-1.02756239e-01 2.96907276e-01 -4.95198727e-01 2.53696948e-01
9.13760841e-01 2.72017539e-01 1.08804595e+00 -6.43311441e-01
-2.48070255e-01 -1.80207253e-01 -6.77673519e-01 -1.68962967e+00
-1.22766100e-01 -8.68492544e-01 1.60377305e-02 -1.75885463e+00
1.88960955e-01 -1.51971519e-01 -3.36274624e-01 4.07004356e-01
-4.24296670e-02 5.21238148e-01 2.67168403e-01 5.09055555e-01
-1.49548495e+00 6.00189745e-01 9.79815006e-01 -1.27698213e-01
-2.50058234e-01 -3.60684544e-01 -6.50077909e-02 3.19534183e-01
3.89631271e-01 -3.32390130e-01 -7.13802099e-01 -9.85282362e-01
8.45433176e-02 1.18451528e-01 9.98666644e-01 -1.25414491e+00
8.08663607e-01 1.09645732e-01 5.86391568e-01 -1.15513492e+00
7.92719007e-01 -3.50691438e-01 1.08947225e-01 4.28106636e-01
-1.25662312e-01 5.32135844e-01 8.81036893e-02 8.51339042e-01
-2.65957445e-01 3.29248577e-01 4.14551318e-01 -1.83269352e-01
-1.59203100e+00 7.51096845e-01 -1.43544137e-01 3.51305902e-01
1.14219499e+00 -8.44046623e-02 -3.27562511e-01 -5.48894703e-01
-8.21539760e-01 6.63183749e-01 6.56351089e-01 6.25760019e-01
9.33533132e-01 -1.42112899e+00 -5.17988503e-01 -1.62668094e-01
4.16877598e-01 -1.25085637e-01 4.96700823e-01 1.09331393e+00
-7.08713412e-01 7.86594748e-01 -3.54040973e-02 -1.08836961e+00
-1.32628691e+00 7.10161328e-01 2.95459390e-01 2.95115918e-01
-9.63457227e-01 1.20036232e+00 3.28399122e-01 1.05905496e-01
5.86204886e-01 -1.81019962e-01 6.85427189e-02 -3.59051628e-03
7.59019256e-01 3.03644598e-01 -3.50400984e-01 -8.08292031e-01
-7.09634304e-01 5.05529106e-01 2.53840555e-02 -2.73610771e-01
1.06051588e+00 -4.33261275e-01 1.45814627e-01 3.25730294e-01
1.45643389e+00 -4.14137363e-01 -1.61575139e+00 -5.85916936e-01
5.84628759e-03 -7.40517437e-01 2.87883520e-01 -2.71264970e-01
-9.23698485e-01 7.04923034e-01 7.40171313e-01 -4.22858804e-01
7.90528238e-01 4.66492683e-01 8.15128684e-01 5.83636880e-01
5.29029131e-01 -1.05858803e+00 4.27072734e-01 4.68747109e-01
7.44866610e-01 -1.21725500e+00 1.22001715e-01 6.71136454e-02
-5.61196566e-01 6.87220931e-01 7.14728415e-01 -2.41915986e-01
5.59005678e-01 -1.20959207e-01 -9.08301845e-02 -6.28012419e-01
-9.90356922e-01 -4.43033308e-01 3.68343383e-01 4.07124847e-01
1.10220581e-01 -2.31301337e-01 1.20982528e-01 3.01953051e-02
1.26003370e-01 1.90160736e-01 -5.96315488e-02 1.06438601e+00
-4.62201625e-01 -6.12281978e-01 -2.64784191e-02 7.19553232e-02
-2.26658598e-01 -1.62067905e-01 -1.18241958e-01 8.93329144e-01
-1.59633026e-01 6.15814090e-01 4.06572759e-01 -2.73914427e-01
2.68325478e-01 1.06479101e-01 5.84480107e-01 -3.04530710e-01
-1.42476454e-01 1.75617620e-01 -9.97655168e-02 -1.42247307e+00
-5.16786277e-01 -7.90914237e-01 -1.36896276e+00 -4.25203592e-01
1.26228705e-01 -2.67018788e-02 5.29960036e-01 6.22511744e-01
8.22456062e-01 2.32258528e-01 -8.34279135e-03 -9.48643506e-01
-7.92829990e-02 -6.14944398e-01 -1.25257418e-01 3.38097900e-01
5.78504682e-01 -9.18763101e-01 8.28262642e-02 1.76247329e-01] | [8.632163047790527, 0.3533104956150055] |
531f6b98-7a5f-4ccc-81ff-ea27bc6a6622 | multilingual-ner-transfer-for-low-resource | 1902.00193 | null | https://arxiv.org/abs/1902.00193v4 | https://arxiv.org/pdf/1902.00193v4.pdf | Massively Multilingual Transfer for NER | In cross-lingual transfer, NLP models over one or more source languages are applied to a low-resource target language. While most prior work has used a single source model or a few carefully selected models, here we consider a `massive' setting with many such models. This setting raises the problem of poor transfer, particularly from distant languages. We propose two techniques for modulating the transfer, suitable for zero-shot or few-shot learning, respectively. Evaluating on named entity recognition, we show that our techniques are much more effective than strong baselines, including standard ensembling, and our unsupervised method rivals oracle selection of the single best individual model. | ['Afshin Rahimi', 'Yuan Li', 'Trevor Cohn'] | 2019-02-01 | massively-multilingual-transfer-for-ner | https://aclanthology.org/P19-1015 | https://aclanthology.org/P19-1015.pdf | acl-2019-7 | ['low-resource-named-entity-recognition'] | ['natural-language-processing'] | [ 1.61255583e-01 9.37316269e-02 -6.21060669e-01 -4.23786044e-01
-1.75670409e+00 -6.73791885e-01 9.48583782e-01 -1.52035639e-01
-7.52460361e-01 9.09414351e-01 4.03534234e-01 -3.77696693e-01
1.80406824e-01 -4.96845871e-01 -8.33292544e-01 -5.97455800e-01
-3.90961654e-02 8.78973424e-01 2.84820586e-01 -3.35091203e-01
-5.53042069e-02 1.91331401e-01 -8.86350870e-01 1.60088181e-01
9.29379404e-01 3.44349027e-01 1.13359183e-01 4.74794090e-01
-5.55671036e-01 5.56162834e-01 -5.16905725e-01 -9.87551928e-01
2.30709568e-01 -5.82951188e-01 -9.69445884e-01 -2.16880828e-01
5.26490867e-01 4.79366146e-02 -4.12127152e-02 1.06032240e+00
8.04483235e-01 2.49034882e-01 7.69707859e-01 -1.13103342e+00
-8.63345027e-01 1.05070674e+00 -4.36938763e-01 2.64613777e-01
1.05995893e-01 6.52522743e-02 1.23997128e+00 -1.09213710e+00
7.17710733e-01 1.24983168e+00 6.95132792e-01 8.17199409e-01
-1.59641588e+00 -6.34116530e-01 3.25914025e-02 -1.36985660e-01
-1.49861896e+00 -1.09127426e+00 2.91150600e-01 -3.18669945e-01
1.13612282e+00 -2.10450068e-01 -1.86565071e-02 1.39344263e+00
-3.32757756e-02 9.11557317e-01 1.13361228e+00 -7.67263770e-01
2.12693796e-01 4.99173522e-01 4.16898169e-02 3.98456126e-01
1.69550732e-01 8.96609426e-02 -7.35308707e-01 -5.07770121e-01
5.09083986e-01 -4.71283883e-01 -1.15690462e-01 -4.87329692e-01
-1.38618374e+00 9.45110142e-01 1.56464621e-01 5.18120050e-01
-2.08825558e-01 6.54279366e-02 3.47160131e-01 4.95784074e-01
7.63958633e-01 5.99812508e-01 -1.00981188e+00 -3.02510500e-01
-9.60456252e-01 -1.58764705e-01 1.14502144e+00 1.27385724e+00
9.79852796e-01 -8.95186067e-02 -1.65049002e-01 1.10654259e+00
7.30349123e-03 3.78005862e-01 5.53316176e-01 -5.20580232e-01
6.04526341e-01 -9.87387598e-02 2.64656752e-01 -7.61877298e-02
7.09380955e-02 -7.67177716e-02 -5.72193801e-01 -2.07714424e-01
3.60505104e-01 -6.18212700e-01 -9.58669186e-01 2.05407810e+00
2.34380886e-01 4.91826981e-01 4.73091543e-01 2.68574446e-01
3.46157521e-01 7.03382254e-01 6.52012289e-01 -2.73799896e-01
1.25863624e+00 -1.24833882e+00 -5.82562327e-01 -6.30281985e-01
7.94272244e-01 -7.94198811e-01 1.09921563e+00 1.11282349e-01
-1.03127921e+00 -2.86358744e-01 -5.71586370e-01 -3.36037502e-02
-4.84396398e-01 -1.36564476e-02 7.55471289e-01 6.72951341e-01
-1.27294946e+00 6.94901764e-01 -7.77527630e-01 -6.65321231e-01
3.67502511e-01 2.09840566e-01 -5.50478339e-01 -5.65921739e-02
-1.47341681e+00 1.34714496e+00 4.83381003e-01 -3.27085286e-01
-9.53822792e-01 -9.29463148e-01 -8.93889904e-01 -7.94334859e-02
1.11751147e-01 -7.35123098e-01 1.50606823e+00 -1.13798654e+00
-1.60933030e+00 1.11673355e+00 -2.85219222e-01 -5.63299716e-01
3.53600949e-01 -4.65738833e-01 -4.11852211e-01 -1.51327670e-01
1.59369484e-01 8.36357534e-01 5.98721206e-01 -1.06519151e+00
-4.42089438e-01 -8.95956066e-03 -2.01026071e-02 3.72045040e-01
-4.53780204e-01 5.82426131e-01 -4.63697761e-01 -4.97015208e-01
-5.63190877e-01 -7.07014978e-01 -4.73439902e-01 -2.77653784e-01
-2.17998162e-01 -4.41586882e-01 7.05539957e-02 -5.63244343e-01
1.00797200e+00 -2.06590939e+00 1.67218909e-01 -2.56672025e-01
-4.55147862e-01 3.36877853e-01 -4.75151449e-01 7.00305998e-01
-6.44142553e-02 3.91625941e-01 -3.55205536e-01 -5.09614587e-01
3.22273932e-02 1.15290746e-01 -3.82804126e-01 3.51054430e-01
3.71110618e-01 9.37768877e-01 -1.02917600e+00 -6.08217180e-01
-9.01200026e-02 5.69155335e-01 -4.74650830e-01 3.72356236e-01
-1.46397635e-01 3.56624484e-01 -2.73500413e-01 3.08825284e-01
3.01071405e-01 -3.17416638e-01 1.49786904e-01 1.58316344e-01
1.11638337e-01 8.58310282e-01 -9.00337338e-01 2.12898064e+00
-8.50400448e-01 1.53982997e-01 -3.09146866e-02 -5.89944184e-01
8.23774159e-01 7.10947335e-01 3.04617256e-01 -2.29806736e-01
-2.05056950e-01 3.60867172e-01 4.66078334e-03 -2.09027186e-01
2.67292887e-01 -8.38448942e-01 -2.38724709e-01 7.04784572e-01
8.13900411e-01 3.43652405e-02 -6.69722930e-02 2.76110858e-01
1.06135535e+00 4.26916510e-01 6.98061287e-01 -3.45063597e-01
4.78990339e-02 7.74244145e-02 4.55263853e-01 8.42181981e-01
-5.64675391e-01 5.00813842e-01 2.15375692e-01 7.71714896e-02
-1.15560365e+00 -1.21018076e+00 -2.82413185e-01 1.82599306e+00
-8.74486342e-02 -2.33935490e-01 -5.99875093e-01 -8.69487703e-01
-1.53869465e-01 1.11934423e+00 -4.34083581e-01 -2.43417934e-01
-4.83913124e-01 -9.00400639e-01 8.45077038e-01 4.12302345e-01
6.12572692e-02 -1.22911060e+00 5.57435229e-02 2.82568276e-01
-8.26596096e-02 -9.35521543e-01 -6.65665686e-01 5.96999764e-01
-7.57146537e-01 -3.78546596e-01 -8.82805645e-01 -9.82056022e-01
2.79980868e-01 6.89494163e-02 1.59716535e+00 -4.44735885e-01
2.64867693e-01 3.01283002e-01 -2.97600657e-01 -3.16867828e-01
-5.34794629e-01 5.80319941e-01 1.90086797e-01 -7.24332556e-02
8.59848678e-01 -5.68881392e-01 -9.59736556e-02 -9.63030607e-02
-5.36842227e-01 -1.03608288e-01 8.72494817e-01 9.38887179e-01
2.14555040e-01 -5.16211212e-01 8.43757272e-01 -1.31630313e+00
5.33578098e-01 -7.79156268e-01 -2.35546693e-01 5.77034235e-01
-4.40639615e-01 1.80726528e-01 5.85122287e-01 -5.36535323e-01
-1.49096525e+00 6.40178425e-03 -2.83395350e-01 -4.01828647e-01
-4.85064536e-01 3.34550589e-01 -3.04697752e-01 1.26000822e-01
9.09625828e-01 1.83362216e-01 -4.62104917e-01 -7.73018479e-01
7.94898093e-01 6.08785272e-01 2.41248801e-01 -8.12608540e-01
8.49364281e-01 1.10762909e-01 -8.74659240e-01 -7.09619343e-01
-1.04810667e+00 -7.37919748e-01 -1.11536694e+00 3.35893065e-01
7.41388023e-01 -1.31482565e+00 2.02409983e-01 2.20458627e-01
-1.36624229e+00 -6.19317472e-01 -3.72301996e-01 5.81070125e-01
-5.44872165e-01 4.37561274e-02 -9.76268232e-01 -7.24367499e-01
-3.74735415e-01 -7.44947493e-01 1.19523716e+00 -3.49774468e-03
-2.29031548e-01 -1.42160487e+00 7.94543624e-01 -1.22928850e-01
5.29090464e-01 -4.70952392e-01 8.46555352e-01 -1.36598086e+00
-2.24195912e-01 -2.91781742e-02 7.87226781e-02 3.82441193e-01
1.67657405e-01 -1.79562747e-01 -1.17086267e+00 -4.21875387e-01
-1.71121255e-01 -7.50252426e-01 7.60214984e-01 4.41210680e-02
4.15135622e-01 -2.40931928e-01 -4.82522190e-01 4.29317474e-01
1.60875094e+00 -3.95049676e-02 4.40890878e-01 1.61955729e-01
6.72267675e-01 5.25656641e-01 3.44189197e-01 -8.94001499e-02
3.19767654e-01 6.36160970e-01 -3.92163038e-01 -2.58442789e-01
-6.01310246e-02 -4.72216278e-01 8.68368208e-01 1.25901473e+00
1.32852152e-01 -1.44372553e-01 -1.20490038e+00 8.94625962e-01
-1.46379983e+00 -8.97379637e-01 5.94259679e-01 2.37405849e+00
1.42624032e+00 7.56299570e-02 2.10976526e-02 -8.43437970e-01
9.22395825e-01 2.37697065e-01 -3.55902970e-01 -2.17501000e-01
-2.01132253e-01 6.65856779e-01 5.23557246e-01 6.71941936e-01
-1.24375534e+00 1.50363111e+00 7.30342770e+00 9.82949078e-01
-8.93582344e-01 6.27606452e-01 5.28508306e-01 -5.58111584e-03
-4.91708279e-01 3.08016896e-01 -1.09544098e+00 2.01259241e-01
1.64500451e+00 -5.87900162e-01 2.14147434e-01 9.87876534e-01
-3.07461083e-01 3.47858608e-01 -1.33592272e+00 4.87928182e-01
1.85612753e-01 -8.48539233e-01 1.93829432e-01 -1.42822087e-01
1.01124215e+00 7.11209178e-01 -2.81361908e-01 7.87662923e-01
1.24087656e+00 -8.58496845e-01 3.79357219e-01 2.67341048e-01
8.89601648e-01 -6.60996675e-01 3.96782935e-01 3.94860357e-01
-9.26615119e-01 4.90403801e-01 -5.61792195e-01 3.30113411e-01
4.41897333e-01 2.25845307e-01 -7.66898632e-01 4.64268357e-01
3.57659131e-01 5.42526543e-01 -6.09379947e-01 1.02617955e+00
-3.33182782e-01 9.11014616e-01 -3.23738992e-01 7.23429024e-02
3.28715086e-01 -9.35788676e-02 3.66769135e-01 1.63660920e+00
1.70884311e-01 -1.28957689e-01 2.52703607e-01 4.58147138e-01
-3.66115659e-01 6.18880451e-01 -1.03789032e+00 -1.05181359e-01
5.71094632e-01 1.20097816e+00 -3.48834008e-01 -7.85881937e-01
-8.54078948e-01 1.19092619e+00 8.80385578e-01 4.98304009e-01
-6.13612354e-01 -3.84654343e-01 5.78788161e-01 -3.27872336e-01
4.49620724e-01 -3.08594108e-02 -3.55139561e-02 -1.69512188e+00
-2.77128369e-01 -9.36239243e-01 5.44745624e-01 -4.48174715e-01
-1.92455423e+00 6.75122321e-01 -1.16537750e-01 -9.42063034e-01
-3.33814263e-01 -4.36755896e-01 -7.86142886e-01 1.04866540e+00
-1.51570272e+00 -1.18742025e+00 5.94494700e-01 5.62248826e-01
7.10426033e-01 -1.45343557e-01 1.24426818e+00 4.41123158e-01
-3.73317897e-01 6.12487018e-01 1.54296562e-01 3.23115379e-01
1.30319238e+00 -1.36254656e+00 8.32038760e-01 1.03833199e+00
7.41613805e-01 9.15219307e-01 5.47531307e-01 -4.81895119e-01
-1.19396949e+00 -1.13269424e+00 1.43825114e+00 -8.43892097e-01
9.72506166e-01 -5.83245039e-01 -1.12889183e+00 1.27597475e+00
6.88426077e-01 -8.89294893e-02 1.13376391e+00 6.71605825e-01
-5.46795249e-01 1.29242748e-01 -8.84526134e-01 6.46927595e-01
9.18952823e-01 -7.84913659e-01 -1.02336717e+00 4.59573776e-01
9.70616579e-01 1.14243776e-01 -1.01399755e+00 2.07590908e-01
2.09597513e-01 -5.50420284e-01 8.65352452e-01 -1.34637165e+00
2.58740425e-01 1.26484409e-01 -5.38871400e-02 -1.63425684e+00
-2.54399151e-01 -7.54695952e-01 1.11283518e-01 1.62612426e+00
9.38282371e-01 -5.38025558e-01 4.24668342e-01 5.55933118e-01
1.48373609e-02 -2.96438098e-01 -9.82837617e-01 -9.32692528e-01
7.71428406e-01 -2.59333819e-01 3.03484023e-01 1.37805879e+00
1.37767792e-01 1.01085770e+00 -5.84624887e-01 -2.35803872e-02
5.71415365e-01 -1.40173525e-01 7.39603281e-01 -9.06023502e-01
-5.87763429e-01 -2.96756595e-01 7.88566768e-02 -1.08503175e+00
4.79444295e-01 -1.15310645e+00 5.69413602e-01 -1.26315331e+00
4.19089377e-01 -6.58865988e-01 -6.69075668e-01 5.54691553e-01
-5.40683448e-01 1.60053790e-01 6.43094480e-02 2.96655685e-01
-7.05162942e-01 5.53371370e-01 7.89209604e-01 9.83675569e-02
-1.68673724e-01 -8.61496180e-02 -8.07895303e-01 6.00254118e-01
6.61729395e-01 -6.84007764e-01 -1.92546383e-01 -6.72654867e-01
-3.90004963e-02 -2.36383863e-02 -5.34157008e-02 -6.38105273e-01
3.06593716e-01 -1.29564211e-01 5.12099117e-02 -8.78889561e-02
2.24495873e-01 -4.46446329e-01 -5.08299656e-02 8.99646133e-02
-6.64227962e-01 -2.05775738e-01 1.77008018e-01 5.03065765e-01
-2.53059030e-01 -4.28956568e-01 9.72913027e-01 -3.87338907e-01
-7.89093792e-01 5.28626263e-01 -6.66831210e-02 4.55502123e-01
8.19198489e-01 4.46519375e-01 -1.03326559e-01 -2.40464076e-01
-8.20385814e-01 -1.98767334e-03 5.21541297e-01 5.91769993e-01
-1.60887167e-02 -1.51615572e+00 -9.91056621e-01 -1.29299194e-01
2.96870023e-01 -2.89237052e-01 -1.58907592e-01 8.55302513e-01
-1.99642777e-03 3.51512820e-01 3.04216910e-02 -3.58722448e-01
-7.77783155e-01 7.48999298e-01 3.22411180e-01 -4.89098966e-01
-5.52153945e-01 1.14090097e+00 4.42845583e-01 -8.70102286e-01
4.63567674e-03 3.61450136e-01 1.90742202e-02 1.57694176e-01
5.02160132e-01 -1.33496579e-02 -7.96915591e-02 -8.04748416e-01
-3.73955905e-01 2.68801481e-01 -2.94585496e-01 -5.32525897e-01
1.31519353e+00 -2.32636288e-01 3.05034686e-02 1.09544516e+00
1.21460044e+00 1.38766721e-01 -1.19785678e+00 -6.76329017e-01
4.14995342e-01 -1.73176721e-01 -3.34483624e-01 -7.10952282e-01
-5.81021488e-01 1.09802330e+00 1.17880076e-01 -7.90745914e-02
7.63373852e-01 3.27878535e-01 5.94633758e-01 5.62797964e-01
7.64332592e-01 -8.04861128e-01 -2.71582305e-01 5.90800583e-01
4.35470879e-01 -1.34228957e+00 -3.22906166e-01 -9.91878808e-02
-9.38558578e-01 5.89430809e-01 5.69211662e-01 -1.52705774e-01
6.17513657e-01 3.38587612e-01 3.71046603e-01 1.03519097e-01
-1.17046154e+00 -4.11598980e-01 8.47268924e-02 5.00060797e-01
8.18988383e-01 -4.84074047e-03 -8.95334780e-02 4.51294243e-01
-2.21528128e-01 -1.06515817e-01 1.81347370e-01 8.57536793e-01
-4.66818005e-01 -1.33757889e+00 -2.29656380e-02 3.33625853e-01
-7.98827112e-01 -8.25630486e-01 -3.38983208e-01 8.44801784e-01
-5.11622019e-02 6.15388989e-01 1.05735183e-01 1.28390372e-01
2.01262295e-01 8.57666552e-01 4.45272356e-01 -1.18061757e+00
-7.63169646e-01 2.60748625e-01 3.44389111e-01 -3.31882149e-01
-6.36226952e-01 -7.34715581e-01 -5.87615311e-01 -1.34835377e-01
-5.89889526e-01 4.64878857e-01 2.62217909e-01 1.04910064e+00
3.32921386e-01 -1.08312570e-01 5.26595294e-01 -6.64506257e-01
-7.46575952e-01 -1.29664052e+00 -5.55244744e-01 5.39616823e-01
1.20311126e-01 -4.41696197e-01 -3.51202726e-01 3.74445736e-01] | [11.012696266174316, 9.791007041931152] |
398ff5ea-0b02-4792-b0ce-f852d11d62d1 | mutual-context-network-for-jointly-estimating | 1901.01874 | null | https://arxiv.org/abs/1901.01874v4 | https://arxiv.org/pdf/1901.01874v4.pdf | Mutual Context Network for Jointly Estimating Egocentric Gaze and Actions | In this work, we address two coupled tasks of gaze prediction and action recognition in egocentric videos by exploring their mutual context. Our assumption is that in the procedure of performing a manipulation task, what a person is doing determines where the person is looking at, and the gaze point reveals gaze and non-gaze regions which contain important and complementary information about the undergoing action. We propose a novel mutual context network (MCN) that jointly learns action-dependent gaze prediction and gaze-guided action recognition in an end-to-end manner. Experiments on public egocentric video datasets demonstrate that our MCN achieves state-of-the-art performance of both gaze prediction and action recognition. | ['Yoichi Sato', 'Zhenqiang Li', 'Minjie Cai', 'Yifei Huang'] | 2019-01-07 | null | null | null | null | ['eye-tracking'] | ['computer-vision'] | [ 3.66104126e-01 -1.93753168e-02 -6.02446377e-01 -6.29492760e-01
-1.33280205e-02 -9.90906134e-02 4.60582793e-01 -7.10393071e-01
-2.57699788e-01 4.56857860e-01 7.63705790e-01 2.92657167e-01
1.60569064e-02 -1.09872915e-01 -5.85163593e-01 -8.91886890e-01
-3.67570892e-02 -1.93303823e-01 -6.81061819e-02 1.78424805e-01
8.23494196e-01 -3.50475274e-02 -1.96772349e+00 3.39954108e-01
4.07634020e-01 8.80899966e-01 7.13015124e-02 8.56276155e-01
5.28566360e-01 1.51357150e+00 -1.71970859e-01 -8.02436098e-02
5.18322140e-02 -7.60469854e-01 -1.19334328e+00 1.81237131e-01
1.03542602e+00 -7.22936571e-01 -4.18491840e-01 9.21755075e-01
2.71395266e-01 5.57785928e-01 5.98002613e-01 -1.56655622e+00
-7.39036739e-01 2.22865015e-01 -8.79235089e-01 7.48353720e-01
8.68666410e-01 5.48167765e-01 9.74873841e-01 -7.62337983e-01
6.24702096e-01 1.15381885e+00 1.08848270e-02 1.05964589e+00
-9.70958114e-01 -7.80402184e-01 4.34993029e-01 7.38355994e-01
-1.20087159e+00 -7.52068877e-01 8.72663975e-01 -5.33635259e-01
7.75547206e-01 1.06452703e-01 5.32120228e-01 1.35963356e+00
3.02118748e-01 1.13929462e+00 7.21215844e-01 -3.45159322e-01
-1.62585706e-01 -3.91039431e-01 4.77160923e-02 5.86505890e-01
-3.53026330e-01 2.05779135e-01 -1.31234252e+00 2.80626774e-01
7.38636672e-01 3.59915704e-01 -6.94598019e-01 -4.57314134e-01
-1.45512390e+00 4.41186905e-01 5.51795304e-01 3.47089060e-02
-5.33393681e-01 4.81327444e-01 1.49318561e-01 7.39568621e-02
5.95273793e-01 4.32774834e-02 -3.74616832e-02 -7.64674067e-01
-6.20579720e-01 1.35756865e-01 3.95974368e-01 8.80233705e-01
7.36881316e-01 -3.38157594e-01 -4.73210871e-01 1.38473272e-01
5.02309799e-01 7.12972105e-01 1.96090311e-01 -1.26137793e+00
4.00629669e-01 7.32003570e-01 2.22264677e-01 -9.16851044e-01
-3.23345900e-01 3.66193742e-01 -2.31286779e-01 3.28128815e-01
5.51202059e-01 -1.66069716e-01 -6.06797874e-01 2.10766149e+00
6.48275852e-01 7.15062678e-01 -1.17279731e-01 1.22896945e+00
9.78093028e-01 1.76457196e-01 5.15626192e-01 -2.52509236e-01
1.55475712e+00 -1.13356984e+00 -1.01761532e+00 -3.02304178e-01
8.61680984e-01 -4.34641629e-01 1.20199037e+00 1.29764248e-02
-1.09624231e+00 -5.51719546e-01 -4.64540660e-01 -4.09151375e-01
2.11411610e-01 8.81802887e-02 4.68744904e-01 2.50212580e-01
-9.83446002e-01 3.07243407e-01 -6.26169264e-01 -6.10387623e-01
7.56684482e-01 2.79523790e-01 -5.42527378e-01 1.80352002e-01
-6.69264674e-01 6.79749250e-01 -1.41376644e-01 1.22616976e-01
-1.06307518e+00 -5.03529549e-01 -8.90032828e-01 1.48626864e-01
6.87612236e-01 -8.03588867e-01 1.46422899e+00 -1.45026898e+00
-1.58358741e+00 1.10556197e+00 -9.49562192e-01 -8.86624902e-02
6.60472810e-02 -7.67737985e-01 -4.70049381e-01 4.48399365e-01
8.90318155e-02 9.08292055e-01 1.19450986e+00 -6.37794614e-01
-8.71529639e-01 -7.99588799e-01 4.17827010e-01 6.41116738e-01
-6.37300313e-02 4.13670927e-01 -3.13033998e-01 -1.64178163e-01
-3.17502357e-02 -9.64413285e-01 5.79428911e-01 1.72800481e-01
-2.44373426e-01 -8.45953822e-01 1.15953481e+00 -2.21068040e-01
1.36184144e+00 -2.21910787e+00 3.73196214e-01 -2.89266050e-01
6.29283369e-01 -1.04220867e-01 -3.55163589e-02 2.07267076e-01
-4.11090255e-01 -2.19592139e-01 2.98724562e-01 -4.25791919e-01
-2.29038045e-01 -1.58890054e-01 -3.57288539e-01 8.09509277e-01
5.06214537e-02 1.18104732e+00 -1.20496237e+00 -6.23313248e-01
7.44780004e-02 5.28205872e-01 -5.63289464e-01 4.36227232e-01
-4.46125492e-02 9.58239794e-01 -5.24204850e-01 9.14100528e-01
1.96425572e-01 -6.16267681e-01 -6.53473381e-03 -3.43768783e-02
-3.78793222e-03 3.99177045e-01 -4.98383552e-01 1.82985127e+00
1.43792182e-02 1.16675055e+00 -3.88261497e-01 -3.25568140e-01
3.30895245e-01 2.76634008e-01 3.73907804e-01 -8.35299909e-01
3.80025774e-01 -7.59159148e-01 -3.96231487e-02 -1.18194818e+00
5.74857950e-01 3.11084181e-01 2.77208775e-01 1.22345650e+00
1.21344134e-01 8.88055027e-01 3.62235564e-03 1.05740398e-01
8.99494350e-01 8.29343319e-01 5.35500348e-01 -1.05491154e-01
7.22014189e-01 -3.03262800e-01 4.68991220e-01 3.65167707e-01
-1.02056694e+00 3.50378335e-01 7.94881940e-01 -3.85284811e-01
-3.37767661e-01 -6.48661673e-01 3.49411190e-01 2.02568698e+00
3.71280104e-01 -2.91932315e-01 -9.20106828e-01 -1.05295157e+00
-3.35201800e-01 7.50422835e-01 -1.44488525e+00 -1.98745579e-01
-6.12956285e-01 3.30094934e-01 1.02970898e-01 5.61292231e-01
5.19709051e-01 -1.48332250e+00 -7.95769870e-01 -7.53018677e-01
-3.60125422e-01 -8.71653855e-01 -1.01236486e+00 -6.27836227e-01
-7.76610553e-01 -1.69345176e+00 -5.27001739e-01 -4.75515723e-01
8.11787903e-01 9.33081031e-01 1.16590488e+00 5.09580001e-02
2.34308541e-01 8.22558403e-01 -3.48031610e-01 -2.22833470e-01
4.32124048e-01 -2.24994019e-01 1.88978031e-01 5.45254529e-01
1.26331139e+00 -3.75171840e-01 -9.98879254e-01 5.36346138e-01
-1.88515037e-01 -6.42785477e-03 9.80262533e-02 4.87066090e-01
2.71501124e-01 -7.87488103e-01 -3.05571686e-02 -7.29052424e-01
2.03657612e-01 -6.84399307e-01 -2.02284038e-01 3.41777533e-01
-4.00686532e-01 -2.55241573e-01 -3.44657451e-01 -1.93182722e-01
-1.30276549e+00 -5.40134795e-02 6.11924529e-01 -8.15340817e-01
-6.00122094e-01 -5.31806275e-02 -7.28556737e-02 -1.35712679e-02
5.83939910e-01 1.59745201e-01 1.88083485e-01 -7.10739344e-02
3.27256590e-01 5.34022152e-01 4.74450588e-01 3.04687098e-02
3.02589804e-01 7.83792913e-01 1.30655020e-01 -5.74867666e-01
-1.31983125e+00 -7.33288586e-01 -1.11967301e+00 -9.04179215e-01
1.33849072e+00 -1.05634260e+00 -1.75326633e+00 5.12127876e-01
-8.35000992e-01 -4.69372392e-01 -9.47611332e-02 4.97470975e-01
-8.37523282e-01 2.92486906e-01 1.48490936e-01 -9.08579111e-01
-2.61259943e-01 -9.09342110e-01 1.32540905e+00 6.61560714e-01
-5.18640637e-01 -1.05746496e+00 2.41679400e-01 6.19466186e-01
-9.87553149e-02 -3.16392034e-02 1.42457485e-01 -2.88246274e-01
-7.88944304e-01 9.59535837e-02 -3.29985529e-01 -1.19019441e-01
3.45799685e-01 -5.98057173e-02 -1.16052008e+00 -7.99295977e-02
-4.30495180e-02 -4.75673109e-01 6.14065349e-01 5.51970363e-01
1.09559453e+00 -1.77320600e-01 -6.48844600e-01 8.23368669e-01
7.88185239e-01 -5.28339297e-02 7.46922493e-01 1.50291594e-02
1.06228065e+00 8.41786385e-01 1.06971323e+00 3.10521007e-01
7.18454003e-01 6.40311718e-01 6.73441529e-01 4.51193631e-01
5.61288111e-02 -2.43814573e-01 6.18776858e-01 -3.19416970e-01
-6.78708076e-01 -3.68246734e-01 -8.01140368e-01 3.80204916e-01
-2.02921677e+00 -1.68086481e+00 -2.93815792e-01 1.98717642e+00
4.19612288e-01 -4.23569947e-01 4.21115488e-01 -4.76630896e-01
6.98217511e-01 5.63684523e-01 -8.43566239e-01 -7.49721229e-02
4.40396070e-01 -2.20694497e-01 1.04450293e-01 7.87687600e-02
-1.34700096e+00 9.80905294e-01 6.77871323e+00 -8.07277206e-03
-1.08152640e+00 1.40289560e-01 2.57476538e-01 -8.24656367e-01
4.23133850e-01 -1.35099903e-01 -7.12132215e-01 5.55250287e-01
8.88987422e-01 -1.08659081e-02 3.65257382e-01 9.75452363e-01
5.51781356e-01 -6.04154289e-01 -1.52208245e+00 1.30590630e+00
6.87915623e-01 -9.59035575e-01 -3.54900748e-01 1.84176788e-01
5.66608906e-01 1.69380561e-01 2.83560753e-01 9.24722999e-02
7.83722475e-02 -9.70294237e-01 4.38500524e-01 1.15689194e+00
7.70655930e-01 -5.36199808e-01 2.66365647e-01 1.73757911e-01
-9.90774632e-01 -5.00477135e-01 1.91734195e-01 -4.62874323e-01
2.45490223e-01 -4.72952902e-01 -4.89491552e-01 -1.33675948e-01
1.03822100e+00 1.51747727e+00 -5.41138053e-01 6.49791241e-01
-7.45301843e-01 5.31400025e-01 2.95595258e-01 -1.96453575e-02
2.22750783e-01 -1.08500965e-01 7.14463890e-01 6.15408659e-01
-8.75318721e-02 5.24402261e-01 -3.33966464e-01 9.14649725e-01
-1.45776197e-01 -2.77402014e-01 -6.77437544e-01 -3.55915353e-02
1.92302942e-01 9.97924149e-01 -1.39349103e-01 -1.09290913e-01
-4.44556266e-01 9.87404644e-01 5.16554356e-01 7.07457483e-01
-7.92490304e-01 -3.21538784e-02 1.41017950e+00 6.68899044e-02
5.07454157e-01 1.34005755e-01 2.46177502e-02 -1.25219500e+00
-1.88196922e-04 -5.42577207e-01 5.33566415e-01 -1.37195969e+00
-8.65828454e-01 1.27089158e-01 -5.10183126e-02 -1.75856709e+00
-6.48137510e-01 -3.58664125e-01 -9.71386671e-01 8.95820737e-01
-1.37237632e+00 -1.21551204e+00 -8.94166946e-01 9.56869841e-01
6.07267678e-01 -1.65754810e-01 5.51977158e-01 -2.45494068e-01
-7.15034842e-01 5.19158304e-01 -4.32830215e-01 2.50632793e-01
1.05520248e+00 -1.04904568e+00 3.93176079e-02 8.92851651e-01
6.66120052e-02 7.32665956e-01 5.67829013e-01 -5.25603831e-01
-1.40975356e+00 -6.90902591e-01 9.99406338e-01 -1.21263576e+00
5.28704643e-01 -9.11784619e-02 -6.38624668e-01 1.21755695e+00
5.71927249e-01 1.47509828e-01 1.04202759e+00 5.82216740e-01
-3.01945388e-01 1.69404402e-01 -8.23622823e-01 7.41556525e-01
1.51725376e+00 -9.80763078e-01 -8.67455781e-01 2.08815232e-01
3.26318920e-01 -4.58823144e-01 -4.23237681e-01 1.38462102e-02
8.94126534e-01 -1.24509180e+00 6.88072324e-01 -1.19351459e+00
7.88501561e-01 -2.97070384e-01 1.13527812e-01 -9.09613907e-01
-4.64311689e-01 -7.59307086e-01 -7.25786746e-01 8.70423794e-01
-2.77493149e-01 -3.70382875e-01 8.00593376e-01 8.18957686e-01
2.11096361e-01 -5.01084507e-01 -7.19356894e-01 -3.94472107e-02
-5.77340186e-01 -2.04811305e-01 5.96290231e-01 8.77490163e-01
4.39729869e-01 4.91752118e-01 -6.44501269e-01 -8.52768309e-03
4.81656879e-01 2.22980753e-01 1.37185717e+00 -1.03077364e+00
2.05022141e-01 -4.54267919e-01 -6.72503710e-01 -1.51881480e+00
4.77240413e-01 -3.02396208e-01 6.60449862e-02 -9.83104408e-01
4.05028045e-01 4.36282784e-01 -5.77151179e-01 4.62917179e-01
-5.14050484e-01 3.33056420e-01 1.05325051e-01 5.37442327e-01
-1.30139852e+00 5.35941184e-01 1.43151581e+00 1.75841570e-01
-1.75808057e-01 7.60633796e-02 -8.02369952e-01 8.16429675e-01
2.48012796e-01 -4.27110493e-01 -6.11521244e-01 -4.63674903e-01
2.64396489e-01 -5.86587451e-02 6.80855691e-01 -7.29668736e-01
5.18857777e-01 -4.40816253e-01 2.63248235e-01 -8.82361710e-01
4.38828558e-01 -6.60447180e-01 -6.38508797e-01 -4.18436304e-02
-4.79158431e-01 -1.23840749e-01 -2.62964815e-01 9.79772389e-01
-1.35857627e-01 9.01436359e-02 3.37744594e-01 1.52826458e-01
-1.09953928e+00 4.85960543e-01 -1.36131898e-01 4.59451936e-02
1.36286283e+00 -4.82613057e-01 -5.98212242e-01 -6.96334541e-01
-8.55687797e-01 4.24040377e-01 6.93568468e-01 6.94340885e-01
5.31156778e-01 -1.21805561e+00 -4.21789944e-01 2.07275197e-01
6.01307452e-01 -3.94426405e-01 6.28055930e-01 1.49960530e+00
5.04595824e-02 5.02336502e-01 -4.04815346e-01 -1.12386465e+00
-1.84406984e+00 5.79558969e-01 3.18773866e-01 3.49282920e-01
-5.11486888e-01 1.15843773e+00 8.39986145e-01 1.49388343e-01
3.01145285e-01 -8.05140212e-02 -9.02260721e-01 1.69135213e-01
1.15620625e+00 4.27301139e-01 -8.26499939e-01 -1.33399284e+00
-4.12021667e-01 6.33086801e-01 -6.53720368e-03 3.52558881e-01
1.21020925e+00 -6.43565297e-01 -1.93969116e-01 6.49920762e-01
1.00215924e+00 -4.66474444e-01 -1.84012508e+00 -3.58091503e-01
-3.72919917e-01 -1.11883152e+00 2.56101638e-01 -5.54608881e-01
-1.16773593e+00 9.07148480e-01 6.83828592e-01 -1.36079967e-01
1.35823226e+00 2.28670344e-01 3.88674915e-01 5.28064907e-01
1.52340159e-01 -9.45711434e-01 2.70271868e-01 5.14138222e-01
8.52293670e-01 -1.61925292e+00 1.56026036e-01 -1.29484907e-01
-1.08929396e+00 8.86089802e-01 9.88671541e-01 -4.75737266e-02
8.38885248e-01 -6.74055576e-01 6.19043671e-02 -7.82086015e-01
-1.01459193e+00 -5.03457189e-01 5.93538821e-01 6.01796687e-01
4.12648976e-01 -1.32635191e-01 2.12991521e-01 1.24458909e-01
1.19559631e-01 3.71048123e-01 2.11991951e-01 1.03764153e+00
-2.28351504e-01 -4.21753109e-01 -1.33335590e-01 1.58851758e-01
-3.59647214e-01 3.78435962e-02 -5.52276731e-01 7.38514245e-01
-4.83293273e-02 9.53679621e-01 6.62641525e-01 -5.19327521e-01
5.36680669e-02 3.13911229e-01 6.03623867e-01 -5.88251293e-01
-3.07700008e-01 -2.73641765e-01 -9.66097564e-02 -1.48710263e+00
-1.19715238e+00 -1.15512621e+00 -1.01235759e+00 -4.13366526e-01
-1.36294499e-01 -3.82007182e-01 2.16333508e-01 1.27837026e+00
6.73069060e-01 3.64363492e-01 6.93372250e-01 -1.11289620e+00
-3.38242576e-02 -1.29756975e+00 -5.54321527e-01 6.23262107e-01
6.81946278e-01 -1.18047237e+00 -3.10089320e-01 4.36360627e-01] | [13.991453170776367, 0.054675135761499405] |
8d38bc9b-2b6a-44fe-a31b-6f2ede3c2250 | saliency-based-fire-detection-using-texture | 1912.10059 | null | https://arxiv.org/abs/1912.10059v1 | https://arxiv.org/pdf/1912.10059v1.pdf | Saliency Based Fire Detection Using Texture and Color Features | Due to industry deployment and extension of urban areas, early warning systems have an essential role in giving emergency. Fire is an event that can rapidly spread and cause injury, death, and damage. Early detection of fire could significantly reduce these injuries. Video-based fire detection is a low cost and fast method in comparison with conventional fire detectors. Most available fire detection methods have a high false-positive rate and low accuracy. In this paper, we increase accuracy by using spatial and temporal features. Captured video sequences are divided into Spatio-temporal blocks. Then a saliency map and combination of color and texture features are used for detecting fire regions. We use the HSV color model as a spatial feature and LBP-TOP for temporal processing of fire texture. Fire detection tests on publicly available datasets have shown the accuracy and robustness of the algorithm. | ['Shadrokh Samavi', 'Nader Karimi', 'Maedeh Jamali'] | 2019-12-20 | null | null | null | null | ['fire-detection'] | ['time-series'] | [ 3.56918216e-01 -1.12151015e+00 1.27546368e-02 1.42601863e-01
-1.59615308e-01 -4.85327572e-01 5.95275998e-01 2.93090940e-01
-6.49523735e-01 7.56022334e-01 1.34628505e-01 -1.03465550e-01
-2.47109845e-01 -1.20502722e+00 -1.25493079e-01 -7.57189274e-01
-4.10924435e-01 -2.59976476e-01 1.08515513e+00 -1.01182558e-01
6.05079651e-01 7.85076201e-01 -1.74963605e+00 3.55556726e-01
3.92558455e-01 8.85888875e-01 4.98395175e-01 8.38618279e-01
1.86909854e-01 7.82747209e-01 -4.26101446e-01 4.02375191e-01
5.20673275e-01 -3.81676167e-01 -6.77556992e-01 -1.34510010e-01
-4.32708472e-01 -6.74375713e-01 -4.89231527e-01 6.39470279e-01
4.81099933e-01 4.52036291e-01 7.35248864e-01 -1.44938660e+00
-1.95338696e-01 -9.29346308e-02 -9.08815861e-01 8.82796884e-01
5.58221459e-01 2.29792967e-01 9.84577984e-02 -9.89926338e-01
3.85071367e-01 9.93178129e-01 7.01898277e-01 2.61941522e-01
-7.04767704e-01 -7.43397057e-01 -2.94444859e-01 8.13672900e-01
-1.65022898e+00 -1.04749314e-01 5.91335118e-01 -5.26867032e-01
1.04244614e+00 4.92269307e-01 8.81376863e-01 5.16024411e-01
3.52890939e-01 4.29312557e-01 1.22205734e+00 -4.99461353e-01
1.23201735e-01 -4.83903170e-01 -2.13273197e-01 6.14223778e-01
3.32930684e-01 5.62441289e-01 -3.12666714e-01 -6.86569884e-02
8.38993132e-01 7.18787968e-01 -3.04211676e-01 2.63989270e-01
-1.05049229e+00 6.04488730e-01 6.06109142e-01 3.48186553e-01
-8.30571353e-01 6.93884715e-02 4.40372318e-01 -1.68242857e-01
3.30679566e-01 -5.97296730e-02 9.55425650e-02 -2.88501978e-01
-1.18846989e+00 2.39995241e-01 1.45433769e-01 2.02942282e-01
5.60589910e-01 -7.29218945e-02 -4.26615000e-01 6.17855966e-01
1.26268297e-01 1.00287473e+00 5.89184053e-02 -6.66579664e-01
-7.59503022e-02 5.78571022e-01 5.30906282e-02 -1.54042256e+00
-3.38149965e-01 2.92701274e-01 -1.07885635e+00 7.17449784e-01
1.71347260e-01 5.60799688e-02 -1.05751061e+00 9.92523551e-01
2.78689444e-01 5.44425726e-01 -4.12841529e-01 1.00930369e+00
3.38108957e-01 1.06714761e+00 3.89529586e-01 -2.84472078e-01
1.20870590e+00 -3.58790994e-01 -6.86280608e-01 -5.72568923e-02
-1.48964897e-01 -7.81741381e-01 5.27023792e-01 2.63989091e-01
-5.44987798e-01 -3.39182854e-01 -7.79659390e-01 4.72545981e-01
-5.38274467e-01 -7.93425292e-02 2.82822311e-01 3.37739795e-01
-7.02896237e-01 4.23036814e-01 -7.30320454e-01 -8.70124340e-01
4.89392847e-01 4.69343998e-02 -2.76577234e-01 -2.41801828e-01
-1.08616030e+00 1.03826201e+00 4.11835045e-01 1.49962217e-01
-1.00794542e+00 -1.27041906e-01 -5.90018213e-01 -2.02696189e-01
1.82825461e-01 -1.99668929e-01 7.53355801e-01 -5.05254030e-01
-7.98109651e-01 4.95176673e-01 -2.28901923e-01 -3.19885820e-01
4.19605583e-01 -2.28312593e-02 -4.78604972e-01 6.40834153e-01
2.37662256e-01 3.93750578e-01 9.22244906e-01 -9.65194046e-01
-1.15713823e+00 -7.15079010e-02 -8.59856829e-02 1.46065608e-01
-4.10773903e-02 5.45254171e-01 2.89377332e-01 -6.96445346e-01
7.62008205e-02 -6.61816835e-01 -2.04070821e-01 1.35775372e-01
1.04200445e-01 8.99431184e-02 1.42627811e+00 -9.52950060e-01
1.46830845e+00 -2.01010084e+00 -5.00802994e-01 2.52571166e-01
-1.43142745e-01 5.23113132e-01 3.12994301e-01 3.78577709e-01
1.10046491e-01 1.96672231e-01 -3.80830646e-01 8.09415221e-01
-6.82847261e-01 3.73280533e-02 -2.09525511e-01 4.03578341e-01
4.08322424e-01 3.82367760e-01 -1.03999829e+00 -5.49852371e-01
7.19260335e-01 5.95466673e-01 -8.95431265e-02 1.09027654e-01
3.97872359e-01 3.04675490e-01 -3.49519283e-01 7.42092192e-01
6.68099165e-01 4.46764022e-01 -4.60389942e-01 -2.97982488e-02
-6.41431808e-01 -1.19307458e-01 -1.11769009e+00 8.37390602e-01
-5.39391711e-02 7.20867395e-01 -8.29292834e-02 -7.58155644e-01
9.41945732e-01 5.15185118e-01 7.61939883e-01 -6.87412381e-01
9.91464257e-02 6.73063025e-02 -4.30212915e-01 -9.29155290e-01
4.50738609e-01 -1.36504263e-01 2.49560535e-01 4.90881324e-01
-5.45591176e-01 9.11348239e-02 3.98182690e-01 -5.00289463e-02
1.29106069e+00 6.46719635e-02 2.62692660e-01 -1.55777559e-01
3.30214143e-01 3.75751853e-01 4.75030005e-01 5.53035855e-01
-5.56662858e-01 6.56191945e-01 -1.75008863e-01 -7.35786140e-01
-9.33295846e-01 -1.04157352e+00 3.76818259e-03 7.98758626e-01
2.98282474e-01 -1.00090511e-01 -5.83486974e-01 -3.65800083e-01
-1.43599793e-01 4.55798507e-01 -3.90269876e-01 -2.71286160e-01
-5.64611673e-01 -8.91425908e-01 3.99366438e-01 5.81446469e-01
9.38617468e-01 -1.26403952e+00 -1.49319875e+00 2.35782921e-01
-3.94663066e-01 -6.02366388e-01 -4.48594019e-02 -8.06471705e-02
-6.84164166e-01 -1.39411223e+00 -9.85038459e-01 -6.30276382e-01
5.54291070e-01 9.66592729e-01 5.48556149e-01 3.86350155e-01
-8.72022510e-01 2.71004289e-01 -6.71761870e-01 -5.04903197e-01
6.58216095e-03 -3.69562626e-01 -7.19594508e-02 -1.32497355e-01
4.08408850e-01 -3.58092427e-01 -8.75497043e-01 2.35094830e-01
-9.94100571e-01 1.39028221e-01 4.01071161e-01 4.30919141e-01
1.56327218e-01 5.58374286e-01 1.54362425e-01 5.94762852e-03
5.72178662e-01 -4.85469490e-01 -3.62061054e-01 2.40743250e-01
-2.91417718e-01 -3.21161687e-01 2.41782770e-01 -1.01594560e-01
-9.47110116e-01 2.15761095e-01 3.05358976e-01 -6.72620386e-02
-4.90156054e-01 3.30712736e-01 4.17748421e-01 -1.50776580e-02
6.69989645e-01 2.55630255e-01 -2.09226578e-01 -2.92018086e-01
-3.07915598e-01 8.98598194e-01 5.27335405e-01 -2.02533439e-01
8.50164235e-01 6.17438793e-01 2.59565145e-01 -1.15153909e+00
-2.73746490e-01 -7.40867794e-01 -7.53192723e-01 -1.04679120e+00
9.62169707e-01 -4.44550127e-01 -5.94650149e-01 7.89821744e-01
-1.24982846e+00 -8.59500021e-02 1.47031158e-01 6.22760892e-01
-1.05042666e-01 3.34098309e-01 -3.37907732e-01 -1.28941584e+00
-4.10280794e-01 -6.27921462e-01 6.77725852e-01 4.42461669e-01
4.24986854e-02 -4.63205189e-01 1.34350806e-01 -1.53201431e-01
7.04097450e-01 6.76802933e-01 3.35136980e-01 3.24161768e-01
-4.67888653e-01 -2.09134296e-01 -5.60051620e-01 2.57440619e-02
4.59891915e-01 4.95866328e-01 -6.52267754e-01 6.10896423e-02
-3.16342115e-01 3.18465561e-01 1.06353736e+00 5.94571710e-01
7.31110334e-01 -1.02696501e-01 -5.54137528e-01 3.03961784e-01
1.61286211e+00 7.32097924e-01 7.77476668e-01 6.57495022e-01
4.95743811e-01 4.57950532e-01 9.96497989e-01 6.74463272e-01
-3.39537710e-02 3.84687871e-01 3.38760465e-01 -1.91779971e-01
-1.34816095e-01 3.24026798e-03 3.54785144e-01 1.70822680e-01
-8.31947982e-01 -1.55289590e-01 -1.40866876e+00 6.69100404e-01
-1.85284793e+00 -1.83401120e+00 -6.10090196e-01 2.31232762e+00
3.76286328e-01 -3.76279280e-02 3.65255326e-01 7.43504584e-01
1.19246054e+00 -6.65085316e-02 1.10854790e-01 -1.57220587e-01
-8.30415115e-02 1.92174807e-01 8.15788805e-01 2.90320277e-01
-1.47834516e+00 6.12335682e-01 6.96856785e+00 4.99758840e-01
-1.33200896e+00 8.35143253e-02 3.74140531e-01 1.48307821e-02
3.44620168e-01 -1.90165248e-02 -2.90947795e-01 5.70199311e-01
5.41006565e-01 -2.98849225e-01 4.65098917e-01 4.14363921e-01
7.97049284e-01 -8.29240382e-01 -1.46881402e-01 9.00111020e-01
-9.02865902e-02 -1.03112733e+00 -1.25810757e-01 -3.40805620e-01
3.67045939e-01 -3.14591676e-01 -4.22201455e-01 -2.20772520e-01
1.06933452e-01 -8.26550007e-01 7.65572131e-01 8.43693554e-01
8.28292668e-01 -9.69998896e-01 6.56098008e-01 2.26760685e-01
-1.63083589e+00 -3.01113576e-01 -3.68653357e-01 -6.24661803e-01
5.95397472e-01 4.15997803e-01 -6.70528114e-01 2.31616855e-01
1.15972030e+00 6.43372536e-01 -5.10273039e-01 1.75001025e+00
-2.57213116e-01 5.30716062e-01 -6.65138483e-01 -3.98102440e-02
1.64173394e-01 -7.80963004e-02 5.96724570e-01 1.34000301e+00
6.01216078e-01 4.90645021e-01 3.48678410e-01 5.13958156e-01
7.69514680e-01 -1.82842880e-01 -9.73289967e-01 1.04523093e-01
3.93529326e-01 1.03195143e+00 -1.26433063e+00 -3.47761303e-01
-1.14675649e-01 9.57731426e-01 -5.29587805e-01 1.07936628e-01
-9.31598723e-01 -7.08405435e-01 3.48363310e-01 4.65115935e-01
1.93764959e-02 -5.09691834e-01 -2.50002116e-01 -6.06887758e-01
-2.32485250e-01 -2.46947095e-01 5.42651951e-01 -9.70277727e-01
-7.98333049e-01 4.84066874e-01 4.23032284e-01 -1.27268171e+00
2.04053279e-02 -4.84474123e-01 -6.78184509e-01 8.05652320e-01
-1.09622395e+00 -1.06096578e+00 -6.64575398e-01 6.89961195e-01
6.73529267e-01 1.02777228e-01 7.29989827e-01 3.79934788e-01
-5.01513362e-01 -3.09265852e-01 -1.30286038e-01 2.49471501e-01
3.91429394e-01 -6.67471051e-01 -4.04362120e-02 1.38486445e+00
-3.29614878e-01 -3.04900948e-02 6.79991245e-01 -1.06489456e+00
-8.06575656e-01 -1.01928735e+00 8.37387085e-01 -5.23593388e-02
2.11147353e-01 -5.85293770e-02 -6.77559495e-01 5.75606786e-02
8.33911076e-02 -1.74032643e-01 1.83985427e-01 -6.72786355e-01
2.75982678e-01 -6.89650401e-02 -1.37748742e+00 4.50209230e-01
8.06601465e-01 -4.13020313e-01 -5.66193342e-01 1.32499069e-01
-4.27069776e-02 2.04841107e-01 -1.35912284e-01 5.01531422e-01
7.48135030e-01 -9.98798966e-01 9.87304688e-01 -3.10017522e-02
2.81447649e-01 -5.72310746e-01 4.25343439e-02 -8.42922628e-01
-9.58596587e-01 -1.29245624e-01 5.12483060e-01 1.08902645e+00
-4.05359156e-02 -1.40043542e-01 3.18423778e-01 4.77343261e-01
2.18896225e-01 -1.18907206e-01 -6.74342513e-01 -7.12069571e-01
-7.10319161e-01 -5.37884474e-01 2.22890645e-01 7.38237381e-01
8.81707668e-02 -2.30622947e-01 -3.86215776e-01 1.97634548e-01
5.52117527e-01 -2.14330420e-01 1.49053112e-01 -1.21956778e+00
5.20324349e-01 -3.66876662e-01 -6.91957235e-01 -1.16535025e-02
-4.90738660e-01 -4.42221940e-01 2.53846377e-01 -1.84116304e+00
4.18536633e-01 -2.07372203e-01 -5.19435704e-01 8.72628629e-01
-2.02187911e-01 6.83677018e-01 -7.32716871e-03 1.84635237e-01
-8.25682804e-02 1.13844611e-01 6.35886431e-01 -1.76879525e-01
-1.21582396e-01 -1.47603706e-01 2.46544614e-01 6.69788003e-01
1.19093084e+00 -8.08613956e-01 -1.56007946e-01 -3.10650647e-01
-7.71179050e-02 -1.28954232e-01 8.52382898e-01 -1.41856921e+00
2.27609292e-01 -8.25501323e-01 4.71119881e-01 -6.24779463e-01
8.70302245e-02 -1.03914785e+00 2.12899029e-01 9.17689681e-01
1.96098581e-01 3.80249083e-01 3.48127246e-01 5.31431794e-01
-1.37635782e-01 -1.98313341e-01 8.09414804e-01 -1.13738373e-01
-1.23123384e+00 1.61649525e-01 -1.25573289e+00 -5.44864178e-01
1.43322539e+00 -5.63645124e-01 -2.38563910e-01 -2.05417261e-01
-3.02682906e-01 -2.20867753e-01 3.71008158e-01 4.57248926e-01
9.73463118e-01 -1.38985503e+00 -7.45611429e-01 2.84954220e-01
-1.49809614e-01 -5.04216969e-01 2.43509874e-01 9.72362638e-01
-1.22394621e+00 1.27290323e-01 -9.19135749e-01 -4.77514207e-01
-1.54150665e+00 6.24525487e-01 7.45926797e-02 3.00311685e-01
-5.60810208e-01 5.60329676e-01 -2.71195441e-01 5.94551802e-01
-1.42178446e-01 -1.46773770e-01 -4.50160295e-01 -3.15488279e-02
9.07209992e-01 9.76705551e-01 -2.48716980e-01 -9.36565697e-01
-8.33528101e-01 7.08828092e-01 6.77748144e-01 -3.73034686e-01
1.35314333e+00 -1.65160336e-02 -2.56574571e-01 3.13085675e-01
5.60124218e-01 -3.03857863e-01 -1.15571249e+00 3.53955388e-01
8.20254385e-02 -9.34352994e-01 3.73626053e-01 -8.43077898e-01
-9.59129870e-01 9.39753592e-01 1.02372396e+00 3.41704279e-01
1.54122388e+00 -4.66207981e-01 8.39736760e-01 -2.93014888e-02
4.97371227e-01 -1.19463968e+00 -2.93754429e-01 4.35010612e-01
8.36154878e-01 -1.03700316e+00 6.06945008e-02 -4.06842291e-01
-3.99830133e-01 1.21322298e+00 2.27657914e-01 -2.84587979e-01
7.54943669e-01 5.12611508e-01 -8.00266638e-02 -3.29480357e-02
-4.33582366e-01 -5.76731861e-01 3.28821316e-02 9.74497259e-01
2.27016732e-01 1.36749700e-01 -7.02061594e-01 1.28363535e-01
3.92249376e-01 3.73156458e-01 1.70046568e-01 1.50229144e+00
-1.12721825e+00 -7.23940372e-01 -9.83878732e-01 4.37019289e-01
-4.72121179e-01 1.91428289e-01 -3.74170840e-01 5.08862615e-01
4.12898153e-01 1.39384961e+00 1.45193441e-02 -6.86620235e-01
2.13291451e-01 2.66570062e-03 3.47933263e-01 -9.19000059e-02
-4.64791715e-01 -1.11420266e-01 -1.77917182e-01 -4.30271566e-01
-4.84654903e-01 -6.81320310e-01 -1.27609766e+00 -5.12435675e-01
-1.45660922e-01 1.41341798e-02 6.88476920e-01 8.29070330e-01
9.10732001e-02 3.07040244e-01 6.35449409e-01 -9.20385063e-01
1.73952579e-01 -8.20598006e-01 -6.72952414e-01 5.52560747e-01
2.15992436e-01 -9.59229231e-01 -1.76958203e-01 3.65171492e-01] | [9.168943405151367, -1.1983873844146729] |
d93c17a4-c054-41f7-a5bd-819c8d83b856 | knowledge-graph-and-text-jointly-embedding | null | null | https://aclanthology.org/D14-1167 | https://aclanthology.org/D14-1167.pdf | Knowledge Graph and Text Jointly Embedding | null | ['Jianwen Zhang', 'Jianlin Feng', 'Zhen Wang', 'Zheng Chen'] | 2014-10-01 | null | null | null | emnlp-2014-10 | ['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] | [-7.483160018920898, 3.820765495300293] |
7f5b269a-4426-4fd8-a5ef-9e6051a07e0e | gridnet-with-automatic-shape-prior | 1705.08943 | null | http://arxiv.org/abs/1705.08943v2 | http://arxiv.org/pdf/1705.08943v2.pdf | GridNet with automatic shape prior registration for automatic MRI cardiac segmentation | In this paper, we propose a fully automatic MRI cardiac segmentation method
based on a novel deep convolutional neural network (CNN) designed for the 2017
ACDC MICCAI challenge. The novelty of our network comes with its embedded shape
prior and its loss function tailored to the cardiac anatomy. Our model includes
a cardiac centerof-mass regression module which allows for an automatic shape
prior registration. Also, since our method processes raw MR images without any
manual preprocessing and/or image cropping, our CNN learns both high-level
features (useful to distinguish the heart from other organs with a similar
shape) and low-level features (useful to get accurate segmentation results).
Those features are learned with a multi-resolution conv-deconv "grid"
architecture which can be seen as an extension of the U-Net. Experimental
results reveal that our method can segment the left and right ventricles as
well as the myocardium from a 3D MRI cardiac volume in 0.4 second with an
average Dice coefficient of 0.90 and an average Hausdorff distance of 10.4 mm. | ['Pierre-Marc Jodoin', 'Olivier Humbert', 'Clement Zotti', 'Alain Lalande', 'Zhiming Luo'] | 2017-05-24 | null | null | null | null | ['image-cropping', 'cardiac-segmentation'] | ['computer-vision', 'medical'] | [ 8.69816393e-02 4.02640700e-01 1.47688419e-01 -4.19485062e-01
-5.11179090e-01 -3.59304547e-01 1.73149660e-01 4.00698811e-01
-6.73360348e-01 5.54088354e-01 -1.88190296e-01 -1.07247636e-01
1.62942603e-01 -6.22055411e-01 -5.95266759e-01 -7.64122069e-01
-4.34813708e-01 6.77123308e-01 2.67747551e-01 1.02884673e-01
-5.56452433e-03 6.68247998e-01 -6.60592437e-01 -1.86827809e-01
9.56134975e-01 1.16396260e+00 9.80449989e-02 7.13540435e-01
2.87623793e-01 5.72569966e-01 -2.69004464e-01 -1.98683783e-01
4.15047556e-01 -4.39745724e-01 -1.08831167e+00 3.47179882e-02
2.57622331e-01 -5.03048003e-01 -1.70733899e-01 1.04759657e+00
6.47667825e-01 -7.54395574e-02 7.23934233e-01 -6.50109649e-01
-3.13241005e-01 5.47148943e-01 -4.57080811e-01 4.21002924e-01
-2.10274160e-01 7.72182867e-02 5.30006766e-01 -5.03454626e-01
6.69447184e-01 5.86039484e-01 9.43254292e-01 4.77577209e-01
-1.18555892e+00 -3.12180787e-01 -4.43575114e-01 -2.43723869e-01
-1.18348432e+00 1.03548309e-02 7.03172803e-01 -7.85170197e-01
2.99424618e-01 1.11176103e-01 8.35161388e-01 6.72594786e-01
5.33060610e-01 5.23462892e-01 1.04119503e+00 -1.05049200e-01
2.07018167e-01 -3.51077855e-01 -2.68612765e-02 7.77250111e-01
1.58603892e-01 -7.19988272e-02 4.19799447e-01 1.28164003e-02
1.34017229e+00 1.98005870e-01 -4.37023789e-01 -6.55784488e-01
-1.53774559e+00 7.81756997e-01 8.37229729e-01 6.18704259e-01
-5.53529084e-01 2.42280439e-01 5.37615955e-01 -1.28539354e-01
2.75321215e-01 3.45039129e-01 -3.46418023e-01 2.26061881e-01
-1.00904334e+00 2.99380962e-02 5.25313020e-01 7.17888951e-01
4.92231935e-01 -3.95999737e-02 -4.33538765e-01 6.86221778e-01
2.69475818e-01 2.96790510e-01 6.36307418e-01 -9.91522431e-01
6.60503954e-02 5.25194287e-01 -2.79461980e-01 -9.23354030e-01
-7.57085681e-01 -6.90292418e-01 -1.37077689e+00 1.64308473e-01
4.64449584e-01 -3.71921837e-01 -9.25525069e-01 1.45966303e+00
4.88411129e-01 3.29631656e-01 -2.87942588e-01 1.22125959e+00
8.85900557e-01 -2.99853422e-02 -8.81777853e-02 -1.60548970e-01
1.49138355e+00 -9.46874797e-01 -5.96790910e-01 1.52106658e-01
6.95198953e-01 -3.93935233e-01 6.72181010e-01 4.18423600e-02
-1.23477256e+00 -4.09548759e-01 -1.08970189e+00 4.92690392e-02
-1.04319483e-01 1.23201959e-01 4.57246006e-01 4.53784883e-01
-1.17967558e+00 9.42978680e-01 -1.11577916e+00 1.96034499e-02
8.58557999e-01 3.49897504e-01 -3.78699034e-01 2.15252787e-01
-9.11091208e-01 7.45989382e-01 4.41998780e-01 2.14191347e-01
-7.99374223e-01 -9.30978656e-01 -8.38438272e-01 -1.50722591e-02
1.80192411e-01 -9.01665449e-01 9.26310182e-01 -8.04638863e-01
-1.54128027e+00 1.22545195e+00 4.56052661e-01 -8.30985785e-01
9.00832832e-01 4.23186570e-02 2.82637198e-02 6.46906853e-01
1.36028618e-01 6.73584223e-01 5.79349518e-01 -1.00519955e+00
-9.37125757e-02 -5.21452010e-01 -2.76870996e-01 -5.91090582e-02
9.93943959e-02 -3.43781128e-03 -3.15562874e-01 -1.01757979e+00
2.75672644e-01 -9.80762959e-01 -5.31523049e-01 7.15399906e-02
-2.77717024e-01 3.02903593e-01 4.73175228e-01 -9.53614295e-01
9.72197354e-01 -1.80535793e+00 1.14812754e-01 1.91014305e-01
7.20126390e-01 2.28901222e-01 1.22152336e-01 -2.51670837e-01
-9.48549584e-02 1.84560061e-01 -8.57553661e-01 -7.50169158e-02
-4.29617882e-01 -3.40395384e-02 2.64465064e-01 8.42460513e-01
1.13664843e-01 1.05774605e+00 -1.03010750e+00 -6.29490435e-01
1.20005772e-01 6.75619543e-01 -5.58280051e-01 2.89302111e-01
2.56684184e-01 9.42071795e-01 -2.95075864e-01 4.36954975e-01
8.14876556e-01 -2.70870864e-01 2.71358997e-01 -1.99332833e-01
-7.55884275e-02 -1.19752876e-01 -7.74111867e-01 2.02957988e+00
-1.77744731e-01 2.15500072e-01 5.39217591e-01 -1.31970859e+00
9.09493566e-01 4.79244322e-01 1.09039235e+00 -5.90044439e-01
6.24931097e-01 2.93411016e-01 2.43722767e-01 -3.05016398e-01
-2.56902277e-01 -2.50904560e-01 1.32712349e-01 3.84476542e-01
1.85488746e-01 -2.87769049e-01 1.18892267e-01 -4.75904681e-02
9.33395743e-01 6.89262822e-02 1.08336590e-01 -7.78840661e-01
6.46461844e-01 -3.26084405e-01 8.75136971e-01 4.04958278e-01
-5.10349810e-01 1.01777589e+00 4.53851521e-01 -9.21897054e-01
-1.07800305e+00 -9.84009147e-01 -4.70509857e-01 3.02422106e-01
-4.31945510e-02 -6.58871084e-02 -1.20561337e+00 -8.92964721e-01
-2.72392273e-01 -1.04763201e-02 -7.18773961e-01 7.75062665e-02
-8.65632951e-01 -8.10386300e-01 5.62758088e-01 7.34479785e-01
6.00598872e-01 -1.11646545e+00 -1.14900506e+00 3.34515333e-01
-3.15964311e-01 -1.16437209e+00 -7.40134120e-01 7.10808635e-02
-1.28769183e+00 -1.21936297e+00 -1.10982490e+00 -9.17573273e-01
8.95969868e-01 -4.22388583e-01 1.21070063e+00 2.27267787e-01
-7.09573984e-01 1.10039704e-01 -1.56040624e-01 -3.06842089e-01
-3.89408171e-01 -2.34409422e-03 -1.84250787e-01 4.16500084e-02
-1.74217224e-01 -6.92780554e-01 -1.05449474e+00 2.35516280e-01
-8.67080569e-01 9.27414224e-02 4.77590084e-01 8.89099896e-01
9.36760008e-01 -4.29454386e-01 5.18253863e-01 -7.88052261e-01
3.31727207e-01 -3.96920115e-01 -5.49437344e-01 1.24208756e-01
-6.61629081e-01 -1.59953669e-01 4.71106738e-01 -1.97099671e-01
-4.18668479e-01 3.32994342e-01 -2.06337571e-01 -5.58150709e-01
-1.84706002e-01 3.06095183e-01 2.53765076e-01 -1.01455629e-01
4.72486585e-01 2.39574537e-01 3.38410556e-01 -3.36077452e-01
1.00785471e-01 2.27898002e-01 7.29324102e-01 -4.18124586e-01
4.75826353e-01 6.76755309e-01 3.42267007e-01 -5.41307271e-01
-6.64375126e-01 -3.27872485e-01 -1.40507293e+00 -2.10565627e-01
1.40534282e+00 -6.95925891e-01 -7.80056417e-01 4.49528188e-01
-1.02787220e+00 -5.27557909e-01 -3.78014922e-01 6.79658592e-01
-7.49688804e-01 6.10241771e-01 -9.33610320e-01 -1.55975610e-01
-9.51737761e-01 -1.30752027e+00 8.46723497e-01 9.22437757e-02
-6.91544339e-02 -1.23357117e+00 1.23770557e-01 3.12095493e-01
6.70899451e-01 9.49109077e-01 7.83841729e-01 -7.40425646e-01
-2.78442353e-01 -8.24035332e-02 -2.72806197e-01 6.39199018e-01
3.43802907e-02 -4.23171610e-01 -6.59513831e-01 -4.48365003e-01
2.65961826e-01 -1.64266855e-01 7.76795685e-01 9.59748089e-01
1.43041205e+00 -2.84029126e-01 -1.12669900e-01 1.06701875e+00
1.35782743e+00 1.10078700e-01 4.96219665e-01 3.07597537e-02
8.09139132e-01 3.16385716e-01 1.54988438e-01 2.57084787e-01
3.32161754e-01 4.91600007e-01 6.52947009e-01 -5.18306971e-01
-1.85116515e-01 3.23651463e-01 -2.84544468e-01 1.01700854e+00
-3.95600706e-01 6.25787854e-01 -1.21641886e+00 5.92999876e-01
-1.56655204e+00 -6.84767604e-01 -1.57842815e-01 2.26721120e+00
9.40257967e-01 -1.61185563e-01 2.05529660e-01 -1.48270458e-01
7.34201729e-01 -1.63184166e-01 -5.08716822e-01 -2.37581909e-01
1.26594707e-01 4.65088010e-01 4.65639025e-01 4.22479361e-01
-1.51023698e+00 4.63777661e-01 5.93507385e+00 3.47259521e-01
-1.33087945e+00 7.64983743e-02 1.09804273e+00 2.14382634e-01
1.27000257e-01 -2.62725502e-01 -2.00687811e-01 4.59319949e-01
6.66157901e-01 -2.12670881e-02 2.04894364e-01 7.20581770e-01
-1.11964559e-02 2.69766271e-01 -8.72974753e-01 9.43438828e-01
2.20502187e-02 -1.51119995e+00 -2.73036391e-01 1.91199347e-01
6.88442528e-01 2.44295597e-01 -2.57311136e-01 4.90359031e-02
-2.11333945e-01 -1.34250748e+00 5.41106880e-01 6.56375647e-01
1.03813469e+00 -7.12155223e-01 1.01948440e+00 2.42885709e-01
-1.10049260e+00 1.87805250e-01 -3.05178881e-01 3.56323898e-01
-1.01088602e-02 7.45157599e-01 -8.14685762e-01 5.93231618e-01
7.32899904e-01 7.45272994e-01 -3.35874051e-01 1.10470915e+00
1.28534749e-01 4.62871283e-01 -1.05616771e-01 5.63222289e-01
2.09818363e-01 -6.44157887e-01 5.36298752e-01 1.40563917e+00
2.96821773e-01 1.46974534e-01 4.63020295e-01 1.10368764e+00
-3.85476291e-01 4.16494906e-01 -3.28703135e-01 3.56555462e-01
-3.06859035e-02 1.69546187e+00 -1.17369819e+00 -4.37129021e-01
-9.13251191e-03 9.08911526e-01 3.85352597e-02 6.82620611e-03
-8.06588054e-01 -3.80989224e-01 1.99364915e-01 3.24491799e-01
2.49688104e-01 1.25030484e-02 -4.40348923e-01 -1.29051173e+00
4.15814556e-02 -5.06028891e-01 2.31898502e-01 -2.74265766e-01
-1.20757556e+00 7.96168566e-01 -2.51535684e-01 -1.05052519e+00
-1.62972473e-02 -4.21116889e-01 -7.86880255e-01 9.02579665e-01
-1.56549096e+00 -1.05048287e+00 -3.41427982e-01 4.84573364e-01
1.18811280e-01 -1.38052022e-02 8.59413803e-01 3.82880181e-01
-4.29085702e-01 3.85331959e-01 -1.24882765e-01 8.95118237e-01
4.93159980e-01 -1.57692146e+00 1.65817097e-01 5.82451224e-01
-3.38783830e-01 6.26774073e-01 2.12534040e-01 -4.84224170e-01
-9.90471721e-01 -1.28514528e+00 6.94761753e-01 -1.41256303e-01
4.60992128e-01 -1.57947481e-01 -9.06023145e-01 6.54971719e-01
1.63544402e-01 8.89819145e-01 6.24817371e-01 -3.59842122e-01
-1.32203121e-02 -1.98435429e-02 -1.43847716e+00 2.80847549e-01
7.47443080e-01 -9.13010091e-02 -4.87804651e-01 3.55606139e-01
4.06670809e-01 -7.33865917e-01 -1.52152741e+00 7.77412355e-01
4.98235285e-01 -1.05846417e+00 1.12677443e+00 -3.02383423e-01
5.70574999e-01 -2.29775026e-01 3.27346414e-01 -1.17426634e+00
-3.25447112e-01 -4.82394904e-01 -9.86010656e-02 6.22947454e-01
9.18987468e-02 -4.51702952e-01 4.80296969e-01 3.62832636e-01
-3.76264870e-01 -1.17160821e+00 -1.03668106e+00 -6.53605103e-01
5.02461553e-01 -1.80571929e-01 3.36952060e-01 1.14096987e+00
-2.56470680e-01 1.26389369e-01 7.99059588e-03 -7.02721924e-02
9.21133280e-01 1.33699670e-01 2.30279595e-01 -1.58484721e+00
3.09219677e-03 -6.81708813e-01 -4.72198844e-01 -6.49160087e-01
1.94251556e-02 -1.31019139e+00 -1.44301504e-01 -1.40543151e+00
3.99617910e-01 -4.51700091e-01 -5.21007478e-01 3.94985437e-01
5.52410558e-02 3.61895442e-01 2.24690348e-01 1.07033409e-01
-3.51312101e-01 3.02309930e-01 1.72690344e+00 -1.29985154e-01
-1.13949299e-01 -2.18317029e-03 -4.72190142e-01 8.38700533e-01
8.78420353e-01 -3.37486088e-01 -7.41596296e-02 -2.78121501e-01
-1.52989924e-01 3.33199769e-01 6.63933694e-01 -1.12156081e+00
-2.41697337e-02 3.64327997e-01 6.12111151e-01 -3.65810454e-01
-2.42278829e-01 -8.56981874e-01 -1.33160517e-01 9.37600613e-01
-3.22484881e-01 4.38886881e-02 5.18456884e-02 2.12717652e-01
-1.42190054e-01 -2.42915805e-02 1.26187086e+00 -3.58736932e-01
1.96901411e-01 7.39371002e-01 -1.12487495e-01 2.44719774e-01
1.17911410e+00 -1.54726848e-03 1.67874366e-01 3.79102230e-02
-1.09642649e+00 1.57112092e-01 3.30173820e-01 -4.80016135e-02
5.56547046e-01 -1.33666706e+00 -9.01307285e-01 1.15695357e-01
-1.24344245e-01 4.22130406e-01 2.27789462e-01 1.45857668e+00
-1.01549017e+00 2.34800458e-01 -4.76222366e-01 -9.55033362e-01
-9.50028300e-01 4.40528989e-01 8.07658374e-01 -6.11006796e-01
-1.14787197e+00 4.91482973e-01 1.40609607e-01 -6.09493673e-01
-7.05950474e-03 -7.44724393e-01 -3.51366520e-01 -6.37706518e-02
4.52078819e-01 2.18152300e-01 6.35068566e-02 -7.25211263e-01
-4.04854923e-01 6.90585077e-01 1.38266563e-01 3.07766855e-01
1.52963328e+00 1.12043023e-01 -4.40266281e-01 2.16137439e-01
1.31790304e+00 -2.92670846e-01 -1.41928577e+00 -1.62784308e-01
-1.01380302e-02 1.27461804e-02 2.97515541e-01 -8.24413359e-01
-1.57910919e+00 1.02779973e+00 8.51462781e-01 1.05827205e-01
1.03991294e+00 -2.81445742e-01 1.09469664e+00 -1.75867066e-01
1.25509545e-01 -1.05789471e+00 -8.28446299e-02 5.04380882e-01
9.29708362e-01 -1.30578506e+00 -4.91355211e-02 -1.60704195e-01
-6.69610023e-01 1.37876058e+00 3.37939322e-01 -4.38992202e-01
8.62375140e-01 4.27427769e-01 2.35406607e-01 -2.56111801e-01
-9.80840027e-02 3.40554714e-02 4.25633222e-01 4.70801353e-01
6.01558506e-01 1.53120160e-01 -5.61045647e-01 6.96303248e-01
5.77158704e-02 6.07046224e-02 4.64566708e-01 5.87147355e-01
-2.79871851e-01 -7.54372895e-01 -6.21464057e-03 3.19643497e-01
-8.88462007e-01 -4.90395762e-02 1.11128420e-01 5.17052770e-01
1.76857218e-01 3.24219286e-01 1.00644954e-01 9.30512622e-02
6.16905503e-02 -2.28984244e-02 4.64825541e-01 -5.34236789e-01
-8.73745680e-01 2.45126963e-01 -6.30264044e-01 -7.07906961e-01
-3.93358082e-01 -5.00362098e-01 -1.70451725e+00 1.18995920e-01
1.02707706e-01 -4.44219224e-02 8.26523125e-01 8.11335802e-01
3.09128225e-01 7.46204734e-01 6.23642445e-01 -9.18759525e-01
-4.23555225e-01 -9.65752780e-01 -6.64384604e-01 6.87510669e-01
3.51004392e-01 -3.21097791e-01 3.31644006e-02 2.19678506e-01] | [14.227895736694336, -2.392822265625] |
c935a7a5-28a4-43fa-a745-e2ca5ebe3e84 | seggroup-seg-level-supervision-for-3d | 2012.10217 | null | https://arxiv.org/abs/2012.10217v5 | https://arxiv.org/pdf/2012.10217v5.pdf | SegGroup: Seg-Level Supervision for 3D Instance and Semantic Segmentation | Most existing point cloud instance and semantic segmentation methods rely heavily on strong supervision signals, which require point-level labels for every point in the scene. However, such strong supervision suffers from large annotation costs, arousing the need to study efficient annotating. In this paper, we discover that the locations of instances matter for both instance and semantic 3D scene segmentation. By fully taking advantage of locations, we design a weakly-supervised point cloud segmentation method that only requires clicking on one point per instance to indicate its location for annotation. With over-segmentation for pre-processing, we extend these location annotations into segments as seg-level labels. We further design a segment grouping network (SegGroup) to generate point-level pseudo labels under seg-level labels by hierarchically grouping the unlabeled segments into the relevant nearby labeled segments, so that existing point-level supervised segmentation models can directly consume these pseudo labels for training. Experimental results show that our seg-level supervised method (SegGroup) achieves comparable results with the fully annotated point-level supervised methods. Moreover, it outperforms the recent weakly-supervised methods given a fixed annotation budget. Code is available at https://github.com/AnTao97/SegGroup. | ['Jie zhou', 'Jiwen Lu', 'Yi Wei', 'Yueqi Duan', 'An Tao'] | 2020-12-18 | null | null | null | null | ['3d-instance-segmentation-1'] | ['computer-vision'] | [ 1.09541900e-01 5.30078113e-01 -6.34694874e-01 -7.67654240e-01
-9.65775251e-01 -7.41390824e-01 2.54384279e-01 4.62505966e-01
-2.25868776e-01 2.24638730e-01 -3.76612544e-01 -3.21179390e-01
2.05403805e-01 -7.72967279e-01 -1.03143549e+00 -4.51588690e-01
3.99761891e-04 7.60470152e-01 9.13848042e-01 3.32519472e-01
2.75502056e-01 5.38027227e-01 -1.39497602e+00 -7.72461146e-02
9.87225175e-01 8.31664562e-01 4.28851455e-01 2.99037844e-01
-3.86132002e-01 3.25555503e-01 -4.04042661e-01 -1.59356818e-01
4.24786061e-01 -1.27325296e-01 -1.06066072e+00 4.32261825e-01
4.51973468e-01 -1.59852639e-01 1.29525706e-01 1.12160039e+00
4.95384000e-02 9.55671892e-02 5.20110130e-01 -1.29634750e+00
-1.64062440e-01 6.35471821e-01 -8.39534163e-01 -1.50599465e-01
1.12489343e-01 -3.88736315e-02 1.16242671e+00 -1.06663084e+00
5.60526311e-01 8.83010566e-01 8.11239600e-01 3.33090484e-01
-9.50342596e-01 -5.30990481e-01 5.14809012e-01 -1.91824347e-01
-1.52630746e+00 -9.87814087e-03 1.04997993e+00 -4.58155572e-01
6.53630376e-01 7.99322054e-02 4.68101829e-01 3.75603378e-01
-7.12742507e-01 9.88890946e-01 7.92614162e-01 -4.19422239e-01
3.70561630e-01 5.03326245e-02 4.48962778e-01 7.62528121e-01
3.31929587e-02 -3.88176173e-01 -3.11170310e-01 -7.77982101e-02
1.00751567e+00 1.55250058e-01 -3.93775254e-02 -6.36741459e-01
-1.33978045e+00 6.37080491e-01 7.06634045e-01 2.01603532e-01
-6.39921799e-02 2.16963321e-01 2.09328711e-01 -2.46728271e-01
8.19380045e-01 3.12938839e-01 -7.44400918e-01 3.74455601e-02
-1.14174581e+00 -1.68325096e-01 5.05350947e-01 1.53347445e+00
1.32431400e+00 -5.98610342e-01 6.02236688e-02 8.58473837e-01
3.99808645e-01 3.36031675e-01 -8.60773772e-02 -1.26192415e+00
4.96421337e-01 9.51451063e-01 8.20922926e-02 -7.34559119e-01
-3.61004740e-01 -4.62221324e-01 -3.95653725e-01 -3.89600508e-02
4.24561411e-01 2.22755577e-02 -1.24572170e+00 1.25070107e+00
7.25350261e-01 5.36098063e-01 -3.53605628e-01 1.00212646e+00
7.09347069e-01 5.81574440e-01 1.87259287e-01 1.43263772e-01
1.15058994e+00 -1.34954929e+00 -2.89085358e-01 -2.38862976e-01
1.08284748e+00 -5.16163170e-01 1.40510154e+00 1.45133361e-01
-9.67462599e-01 -5.93184829e-01 -8.66346955e-01 -2.88370758e-01
-3.62107486e-01 1.92132592e-01 6.19479775e-01 3.86994451e-01
-9.07232285e-01 5.33096611e-01 -1.07185233e+00 -2.63683975e-01
6.90950930e-01 3.02529871e-01 -7.12996721e-02 3.27833295e-02
-6.59160197e-01 2.65106618e-01 4.45128679e-01 -1.76035911e-02
-7.19083369e-01 -6.75211489e-01 -1.03942156e+00 -2.09389210e-01
6.80416226e-01 -4.24003869e-01 1.40314043e+00 -6.28555477e-01
-1.14384413e+00 1.26678288e+00 -4.10869986e-01 -1.84943229e-01
4.63011861e-01 -2.42582604e-01 1.26134798e-01 4.00737703e-01
7.33040214e-01 1.26707077e+00 5.21315157e-01 -1.78090191e+00
-8.98667872e-01 -4.56535339e-01 2.13314235e-01 2.90613174e-01
4.15807366e-02 -1.70903683e-01 -1.17098176e+00 -4.54644561e-01
8.01123083e-01 -9.29143131e-01 -5.85703135e-01 1.02534711e-01
-8.70221496e-01 -6.54824734e-01 1.06996012e+00 -1.41870573e-01
8.23207378e-01 -2.39070845e+00 -3.04665923e-01 3.80345941e-01
1.88483715e-01 -1.64154232e-01 1.28741875e-01 9.71275866e-02
2.61148587e-02 3.20314974e-01 -6.87399268e-01 -9.45424795e-01
3.16192284e-02 4.75231230e-01 -2.14744940e-01 3.74550581e-01
1.91945925e-01 9.08640802e-01 -1.16793454e+00 -9.06123400e-01
3.76219660e-01 7.94846192e-02 -6.43331110e-01 1.70457616e-01
-5.65596640e-01 6.46123409e-01 -7.19798386e-01 1.14890254e+00
6.49658918e-01 -6.34659648e-01 -3.49335521e-01 -1.80852711e-01
-1.23127542e-01 2.60971636e-01 -9.93490458e-01 2.07522178e+00
-1.89111173e-01 2.10348144e-01 -8.64781961e-02 -1.00724232e+00
9.86387074e-01 1.38807790e-02 7.55550861e-01 -1.20179936e-01
-4.53672670e-02 4.31204706e-01 -5.95657706e-01 -2.23764047e-01
3.88062268e-01 3.99606675e-02 -3.32074225e-01 2.87917167e-01
-1.15848452e-01 -5.48428774e-01 9.89845172e-02 3.74020487e-01
8.59000325e-01 5.02450645e-01 -2.02231288e-01 -3.76678049e-03
3.21899801e-01 5.38027167e-01 7.42130876e-01 6.85651064e-01
-2.72366703e-01 1.00648129e+00 3.26007456e-01 -1.68807879e-01
-8.84389222e-01 -8.70588005e-01 -3.65843266e-01 1.04560900e+00
8.48356545e-01 -4.14216042e-01 -9.63064849e-01 -9.30214286e-01
-1.20037474e-01 5.87257862e-01 -2.61822253e-01 3.11180294e-01
-5.79193652e-01 -3.10986578e-01 4.19135332e-01 7.43049741e-01
5.60161114e-01 -9.47187901e-01 -3.64667028e-01 -6.32714033e-02
-1.21679649e-01 -1.31651616e+00 -4.82093394e-01 4.84877676e-01
-1.09716988e+00 -1.02144706e+00 -7.51684487e-01 -1.15956724e+00
1.14289463e+00 4.06819850e-01 9.95386064e-01 3.33279520e-01
2.27425084e-01 3.77887398e-01 -5.46544313e-01 -2.70765901e-01
9.44465175e-02 4.73399699e-01 -2.20137984e-01 -3.50792199e-01
5.16433895e-01 -5.22583842e-01 -5.95181465e-01 7.66937971e-01
-6.00262284e-01 2.29064137e-01 4.20032650e-01 2.65209645e-01
1.34912157e+00 -9.53675248e-03 3.24237615e-01 -1.25384963e+00
-2.16108203e-01 -4.34160948e-01 -6.68631792e-01 -6.35439306e-02
-2.78284401e-01 -3.66996795e-01 2.71036923e-01 -9.11934376e-02
-7.72116721e-01 5.41094005e-01 -2.02463761e-01 -6.66240811e-01
-6.89618111e-01 4.10270482e-01 -3.67134988e-01 -3.42021585e-02
4.07673359e-01 -2.82632951e-02 -4.12575036e-01 -7.10117459e-01
5.05216002e-01 5.97825050e-01 6.49744630e-01 -7.63251185e-01
9.23537552e-01 6.73628449e-01 -1.82944268e-01 -6.75705194e-01
-1.34693444e+00 -9.88209903e-01 -1.20613635e+00 -1.69147685e-01
1.04989707e+00 -1.00099027e+00 -2.65300781e-01 2.35046580e-01
-1.16321242e+00 -7.85477161e-01 -5.44427633e-01 3.00812036e-01
-6.35277689e-01 5.34425795e-01 -5.64752042e-01 -5.52636623e-01
2.19329372e-01 -1.11880255e+00 1.70984495e+00 5.34488223e-02
-4.98369429e-03 -1.04237711e+00 -1.56841755e-01 6.57799840e-01
-4.15983796e-01 2.62867868e-01 5.18444121e-01 -6.78331852e-01
-9.46103275e-01 -3.15352529e-01 -3.84762883e-01 1.86047554e-01
7.47063756e-02 -1.36386022e-01 -8.88358593e-01 1.30094722e-01
-1.45594612e-01 -2.27245778e-01 6.41767383e-01 3.96379292e-01
1.67250156e+00 1.05224840e-01 -7.47219443e-01 8.11211050e-01
1.15680373e+00 -1.20353170e-01 1.29291371e-01 3.72793078e-01
1.33231008e+00 6.07536435e-01 1.05532801e+00 1.34898573e-01
6.34747267e-01 5.10305643e-01 5.78813434e-01 -4.23393607e-01
2.90444568e-02 -6.34246588e-01 -7.31031224e-02 7.31946766e-01
-1.19343221e-01 -2.17843965e-01 -1.17916489e+00 6.56395912e-01
-1.97033572e+00 -3.52778077e-01 -6.36227906e-01 1.99474680e+00
8.35623026e-01 4.00001019e-01 1.72078788e-01 2.02982888e-01
8.58465016e-01 5.53580225e-02 -7.98074901e-01 2.08302170e-01
1.21003374e-01 -7.36092171e-03 8.58085215e-01 5.53072333e-01
-1.38728476e+00 1.25445616e+00 5.27375174e+00 8.68468761e-01
-6.15133464e-01 2.10608795e-01 8.02657902e-01 2.41059348e-01
-2.63543248e-01 3.20927709e-01 -8.85677576e-01 4.39217508e-01
4.62566584e-01 3.00242215e-01 -1.93314388e-01 1.23405123e+00
3.99897873e-01 -1.68101460e-01 -1.13224304e+00 8.36628795e-01
-1.95753112e-01 -1.03424919e+00 -6.77119866e-02 5.31618185e-02
8.71755719e-01 3.51009816e-01 -3.12831402e-01 4.37945984e-02
2.92703688e-01 -5.98381937e-01 7.72996783e-01 8.03862214e-02
7.08255410e-01 -5.48313022e-01 6.02020264e-01 7.41783321e-01
-1.33117676e+00 4.20345992e-01 -4.53278601e-01 5.20535111e-02
4.16394770e-01 9.44826782e-01 -7.03809023e-01 4.99529302e-01
8.23831081e-01 1.11721516e+00 -5.02915800e-01 1.04921854e+00
-6.47874951e-01 9.38265085e-01 -7.44501114e-01 3.78211796e-01
4.87051576e-01 -2.97208786e-01 3.50371748e-01 1.05410779e+00
2.34358087e-01 2.81181514e-01 7.74872124e-01 8.78628433e-01
-1.66476041e-01 1.31132249e-02 -3.77326369e-01 3.85057688e-01
7.28713930e-01 1.14197314e+00 -1.44107342e+00 -5.44505537e-01
-3.44023138e-01 9.70073164e-01 2.00604260e-01 3.69030863e-01
-8.50875318e-01 -2.57019132e-01 1.93242043e-01 3.70112181e-01
2.28290141e-01 -5.08114040e-01 -7.35638499e-01 -9.61759269e-01
1.71332732e-01 -6.38488308e-02 3.99948180e-01 -8.97311449e-01
-1.14453280e+00 2.12691560e-01 1.84863165e-01 -1.47102714e+00
2.81849921e-01 -3.16477448e-01 -5.65875351e-01 4.29103196e-01
-1.66531169e+00 -1.29575193e+00 -4.89505380e-01 5.31020224e-01
7.32114732e-01 6.44299567e-01 3.30673486e-01 3.25621903e-01
-5.22189915e-01 3.76624614e-01 -4.32886720e-01 4.18953598e-01
4.86572683e-01 -1.54754066e+00 4.42863375e-01 6.53511286e-01
3.27033937e-01 4.71798331e-01 2.61526763e-01 -8.21746945e-01
-7.25803137e-01 -1.33997929e+00 7.94786334e-01 -7.42932200e-01
4.81881917e-01 -5.84071636e-01 -1.02546072e+00 8.73535931e-01
-2.70967066e-01 4.00499731e-01 6.13723397e-01 8.26359615e-02
-1.04449011e-01 2.76974440e-01 -1.08556807e+00 3.47496927e-01
1.56762552e+00 -4.41774368e-01 -6.07513905e-01 7.80183017e-01
1.21264672e+00 -6.12249732e-01 -7.99433231e-01 6.12985730e-01
-2.93807000e-01 -8.40146959e-01 1.01804650e+00 8.34978819e-02
3.53263766e-01 -9.09840107e-01 1.55171245e-01 -9.07308459e-01
-2.20508035e-02 -2.75234520e-01 3.13964151e-02 1.31645525e+00
6.64239943e-01 -4.54721957e-01 1.39544106e+00 6.51685417e-01
-6.70001388e-01 -7.56019533e-01 -6.87998414e-01 -8.46777141e-01
-6.26132935e-02 -8.00876975e-01 6.14201069e-01 1.19865620e+00
-6.66938722e-02 1.41841725e-01 2.38718480e-01 7.39246905e-01
8.45374882e-01 3.45550656e-01 8.87666881e-01 -1.22058475e+00
-2.32882481e-02 -2.31039986e-01 -3.84776652e-01 -1.75128460e+00
1.06105916e-01 -1.04896891e+00 3.72087687e-01 -1.69261670e+00
-9.05137062e-02 -1.17561018e+00 -1.17241137e-01 8.81875277e-01
-2.09209025e-01 6.52507246e-01 -1.06674105e-01 6.90655768e-01
-1.05366290e+00 3.95746171e-01 1.32860219e+00 -4.41643372e-02
-3.63726079e-01 2.88676053e-01 -3.57329428e-01 1.14774704e+00
9.11587059e-01 -5.37034929e-01 -4.90756303e-01 -5.57848334e-01
4.14418951e-02 -2.25598812e-01 3.63219112e-01 -1.05296898e+00
4.71200168e-01 -1.33611083e-01 2.59645120e-03 -1.17977858e+00
3.30830783e-01 -9.46018577e-01 -2.75501728e-01 -7.08367899e-02
-3.20450872e-01 -4.03906345e-01 -1.23244442e-01 6.21561944e-01
-3.65463495e-01 -4.57448810e-01 5.05818725e-01 -2.68394232e-01
-8.14423978e-01 6.48501039e-01 2.44091488e-02 6.06088601e-02
1.24254441e+00 -6.30052924e-01 2.11915880e-01 2.93201711e-02
-9.73957121e-01 6.54407442e-01 8.39653373e-01 1.09023243e-01
3.53208065e-01 -1.01552820e+00 -2.13406533e-01 -1.79302990e-02
4.02783930e-01 1.29876459e+00 -3.25074717e-02 6.51943862e-01
-6.19402349e-01 1.86334088e-01 5.81820250e-01 -1.25410211e+00
-9.78248835e-01 4.27818388e-01 1.05922975e-01 2.12005019e-01
-7.90918708e-01 1.09925878e+00 3.03706288e-01 -8.91827047e-01
3.09418023e-01 -6.41600072e-01 7.35913068e-02 -2.17352822e-01
-9.69740003e-02 2.23773822e-01 -9.54359099e-02 -6.29473150e-01
-3.45833808e-01 1.04675782e+00 1.51942417e-01 1.41256183e-01
1.23254347e+00 -1.64820537e-01 -1.56659439e-01 5.90479732e-01
1.02080011e+00 -4.51469086e-02 -1.46568990e+00 -2.58767009e-01
4.24961686e-01 -4.95019883e-01 -3.26783359e-02 -4.57543731e-01
-1.14103878e+00 8.74193013e-01 5.21319024e-02 2.21472278e-01
8.53681803e-01 6.74046695e-01 8.60908568e-01 3.04758281e-01
7.85751879e-01 -9.88000929e-01 -6.17626794e-02 4.38551575e-01
1.98620811e-01 -1.35985982e+00 -1.35865703e-01 -1.31558514e+00
-4.02813822e-01 7.02664316e-01 8.69576395e-01 -2.09839374e-01
8.57690692e-01 5.50826304e-02 2.77975738e-01 -5.66606522e-01
-1.21266454e-01 -3.47316414e-01 1.60956502e-01 5.60834110e-01
1.26378745e-01 6.08160831e-02 4.12417352e-02 3.68835479e-01
-2.23375991e-01 -1.70343533e-01 2.13115528e-01 1.12140119e+00
-6.23844266e-01 -1.16768467e+00 -3.63068670e-01 3.72467995e-01
-5.94753064e-02 5.88731691e-02 -3.81205440e-01 6.35611594e-01
4.19592619e-01 8.30432057e-01 2.92333663e-01 -6.99299797e-02
3.76848459e-01 -8.26212019e-02 5.05396398e-04 -1.27294385e+00
-1.81934908e-01 1.97288007e-01 -1.30237415e-01 -5.58205009e-01
-7.83908248e-01 -6.24943495e-01 -1.95584464e+00 2.73213267e-01
-6.26139820e-01 4.13205236e-01 6.42916024e-01 9.61956322e-01
4.09792244e-01 2.17244774e-01 7.25706875e-01 -1.20885646e+00
6.30607307e-02 -7.28416622e-01 -4.62583065e-01 3.98463190e-01
3.77732888e-02 -6.63628578e-01 -5.52579641e-01 3.13249677e-01] | [8.013051986694336, -3.180424213409424] |
5d6bc172-c5db-4605-81ac-6feb378d8b84 | 6d-rotation-representation-for-unconstrained | 2202.12555 | null | https://arxiv.org/abs/2202.12555v2 | https://arxiv.org/pdf/2202.12555v2.pdf | 6D Rotation Representation For Unconstrained Head Pose Estimation | In this paper, we present a method for unconstrained end-to-end head pose estimation. We address the problem of ambiguous rotation labels by introducing the rotation matrix formalism for our ground truth data and propose a continuous 6D rotation matrix representation for efficient and robust direct regression. This way, our method can learn the full rotation appearance which is contrary to previous approaches that restrict the pose prediction to a narrow-angle for satisfactory results. In addition, we propose a geodesic distance-based loss to penalize our network with respect to the SO(3) manifold geometry. Experiments on the public AFLW2000 and BIWI datasets demonstrate that our proposed method significantly outperforms other state-of-the-art methods by up to 20\%. We open-source our training and testing code along with our pre-trained models: https://github.com/thohemp/6DRepNet. | ['Ayoub Al-Hamadi', 'Ahmed A. Abdelrahman', 'Thorsten Hempel'] | 2022-02-25 | null | null | null | null | ['head-pose-estimation'] | ['computer-vision'] | [-2.75930494e-01 3.98064703e-01 -3.75065565e-01 -6.93446577e-01
-1.13901365e+00 -3.32801610e-01 3.99296373e-01 -4.93662149e-01
-6.57024980e-01 6.70027375e-01 3.97975534e-01 -3.15216243e-01
1.71861410e-01 -1.85307398e-01 -8.35669577e-01 -6.29838824e-01
1.47021011e-01 6.53807104e-01 -1.24497347e-01 -2.77260035e-01
8.21339414e-02 5.96483946e-01 -1.24135768e+00 -4.46095824e-01
4.69866604e-01 5.48436224e-01 -2.01573238e-01 3.89600307e-01
7.20712543e-01 2.20575258e-01 -2.13504195e-01 -4.77488995e-01
2.29521737e-01 -3.72327566e-02 -8.86289179e-01 2.77035665e-02
8.34240973e-01 -3.69925588e-01 -5.30895889e-01 8.21830034e-01
9.27438617e-01 1.83265358e-01 6.51205480e-01 -1.08243716e+00
-2.31452122e-01 2.41934329e-01 -6.89262211e-01 -1.94120169e-01
6.77988172e-01 -1.26900062e-01 9.11252558e-01 -1.18409050e+00
8.59595001e-01 1.13950968e+00 7.66343415e-01 7.46772408e-01
-1.02789187e+00 -6.45614803e-01 2.08101764e-01 2.17746586e-01
-1.88359511e+00 -8.56031895e-01 9.52520907e-01 -2.49865457e-01
7.30632067e-01 2.48234332e-01 4.79267567e-01 1.21243274e+00
-8.56964663e-02 8.03138673e-01 7.40412354e-01 -4.72538888e-01
-4.24970500e-02 -5.28462350e-01 1.75660834e-01 8.78273129e-01
3.26681644e-01 -3.04478370e-02 -3.89990240e-01 -4.77910638e-02
6.17234945e-01 -3.38744670e-01 -4.14900154e-01 -6.89180017e-01
-1.03940082e+00 9.42257941e-01 4.92627501e-01 -7.16109723e-02
-1.42496020e-01 4.69900481e-02 2.55592257e-01 -9.17159319e-02
5.75750053e-01 8.07539851e-04 -5.21214724e-01 -1.86447240e-02
-8.00171375e-01 4.15393323e-01 6.13493204e-01 1.08997881e+00
4.93758798e-01 -5.41241728e-02 2.24625707e-01 1.01349270e+00
8.88926923e-01 4.99145806e-01 3.44990134e-01 -1.16060829e+00
5.83761871e-01 -2.54925806e-02 -7.61968866e-02 -7.02215433e-01
-9.31345344e-01 -5.12122810e-01 -6.17114961e-01 -4.58844826e-02
7.66516924e-01 -2.41153866e-01 -9.37179208e-01 1.90009820e+00
7.15199053e-01 8.66339281e-02 -2.68658698e-01 1.03414452e+00
9.29933131e-01 9.55528468e-02 -1.94604322e-01 -1.83227435e-01
1.38875747e+00 -1.04066074e+00 -6.80056274e-01 -3.92344654e-01
9.35759246e-01 -8.96485865e-01 8.96912038e-01 3.98276925e-01
-1.10677254e+00 -1.37853280e-01 -9.89518464e-01 -3.06217283e-01
3.08791697e-02 3.19322765e-01 5.66343665e-01 6.40445769e-01
-1.21050930e+00 3.98303300e-01 -1.05815148e+00 -3.02000880e-01
1.27494231e-01 5.38368702e-01 -6.57426238e-01 -1.29963875e-01
-9.19409037e-01 1.06988144e+00 1.06006891e-01 4.34217006e-01
-3.42102975e-01 -4.09183234e-01 -1.11843228e+00 -6.61139965e-01
2.11586654e-01 -6.73771381e-01 1.52830112e+00 -1.38116971e-01
-1.98116338e+00 1.15643787e+00 -3.62076372e-01 -1.46213114e-01
8.48290026e-01 -5.55100679e-01 9.31944251e-02 7.00253411e-04
-6.24237098e-02 8.38684797e-01 5.57949483e-01 -1.08861220e+00
-1.70081943e-01 -6.55494809e-01 -8.07569176e-02 4.34030920e-01
2.24000365e-02 2.08023712e-02 -9.53759849e-01 -5.65063536e-01
6.46515429e-01 -1.48006690e+00 -2.58206725e-01 -3.81959304e-02
-6.91424072e-01 -3.09267044e-01 3.52744013e-01 -8.74212325e-01
8.81219804e-01 -1.92591417e+00 1.75691456e-01 2.12523267e-01
1.13706455e-01 -7.17317744e-06 -1.10672392e-01 -5.18330634e-02
-3.37726861e-01 -3.06248635e-01 -1.90808401e-01 -8.97754550e-01
3.94411050e-02 1.46645885e-02 -4.12286967e-02 1.29761851e+00
-3.40600044e-01 5.99544406e-01 -7.09577262e-01 -5.49567997e-01
2.13650182e-01 9.99234200e-01 -8.68147731e-01 7.34101608e-03
2.28849590e-01 7.61024296e-01 -3.15807402e-01 5.73347330e-01
9.55206156e-01 8.10756981e-02 3.01936656e-01 -2.52588779e-01
1.36754245e-01 4.94767129e-01 -1.24495721e+00 2.10275292e+00
-4.12379116e-01 4.44744468e-01 9.43542346e-02 -7.73444414e-01
7.15387940e-01 3.53219658e-01 5.93797088e-01 -4.73120928e-01
4.57088917e-01 1.99886173e-01 -2.21039340e-01 -9.58020389e-02
4.42461282e-01 5.52756749e-02 5.05910628e-02 1.39106765e-01
7.60445073e-02 -1.02684796e-01 -4.99861315e-02 -1.65789053e-01
5.44271290e-01 5.80628574e-01 2.87206292e-01 -2.82847345e-01
5.23447692e-01 -5.73795199e-01 6.54177308e-01 1.81021452e-01
-2.47631460e-01 1.15032518e+00 1.89122796e-01 -2.82354832e-01
-7.94376850e-01 -9.24968064e-01 -5.65015912e-01 1.15192354e+00
-2.15639040e-01 -3.27585161e-01 -1.04380560e+00 -6.22601211e-01
-1.50020465e-01 7.79045045e-01 -5.21153450e-01 1.64579347e-01
-1.07191133e+00 -8.62847567e-01 5.77421725e-01 5.79672754e-01
9.63620991e-02 -6.28765464e-01 -1.17126867e-01 -1.41807450e-02
-5.22764683e-01 -1.31401217e+00 -7.60991037e-01 2.32956912e-02
-8.82309377e-01 -9.95345652e-01 -8.65186453e-01 -8.70698810e-01
8.76204610e-01 6.79663643e-02 9.41707313e-01 -3.47419344e-02
-9.82960910e-02 1.79507196e-01 -2.20517546e-01 -1.93767279e-01
2.67030951e-02 4.03093398e-01 1.85203388e-01 -3.87588948e-01
3.44743520e-01 -4.28054780e-01 -7.94860899e-01 4.50746685e-01
-2.83862233e-01 1.86159294e-02 9.48206112e-02 6.20804012e-01
6.30823731e-01 -8.51154566e-01 3.04812759e-01 -6.30684853e-01
2.37028465e-01 -2.64718920e-01 -6.17178500e-01 -1.20733909e-01
-6.62339926e-01 3.24253440e-01 9.56329554e-02 -2.08890870e-01
-8.35746169e-01 5.03557801e-01 -6.86371982e-01 -2.36488357e-01
-2.30042294e-01 1.94746360e-01 -2.69757867e-01 -1.37891844e-01
5.44035375e-01 -1.33246720e-01 7.48623684e-02 -6.16980612e-01
7.17419922e-01 5.79856813e-01 5.95733464e-01 -6.53440773e-01
7.45927632e-01 5.54167986e-01 2.12512285e-01 -7.16153026e-01
-8.03531110e-01 -6.21143878e-01 -1.00261986e+00 -3.02177165e-02
8.23781788e-01 -1.04822218e+00 -8.11234653e-01 4.34978753e-01
-1.25029314e+00 -1.84836388e-01 2.00676352e-01 8.45059216e-01
-8.23500037e-01 6.05982959e-01 -5.93163490e-01 -6.49857581e-01
-4.95319963e-01 -1.40046728e+00 1.35958338e+00 -1.55779839e-01
-3.76312077e-01 -8.52320075e-01 4.06030804e-01 5.86594343e-01
-1.77371409e-02 3.19913298e-01 1.77169964e-01 -4.90862280e-01
-2.16326281e-01 -3.25626016e-01 5.46323918e-02 2.03077309e-02
-2.37876043e-01 -9.19550508e-02 -1.02191496e+00 -5.70749700e-01
-1.79563612e-01 -2.39935100e-01 7.37976015e-01 5.42839408e-01
1.06490874e+00 -2.01917887e-01 -2.87196875e-01 1.10655868e+00
1.07490218e+00 -2.48648092e-01 6.90817297e-01 4.70915377e-01
9.86681879e-01 5.84479034e-01 6.17599130e-01 3.00307602e-01
9.27018344e-01 1.11533463e+00 4.36068475e-01 -1.05933338e-01
-1.47639513e-01 -3.10817242e-01 3.49553138e-01 9.48128760e-01
-4.90392148e-01 -3.07009667e-02 -8.40678751e-01 2.94692487e-01
-1.77144539e+00 -6.19266629e-01 -1.17176734e-01 2.45442033e+00
8.83296669e-01 -3.49336080e-02 2.70098954e-01 1.34490490e-01
6.60477936e-01 2.82722116e-01 -3.01588625e-01 -1.91994071e-01
1.81313351e-01 2.54366159e-01 7.89777100e-01 9.44217801e-01
-1.17517519e+00 1.11401796e+00 6.21336460e+00 6.17583811e-01
-1.23864508e+00 2.40157485e-01 4.85896438e-01 -1.80366233e-01
2.62211729e-03 -2.66938508e-01 -1.25004220e+00 6.47013187e-02
8.55113447e-01 4.36633438e-01 3.45870495e-01 9.72551644e-01
2.11243466e-01 2.66521275e-01 -9.81453538e-01 1.03574562e+00
3.71132106e-01 -6.51609182e-01 -4.90096390e-01 2.52659887e-01
3.67087454e-01 4.73237723e-01 7.27495253e-02 1.37200892e-01
1.13328241e-01 -9.49851930e-01 8.26485038e-01 2.24843845e-01
1.07923019e+00 -7.42544651e-01 4.52655166e-01 1.77865207e-01
-1.16171706e+00 3.97867322e-01 -2.58574933e-01 1.97578341e-01
2.62846380e-01 2.59992927e-01 -1.03489065e+00 5.42380095e-01
3.78604442e-01 5.13943672e-01 -4.95487660e-01 1.10300112e+00
-6.71070635e-01 4.95586842e-01 -6.79258168e-01 2.46776685e-01
-9.53093320e-02 -2.43162826e-01 5.80964267e-01 1.12556744e+00
2.17711955e-01 -5.99718094e-02 -9.64498743e-02 2.08575651e-01
-2.78721005e-01 3.85227442e-01 -4.57229793e-01 7.36651123e-01
2.29238123e-01 1.14593625e+00 -5.71663022e-01 1.62255690e-01
-4.19204205e-01 8.15302849e-01 5.53523362e-01 4.81477469e-01
-9.06063914e-01 -2.72860557e-01 6.91190422e-01 1.63697645e-01
2.17392504e-01 -4.83518332e-01 -1.54345021e-01 -1.36169958e+00
2.35781237e-01 -7.29029119e-01 2.09323362e-01 -5.43227315e-01
-8.61792624e-01 6.06777608e-01 2.02524468e-01 -1.13792443e+00
-6.62411273e-01 -8.77047896e-01 -3.98830384e-01 6.26265287e-01
-1.51681912e+00 -1.33590472e+00 -6.69736937e-02 5.58685243e-01
3.81795108e-01 1.24503307e-01 8.41306090e-01 4.27150339e-01
-5.45496106e-01 1.16863596e+00 1.55246824e-01 3.00190955e-01
9.19479132e-01 -1.08603930e+00 5.37468314e-01 7.11463869e-01
1.15306541e-01 7.64516711e-01 9.42041814e-01 -3.00600469e-01
-1.50264204e+00 -8.80382955e-01 9.82955873e-01 -6.16971493e-01
3.63413215e-01 -5.13063192e-01 -6.66349888e-01 1.06731176e+00
2.54162867e-02 2.70537496e-01 5.52252114e-01 4.15438354e-01
-5.45741916e-01 7.41533488e-02 -1.17152727e+00 5.97714961e-01
1.32647693e+00 -2.03233540e-01 -5.89253247e-01 6.01591766e-01
4.88996297e-01 -8.96351337e-01 -7.04249918e-01 6.49123430e-01
8.42432976e-01 -6.59807146e-01 1.18451858e+00 -4.08216983e-01
-4.96457964e-02 -1.56442121e-01 -2.37413168e-01 -1.21399367e+00
-1.21398434e-01 -7.10869133e-01 -4.21780981e-02 7.87228286e-01
4.51351613e-01 -7.37822890e-01 1.04833376e+00 4.27318066e-01
-1.99367046e-01 -9.18613970e-01 -1.27309442e+00 -5.00833690e-01
5.29009759e-01 -7.02398002e-01 3.54916066e-01 7.94444621e-01
-6.21279106e-02 3.55787456e-01 -3.57802778e-01 2.52860218e-01
9.51244473e-01 -2.86890924e-01 8.02887380e-01 -1.09266853e+00
-5.57353869e-02 -4.04359162e-01 -5.20156980e-01 -1.26156187e+00
6.77550793e-01 -9.96742070e-01 1.75898805e-01 -1.43840575e+00
1.56989880e-02 -1.65675476e-01 9.28177088e-02 4.95499372e-01
2.20453776e-02 6.13733053e-01 6.60487413e-02 1.44819513e-01
-4.20160949e-01 5.76512039e-01 1.19102871e+00 2.23619372e-01
-1.22589357e-01 1.65369079e-01 -5.21727920e-01 1.08941400e+00
8.54793310e-01 -4.39080060e-01 -1.65091112e-01 -4.67985809e-01
5.96721955e-02 -5.27840704e-02 1.94061443e-01 -7.18777716e-01
8.01030770e-02 1.31021634e-01 3.46888870e-01 -8.17903280e-01
6.61804795e-01 -4.49772567e-01 -2.44056016e-01 2.15495363e-01
-1.20459810e-01 5.56653775e-02 -2.06146240e-02 9.56395715e-02
1.06223151e-01 -1.65225461e-01 9.50258017e-01 3.50206405e-01
-1.02409065e-01 4.04787004e-01 -2.26809885e-02 2.79163748e-01
6.25026882e-01 1.29238451e-02 -2.33762115e-01 -5.32721996e-01
-8.96965563e-01 8.65679532e-02 4.81013447e-01 3.68630171e-01
5.58267713e-01 -1.34712183e+00 -8.72899294e-01 1.83990270e-01
1.94358394e-01 1.68528721e-01 -5.98909445e-02 9.71340179e-01
-7.91835666e-01 6.45425379e-01 1.76006258e-01 -6.09438419e-01
-1.42401898e+00 1.43646032e-01 4.38553810e-01 -9.89309028e-02
-6.57566607e-01 7.71683156e-01 4.21086140e-02 -1.07690978e+00
3.98029298e-01 -1.77920043e-01 -3.15003216e-01 -8.65256116e-02
3.72409374e-01 3.61490846e-01 2.98398674e-01 -1.35071111e+00
-6.08413994e-01 9.00226057e-01 -8.57494026e-02 -3.56299073e-01
1.39761436e+00 -1.42178625e-01 9.10748839e-02 -1.86954811e-02
1.63613534e+00 2.45776698e-01 -1.09278345e+00 -2.53080308e-01
-1.72794953e-01 -2.51080543e-01 1.04416698e-01 -4.47634757e-01
-1.18096459e+00 7.72091091e-01 7.10514545e-01 -6.54681802e-01
8.02088559e-01 1.40063971e-01 5.97082257e-01 5.00545084e-01
3.19491088e-01 -1.00975668e+00 -1.97662771e-01 7.52862215e-01
1.05444109e+00 -1.25415504e+00 2.41361216e-01 -6.09342933e-01
-4.65562165e-01 1.01811159e+00 5.62631905e-01 -1.97227165e-01
7.99075425e-01 1.53285740e-02 3.71499956e-01 3.08075137e-02
-1.53821424e-01 -1.52322263e-01 6.06737792e-01 5.36819100e-01
9.96857822e-01 1.51451200e-01 -5.65847695e-01 2.77725726e-01
-8.19638968e-01 -1.04875922e-01 3.38152289e-01 7.80892193e-01
-1.04868233e-01 -1.33270955e+00 -5.81808388e-01 -9.56375301e-02
-6.21025562e-01 4.75077815e-02 6.96107820e-02 8.47793341e-01
-2.54453182e-01 7.53278077e-01 -1.54831007e-01 -2.48982236e-01
3.77484053e-01 2.00294212e-01 8.01489532e-01 -4.22806352e-01
4.62796092e-02 3.83117259e-01 2.04808205e-01 -6.07957840e-01
-2.39079550e-01 -9.30350661e-01 -1.38809752e+00 -1.88592568e-01
-3.72466624e-01 -6.74744844e-02 1.01677966e+00 8.90033782e-01
1.91465303e-01 6.66365102e-02 6.61658883e-01 -1.17079628e+00
-6.61252797e-01 -1.19856632e+00 -3.73665392e-01 2.85473228e-01
4.28535670e-01 -8.79189670e-01 -5.75805604e-01 -1.66198343e-01] | [13.656578063964844, 0.2563970983028412] |
33bdfb67-0630-4544-9b95-2e329bbc9262 | adapting-pre-trained-language-models-for | 2302.13812 | null | https://arxiv.org/abs/2302.13812v1 | https://arxiv.org/pdf/2302.13812v1.pdf | Adapting Pre-trained Language Models for Quantum Natural Language Processing | The emerging classical-quantum transfer learning paradigm has brought a decent performance to quantum computational models in many tasks, such as computer vision, by enabling a combination of quantum models and classical pre-trained neural networks. However, using quantum computing with pre-trained models has yet to be explored in natural language processing (NLP). Due to the high linearity constraints of the underlying quantum computing infrastructures, existing Quantum NLP models are limited in performance on real tasks. We fill this gap by pre-training a sentence state with complex-valued BERT-like architecture, and adapting it to the classical-quantum transfer learning scheme for sentence classification. On quantum simulation experiments, the pre-trained representation can bring 50\% to 60\% increases to the capacity of end-to-end quantum models. | ['Qun Liu', 'Christina Lioma', 'Yudong Zhu', 'Benyou Wang', 'Qiuchi Li'] | 2023-02-24 | null | null | null | null | ['sentence-classification'] | ['natural-language-processing'] | [ 4.56731111e-01 2.53981918e-01 1.83569882e-02 -4.25837457e-01
-1.03459442e+00 -3.77717078e-01 7.96220601e-01 2.08900124e-01
-5.32155037e-01 6.50086045e-01 -1.06055573e-01 -6.97140574e-01
2.38202497e-01 -1.17508352e+00 -7.62693405e-01 -4.34393287e-01
-9.88111421e-02 5.82270563e-01 2.29903776e-02 -6.49611175e-01
3.60763222e-01 -3.46605889e-02 -1.11132824e+00 6.48981512e-01
9.20856535e-01 7.00784266e-01 -2.06553116e-01 8.69025588e-01
6.74485564e-02 5.47715485e-01 -1.69461071e-01 -6.42163396e-01
2.69981295e-01 -8.20773840e-01 -9.51351404e-01 -8.64113390e-01
2.63200879e-01 -3.38128120e-01 -9.05197799e-01 1.41238534e+00
3.28113586e-01 2.17230022e-01 6.86958194e-01 -5.74050546e-01
-9.07106221e-01 4.69318658e-01 2.16663837e-01 3.19075882e-01
3.70527834e-01 4.61079806e-01 1.17673123e+00 -3.55505019e-01
6.73651755e-01 1.15189910e+00 4.04828191e-01 8.41944039e-01
-1.58109200e+00 -5.70413232e-01 -1.07053041e+00 6.73583388e-01
-1.31900597e+00 -3.90411258e-01 3.54193211e-01 -1.87512282e-02
1.75287926e+00 -1.79257512e-01 3.92230302e-01 9.15075481e-01
8.33262384e-01 2.59080112e-01 1.36091363e+00 -7.61594474e-01
3.97757769e-01 7.86694363e-02 1.11780912e-01 9.31935191e-01
-2.51677692e-01 6.44543469e-01 -7.63049781e-01 -6.95264488e-02
3.24916780e-01 -2.48297811e-01 2.74800837e-01 1.99351579e-01
-1.11767042e+00 1.00721490e+00 9.55313623e-01 3.09539855e-01
-1.70406252e-01 4.48085040e-01 5.62589347e-01 5.95973253e-01
2.99721181e-01 7.60612369e-01 -3.24677259e-01 -2.34203890e-01
-7.42467284e-01 4.89956848e-02 7.25948691e-01 7.42993712e-01
1.19359815e+00 -3.66248190e-01 -7.14471936e-02 1.04335859e-01
6.27566725e-02 7.39452362e-01 2.14968994e-01 -8.14699233e-01
3.58669221e-01 2.13778123e-01 -1.91108093e-01 -3.32225055e-01
-3.85344565e-01 -1.61765814e-01 -8.53038132e-01 -1.28993139e-01
3.09060246e-01 2.23509725e-02 -7.86999762e-01 1.49525428e+00
-3.55891942e-04 3.24742585e-01 6.68636739e-01 9.01391804e-01
5.27443945e-01 9.99976695e-01 2.10073769e-01 -8.65223780e-02
1.33675575e+00 -7.14149952e-01 -3.67813200e-01 -1.55466348e-01
1.24375224e+00 -6.77823126e-01 8.14992607e-01 2.47191623e-01
-8.42697024e-01 -4.71913129e-01 -1.23483157e+00 -3.52494836e-01
-4.22769666e-01 -5.20595670e-01 1.07358587e+00 9.63136077e-01
-9.35644805e-01 1.22076297e+00 -9.39798295e-01 -3.51301074e-01
2.82336205e-01 6.24332428e-01 -3.73452991e-01 -3.94884080e-01
-1.79395485e+00 1.10574508e+00 9.29738402e-01 -9.65778157e-02
-7.31200218e-01 -3.52493942e-01 -5.03750682e-01 1.22344002e-01
9.97957960e-03 -1.23756945e+00 1.26657593e+00 -4.39331293e-01
-2.08887768e+00 8.71783733e-01 -1.53640658e-01 -8.04185212e-01
-1.87111378e-01 1.08076222e-01 -4.08498079e-01 4.00075793e-01
-1.51823893e-01 6.95801437e-01 6.53412044e-01 -3.15855980e-01
-2.38259211e-01 -3.72876555e-01 3.94264966e-01 2.72680223e-02
-7.89171979e-02 1.48119768e-02 1.97916120e-01 4.40461904e-01
2.13793352e-01 -1.21595538e+00 -4.33911800e-01 -6.93257987e-01
-2.02547247e-03 -3.67433071e-01 2.91504353e-01 -1.37872070e-01
6.49819314e-01 -2.02814651e+00 9.37436149e-02 -1.39531776e-01
-2.13527568e-02 4.89641845e-01 -2.46730357e-01 8.12050939e-01
1.56168774e-01 7.70785138e-02 -1.99693665e-01 -1.51132613e-01
2.68295527e-01 3.05450857e-01 -4.65222657e-01 4.58678961e-01
5.25306284e-01 1.37653673e+00 -1.10580289e+00 -3.81451041e-01
2.74915010e-01 2.15952665e-01 -1.03720951e+00 -2.64446717e-02
-4.21939969e-01 7.62354195e-01 -3.92389446e-01 1.42881334e-01
5.68134785e-01 -3.85874927e-01 1.30560920e-01 1.10988051e-01
1.62174627e-02 9.99568224e-01 -4.48333085e-01 2.10832500e+00
-5.43517113e-01 5.11764407e-01 -3.90108943e-01 -1.00972605e+00
5.58577418e-01 2.01492116e-01 -2.39395164e-02 -1.19916022e+00
2.44247809e-01 4.27357584e-01 5.26205242e-01 -4.05273825e-01
6.26334071e-01 -9.24000442e-01 -2.73199558e-01 5.51616371e-01
5.22868574e-01 -7.98850417e-01 7.83050880e-02 3.31550360e-01
1.17333829e+00 3.22239511e-02 4.78725955e-02 -1.60161763e-01
4.75340694e-01 1.99431330e-01 1.10360540e-01 8.71857643e-01
-5.78158200e-01 2.31036454e-01 2.85902768e-01 -5.21754205e-01
-1.39604664e+00 -1.19789469e+00 -4.97234792e-01 1.10033190e+00
2.95847654e-02 -5.66240251e-01 -7.49583244e-01 -2.22588196e-01
-5.20500302e-01 9.66478050e-01 -2.73665398e-01 -7.50219762e-01
-4.30406660e-01 -9.94150877e-01 8.60041380e-01 -2.50508618e-02
5.34562409e-01 -9.51759696e-01 -2.43750677e-01 3.47539097e-01
1.81090832e-01 -1.48068464e+00 1.91213101e-01 4.50512528e-01
-1.05207121e+00 -5.86091697e-01 -4.37031798e-02 -4.74678695e-01
3.28987747e-01 -1.74974605e-01 9.73986626e-01 -1.48474157e-01
-1.58752844e-01 -1.81907371e-01 -4.89257723e-01 -8.73541757e-02
-1.10166109e+00 3.19772124e-01 3.44238788e-01 -3.99194032e-01
8.10528100e-01 -4.89790082e-01 -5.76882005e-01 -3.47644180e-01
-9.47297871e-01 1.51878759e-01 6.92434788e-01 1.15850270e+00
1.33755296e-01 -2.33758226e-01 4.02892500e-01 -6.28452539e-01
4.61185962e-01 -9.03375149e-02 -4.13317561e-01 3.62738483e-02
-5.50068200e-01 6.16063178e-01 9.72884178e-01 -7.76318461e-02
-8.74195814e-01 -2.84677297e-02 -3.70207489e-01 5.50214052e-02
-1.44387886e-01 7.21058428e-01 4.45170999e-01 -1.94162160e-01
1.15066695e+00 3.11460257e-01 -1.47969022e-01 2.83072650e-01
8.07728827e-01 7.58992612e-01 3.67535353e-01 -6.66634977e-01
8.61465335e-01 3.57023805e-01 5.81135988e-01 -9.35841620e-01
-1.20446062e+00 -2.37148166e-01 -9.68847513e-01 4.21380848e-01
1.25011933e+00 -7.88332403e-01 -7.89557934e-01 1.60094768e-01
-1.34899795e+00 -1.33428186e-01 -1.40459642e-01 9.92808282e-01
-7.80866027e-01 5.41447580e-01 -1.11099744e+00 -9.08618808e-01
-5.53888738e-01 -1.12694418e+00 9.95224655e-01 2.80360192e-01
2.97514081e-01 -1.00207233e+00 2.52132356e-01 5.17033458e-01
4.04736400e-01 -2.30815396e-01 1.19206357e+00 -4.55157787e-01
-8.55050623e-01 -5.20737410e-01 -2.93934286e-01 4.45782453e-01
-6.39429390e-01 -4.69672501e-01 -1.22309506e+00 -2.47428849e-01
7.38178417e-02 -9.43253398e-01 1.03068566e+00 -3.46216321e-01
3.86431307e-01 1.81450367e-01 3.02190725e-02 5.49313188e-01
1.35705626e+00 -1.71921909e-01 8.95616710e-01 6.24699146e-02
3.14836323e-01 1.78697959e-01 9.05976966e-02 -3.04176081e-02
2.78329611e-01 4.78658676e-01 3.94420445e-01 5.97796023e-01
2.00309381e-01 -3.10901850e-01 5.96624076e-01 1.38930404e+00
-2.27974221e-01 3.70322257e-01 -1.22513425e+00 -1.46218047e-01
-1.54988444e+00 -1.18968904e+00 -2.51262248e-01 2.15191793e+00
8.30747426e-01 4.75227028e-01 -5.17675340e-01 -2.01056346e-01
3.17902952e-01 -1.73400193e-01 -3.52383733e-01 -9.96953666e-01
-7.46154925e-03 9.20704544e-01 3.51187527e-01 2.91694641e-01
-1.13626432e+00 1.43034613e+00 6.17846298e+00 8.19971800e-01
-1.16862023e+00 4.97098327e-01 3.47290128e-01 4.63888705e-01
-4.60580178e-03 6.34212971e-01 -6.20617628e-01 3.38377394e-02
2.04292059e+00 -1.70915559e-01 1.03864682e+00 4.37466204e-01
-2.06749529e-01 -1.33603230e-01 -1.44345057e+00 1.10102117e+00
-1.13451526e-01 -1.49594498e+00 -4.01563533e-02 2.25890741e-01
8.49423826e-01 7.98442841e-01 -7.00739622e-02 9.97219503e-01
1.96330696e-02 -1.25114322e+00 2.42195278e-01 3.74818116e-01
9.27054942e-01 -6.21758401e-01 9.17053580e-01 8.31847012e-01
-6.78235888e-01 -1.71657018e-02 -9.52223301e-01 -7.52296805e-01
3.94616351e-02 1.45640716e-01 -1.07277143e+00 8.03692758e-01
2.42115512e-01 3.76515955e-01 -4.37846869e-01 3.76881033e-01
-3.38778526e-01 8.77084494e-01 -4.64144021e-01 -4.70685273e-01
6.17939591e-01 -7.11145043e-01 1.59683283e-02 9.70702946e-01
5.89245744e-02 4.27344471e-01 -2.36707535e-02 1.24369478e+00
-2.29273096e-01 4.35836613e-02 -7.63271570e-01 -5.19369125e-01
-1.81221720e-02 1.10749173e+00 -5.12148201e-01 -5.15863955e-01
-4.12164241e-01 1.14785886e+00 4.67749089e-01 7.80062051e-03
-7.46132135e-01 -4.02690351e-01 1.13831706e-01 -3.66472006e-01
-7.75545463e-02 -7.63576627e-01 -2.62810737e-01 -1.48282373e+00
-4.68610525e-01 -4.80601430e-01 -1.33429587e-01 -4.76951540e-01
-1.31940603e+00 4.67486024e-01 -3.81992072e-01 -9.00773704e-01
-4.58637774e-01 -9.13315177e-01 -6.59869432e-01 1.09839845e+00
-1.29119909e+00 -1.13899899e+00 5.05213916e-01 3.43319118e-01
-2.19453424e-01 -6.07161894e-02 1.52573395e+00 1.37681410e-01
-3.84163201e-01 4.04267073e-01 5.85688472e-01 1.90069616e-01
4.77071911e-01 -1.13962340e+00 7.20521927e-01 6.28225029e-01
4.49647516e-01 9.21310127e-01 7.33400822e-01 -1.38792787e-02
-2.02178717e+00 -7.32903600e-01 1.03192186e+00 -8.39625001e-01
1.14288020e+00 -6.05182827e-01 -7.71063149e-01 3.72851551e-01
3.37373167e-01 2.04128578e-01 9.19839442e-01 4.34143811e-01
-6.37463093e-01 1.86473429e-01 -9.13634300e-01 3.64476621e-01
7.77355194e-01 -1.58753550e+00 -8.64756167e-01 7.92529583e-01
7.13914871e-01 -2.66832769e-01 -1.09934437e+00 1.97920620e-01
3.74661386e-01 -8.73787999e-01 7.52702117e-01 -1.03912187e+00
6.41370416e-01 8.62122998e-02 -3.11299950e-01 -1.19044220e+00
-1.35040715e-01 -7.87257135e-01 1.20560452e-01 4.64744419e-01
4.43587393e-01 -6.98045552e-01 8.62873733e-01 6.47601128e-01
-2.77583241e-01 -3.95832241e-01 -1.47649407e+00 -7.36515284e-01
9.27666068e-01 -6.67157412e-01 1.43387839e-01 7.62669504e-01
6.19564652e-01 1.18870521e+00 -4.61310409e-02 5.83945513e-02
6.58358097e-01 1.88294262e-01 7.33543158e-01 -9.04666483e-01
-6.44758701e-01 -2.60998368e-01 -7.57301033e-01 -1.07457530e+00
4.04443502e-01 -1.70725226e+00 -3.39903347e-02 -1.11345720e+00
4.65128601e-01 -1.86316043e-01 -3.52421492e-01 1.81853510e-02
-2.28592232e-02 4.63024676e-01 2.93444335e-01 3.69819820e-01
-8.29851449e-01 7.75551200e-01 1.25690687e+00 -2.56084263e-01
8.99605229e-02 -3.79689842e-01 -1.02320425e-01 3.81461233e-01
7.22114384e-01 -7.88993478e-01 7.61725679e-02 -3.94732147e-01
6.99690819e-01 2.99391031e-01 3.87364686e-01 -1.25154221e+00
3.29000592e-01 2.09874362e-01 -2.51729917e-02 -1.55447587e-01
5.89014471e-01 -6.07622378e-02 -5.07117391e-01 9.45957899e-01
-1.79201484e-01 -4.17139620e-01 -4.12525125e-02 4.91303444e-01
-1.37273774e-01 -4.82343495e-01 8.96232486e-01 -2.15364486e-01
-4.62476462e-01 1.58633694e-01 -2.37610996e-01 -6.32846281e-02
7.07036734e-01 1.94265679e-01 -6.21813774e-01 -9.10841450e-02
-6.44363999e-01 -2.00219050e-01 3.40396911e-01 -1.05918005e-01
2.61403888e-01 -8.33249569e-01 -4.85189885e-01 1.21073976e-01
1.76518038e-01 -2.41970062e-01 3.24656487e-01 8.97541702e-01
-8.67212117e-01 1.15161741e+00 -3.33158612e-01 -6.80614114e-01
-3.81179661e-01 7.62444317e-01 3.38887244e-01 -3.91786486e-01
-3.49372208e-01 6.01429045e-01 -1.11461639e-01 -8.76945734e-01
-5.56427181e-01 -3.26402038e-01 4.19386595e-01 -6.34214878e-01
3.15843940e-01 4.53752559e-03 2.26554722e-01 -7.41009891e-01
-3.15212935e-01 3.25026006e-01 3.73206823e-03 -2.34789953e-01
1.07357979e+00 3.13211679e-01 -2.60832459e-01 4.82346207e-01
1.46775901e+00 -6.48500144e-01 -6.58889294e-01 -4.59749579e-01
1.34125873e-01 1.89637154e-01 1.68801293e-01 -4.79751498e-01
4.16132584e-02 1.57752323e+00 5.68952024e-01 2.13117287e-01
6.16916537e-01 1.30136833e-01 1.07986844e+00 1.48526990e+00
1.06401455e+00 -1.08427858e+00 5.52422889e-02 1.22762382e+00
1.20940238e-01 -1.51851809e+00 -1.02944121e-01 -1.38339832e-01
-2.15881109e-01 1.40701330e+00 1.20208979e-01 -5.02926469e-01
5.56522727e-01 -3.68436396e-01 -1.32031232e-01 -2.27318898e-01
-8.57513428e-01 -3.22817117e-01 9.35152471e-02 2.40217030e-01
5.39562881e-01 4.18738514e-01 -2.87035644e-01 1.95885509e-01
-5.02370059e-01 1.16432786e-01 6.61184192e-01 8.73598099e-01
-5.44564903e-01 -1.45795739e+00 -1.91814169e-01 3.18788081e-01
-4.51583773e-01 -6.08694911e-01 7.20168557e-03 2.10016191e-01
2.70723328e-02 9.69718575e-01 -4.81300987e-02 -7.19301939e-01
1.14292074e-02 5.55453122e-01 9.74527419e-01 -9.76915538e-01
-5.89748979e-01 -3.37368071e-01 -7.12747592e-03 -3.00296843e-01
-3.17349643e-01 -3.86036664e-01 -1.65633249e+00 -6.39652252e-01
-5.57211757e-01 2.93706834e-01 1.02336049e+00 1.29110563e+00
4.20735091e-01 2.03113720e-01 4.56816822e-01 -9.98943448e-01
-1.41844451e+00 -1.21256721e+00 -3.22453827e-01 3.46454203e-01
-1.13635627e-03 -1.36816636e-01 -6.26860261e-02 -2.01673999e-01] | [5.570859909057617, 4.968654632568359] |
9e27a389-e6f3-4215-92db-42175cf6220e | one-shot-action-recognition-towards-novel | 2102.08997 | null | https://arxiv.org/abs/2102.08997v4 | https://arxiv.org/pdf/2102.08997v4.pdf | One-shot action recognition in challenging therapy scenarios | One-shot action recognition aims to recognize new action categories from a single reference example, typically referred to as the anchor example. This work presents a novel approach for one-shot action recognition in the wild that computes motion representations robust to variable kinematic conditions. One-shot action recognition is then performed by evaluating anchor and target motion representations. We also develop a set of complementary steps that boost the action recognition performance in the most challenging scenarios. Our approach is evaluated on the public NTU-120 one-shot action recognition benchmark, outperforming previous action recognition models. Besides, we evaluate our framework on a real use-case of therapy with autistic people. These recordings are particularly challenging due to high-level artifacts from the patient motion. Our results provide not only quantitative but also online qualitative measures, essential for the patient evaluation and monitoring during the actual therapy. | ['Ana C. Murillo', 'Luis Montesano', 'Alexandre Bernardino', 'Jose Santos-Victor', 'Laura Santos', 'Alberto Sabater'] | 2021-02-17 | null | null | null | null | ['one-shot-3d-action-recognition'] | ['computer-vision'] | [ 7.83666730e-01 2.57436261e-02 -4.69202340e-01 -1.03885055e-01
-1.13033295e+00 -2.23108053e-01 8.21752846e-01 -2.48197109e-01
-3.28918159e-01 4.41211611e-01 7.40727067e-01 5.22327363e-01
-2.22400755e-01 -9.66245160e-02 -1.24767728e-01 -8.03590536e-01
-2.85024017e-01 5.38479388e-01 3.21365982e-01 -1.73189402e-01
2.47863635e-01 7.40150034e-01 -1.69903064e+00 8.70080471e-01
3.75466913e-01 7.78627515e-01 -1.42924607e-01 1.02658617e+00
2.91416049e-01 1.23600960e+00 -7.51232386e-01 1.92752242e-01
1.74322411e-01 -8.31449449e-01 -9.89057422e-01 4.41335499e-01
3.76901537e-01 -5.09048700e-01 -2.94585735e-01 6.11144483e-01
8.17907035e-01 4.09384787e-01 4.76511210e-01 -1.19666862e+00
4.19993438e-02 3.28230232e-01 1.59870684e-02 3.48221749e-01
1.19299281e+00 7.18227267e-01 6.50849283e-01 -6.53179169e-01
1.10429919e+00 1.05427873e+00 6.82582200e-01 1.01931190e+00
-9.82244551e-01 -5.78037649e-02 -5.16425557e-02 7.79153228e-01
-1.00446391e+00 -8.49866450e-01 6.75318778e-01 -6.00270092e-01
1.19127917e+00 4.34879273e-01 8.37448299e-01 1.69969988e+00
1.66433826e-01 1.10190320e+00 7.34516859e-01 -3.60483766e-01
5.86042464e-01 -5.80374897e-01 1.36399120e-01 1.29399046e-01
-3.16366225e-01 1.97299957e-01 -6.80583537e-01 2.04260461e-02
4.76935893e-01 1.21785343e-01 -5.09611964e-01 -5.21395326e-01
-1.51912940e+00 1.69008330e-01 3.32874134e-02 1.03648520e+00
-8.02048445e-01 2.13725805e-01 6.88373148e-01 2.12276861e-01
1.09935470e-01 1.21068843e-01 -1.80736750e-01 -1.39322221e+00
-9.81950104e-01 8.08976069e-02 6.26932979e-01 7.27532923e-01
-1.37017354e-01 9.30159166e-02 -9.83793020e-01 5.13211429e-01
-1.08422704e-01 2.28642702e-01 8.17568421e-01 -8.64486456e-01
4.71187234e-01 5.13294041e-01 4.41572219e-01 -5.67357421e-01
-7.51031935e-01 7.13095954e-03 -3.83964568e-01 2.65252709e-01
3.85644257e-01 1.83313668e-01 -1.09333587e+00 1.45160687e+00
3.60229343e-01 5.31827986e-01 1.91523612e-01 9.25742686e-01
7.90574789e-01 1.32486254e-01 6.18051477e-02 -6.48659170e-01
1.05504465e+00 -1.13594341e+00 -1.10432661e+00 -8.26169252e-02
1.31330764e+00 -3.71027380e-01 1.02808952e+00 4.93776351e-01
-1.10630500e+00 -5.24849713e-01 -7.68181026e-01 4.11614388e-01
-4.59502451e-02 4.12756622e-01 4.28781539e-01 7.45147943e-01
-7.15711832e-01 1.03966403e+00 -1.33723783e+00 -6.89030111e-01
5.86101472e-01 3.65624994e-01 -7.10767150e-01 1.11047633e-01
-7.40683198e-01 9.33294415e-01 2.51634926e-01 4.16080989e-02
-9.73429382e-01 -5.79794586e-01 -7.25546479e-01 -3.05007458e-01
4.41550583e-01 -1.52746379e-01 1.68973100e+00 -1.10992169e+00
-2.08384824e+00 7.43531823e-01 7.60082975e-02 -4.52501416e-01
8.26869369e-01 -3.63887846e-01 -7.59137511e-01 5.19199312e-01
-3.39701846e-02 1.82567269e-01 7.55438685e-01 -6.94038749e-01
-3.50707114e-01 -3.62846941e-01 5.71357086e-03 2.04141200e-01
-1.67894006e-01 2.61840940e-01 -2.23733097e-01 -8.27024043e-01
2.45382618e-02 -9.83011484e-01 -4.46111336e-02 7.26744160e-02
-6.76477998e-02 4.54547182e-02 7.12680817e-01 -5.87108612e-01
1.14349961e+00 -2.13055325e+00 5.42739272e-01 -1.71511024e-01
-2.13964269e-01 5.34312963e-01 -1.95003092e-01 5.80445468e-01
-6.07042074e-01 -4.65719104e-01 -2.35203326e-01 -3.05951536e-01
-1.93026528e-01 2.38903403e-01 -2.76931170e-02 6.42097175e-01
-1.33932397e-01 9.48887408e-01 -9.44663823e-01 -2.91681945e-01
6.29720807e-01 2.90531039e-01 -2.77464956e-01 2.62263745e-01
3.69113870e-02 1.08250391e+00 -3.45719188e-01 8.59151363e-01
3.66629213e-02 6.22044504e-02 4.02494743e-02 -3.04028988e-01
1.51914194e-01 2.13994570e-02 -1.25050676e+00 2.17307019e+00
-2.29437962e-01 3.73923361e-01 -2.95429558e-01 -9.01249468e-01
5.00407755e-01 6.49577200e-01 1.38268518e+00 -5.55058360e-01
4.66042906e-01 -6.06562383e-02 6.02325834e-02 -9.93876815e-01
1.74683347e-01 -1.04562059e-01 -4.82443869e-02 5.88386595e-01
1.84272632e-01 1.93037137e-01 2.19019651e-01 -5.35910279e-02
1.66279268e+00 5.81729352e-01 8.05507600e-01 2.11497322e-01
7.02966630e-01 4.25172560e-02 5.00294864e-01 5.91492593e-01
-8.78422737e-01 8.52407217e-01 2.33498678e-01 -4.79703188e-01
-6.28503799e-01 -8.64951551e-01 1.92176551e-01 8.24458301e-01
-1.46176860e-01 -6.27415657e-01 -6.21840477e-01 -7.98267782e-01
-3.68172139e-01 7.21378267e-01 -8.72917891e-01 -4.17428851e-01
-6.88619196e-01 -3.04504275e-01 5.82489550e-01 1.00606906e+00
1.42014697e-01 -1.38778615e+00 -1.29562855e+00 4.01501358e-01
-2.35972255e-01 -1.27450860e+00 -2.73277670e-01 -2.13094532e-01
-8.35644662e-01 -1.31466508e+00 -9.98619795e-01 -2.15928450e-01
2.97331899e-01 3.05772293e-02 7.40654051e-01 -3.31947029e-01
-6.09727561e-01 1.15914190e+00 -9.39465106e-01 -1.54327407e-01
-7.03371286e-01 -4.48972136e-01 4.04636472e-01 3.54586214e-01
2.51186848e-01 -5.72608471e-01 -4.56787288e-01 4.47949886e-01
-7.37798750e-01 -7.60113448e-02 2.82514066e-01 6.82444990e-01
6.23308778e-01 -6.54280603e-01 1.91098496e-01 -2.95618087e-01
2.16121316e-01 -9.70045775e-02 1.00462604e-02 4.10591573e-01
-2.34546773e-02 -9.13998932e-02 3.85978073e-01 -8.52622092e-01
-8.62698019e-01 4.83224839e-01 -1.11021653e-01 -7.44799435e-01
-5.40783644e-01 2.93420851e-02 -1.71068504e-01 -1.61167949e-01
8.17460001e-01 1.18950665e-01 7.70990103e-02 -5.61920583e-01
3.79273713e-01 6.39678597e-01 7.90484846e-01 -4.31475565e-02
4.47437167e-01 7.61908948e-01 -1.01363689e-01 -8.90885293e-01
-5.22374690e-01 -6.32706106e-01 -1.27639043e+00 -8.19230199e-01
9.67213452e-01 -5.20441294e-01 -8.26522589e-01 7.41266012e-01
-8.68209124e-01 -4.64500695e-01 -8.95461619e-01 8.58147740e-01
-1.50983417e+00 4.52330798e-01 -2.96339154e-01 -8.97807896e-01
-3.22737694e-01 -1.03472853e+00 1.36769068e+00 -4.00972217e-02
-5.81650138e-01 -6.04245186e-01 5.29001355e-01 3.59797746e-01
1.64978758e-01 5.78576326e-01 1.16802484e-01 -9.64148760e-01
-1.09215423e-01 -4.83198732e-01 5.63101411e-01 1.18377395e-01
4.31240916e-01 -8.80493000e-02 -9.70609605e-01 -3.47192287e-01
1.24581605e-01 -4.58219320e-01 4.57406521e-01 2.53256619e-01
8.94455373e-01 -1.61763355e-02 -2.98977047e-01 3.48162681e-01
7.75160670e-01 4.52058762e-01 9.91447210e-01 1.02633789e-01
7.01656222e-01 3.49814564e-01 1.19433856e+00 6.83393538e-01
-4.10779476e-01 1.35427356e+00 1.94783121e-01 4.42385286e-01
-2.06367537e-01 2.05275163e-01 7.05808818e-01 6.57506883e-01
-6.49318337e-01 1.20086959e-02 -1.08071673e+00 3.78689885e-01
-2.03736520e+00 -1.41944909e+00 5.31467497e-02 2.08460045e+00
2.92478442e-01 -1.43287482e-03 4.37467575e-01 5.13323128e-01
3.36583197e-01 3.53404522e-01 -4.84590918e-01 -1.93037346e-01
2.47798920e-01 2.97414809e-01 1.13228314e-01 1.16487801e-01
-1.36423445e+00 8.57894182e-01 6.60869026e+00 5.78577578e-01
-1.01341963e+00 2.99787611e-01 -1.39140248e-01 -5.66421807e-01
5.78573227e-01 -2.77038693e-01 -3.12657386e-01 2.94245422e-01
1.19768941e+00 -8.35421607e-02 -1.41648352e-01 9.32261348e-01
5.50302148e-01 -1.78686500e-01 -1.35747170e+00 1.32748401e+00
5.16694963e-01 -1.21792090e+00 -3.10915530e-01 -2.06185073e-01
3.34473550e-01 -1.10431790e-01 -4.82458383e-01 3.01443458e-01
-2.25670353e-01 -7.69345284e-01 5.55970311e-01 9.74086344e-01
9.22538579e-01 -3.00111800e-01 4.51220453e-01 2.69919962e-01
-1.32656944e+00 -3.09493691e-01 3.02971274e-01 -5.96444942e-02
5.60181618e-01 -3.00323963e-01 -6.47637308e-01 8.45528245e-01
4.02613610e-01 1.30942357e+00 -5.49531341e-01 1.03425801e+00
-5.31000756e-02 4.12206948e-01 -6.08434640e-02 2.36748189e-01
1.65892363e-01 1.55879304e-01 9.65182304e-01 9.87385750e-01
2.46358424e-01 3.79068196e-01 1.69117510e-01 2.25107774e-01
5.84881604e-01 1.20742299e-01 -8.92688692e-01 -4.22273815e-01
-2.63872325e-01 9.37276363e-01 -7.78953910e-01 -3.37480575e-01
-2.49996319e-01 1.46464062e+00 -1.11762621e-01 5.56127131e-02
-9.05880690e-01 6.75214157e-02 7.13687122e-01 -1.32556558e-01
1.92122966e-01 -2.14281544e-01 2.34797806e-01 -1.21538174e+00
1.54939830e-01 -1.07929885e+00 5.72016358e-01 -8.52127314e-01
-6.69754744e-01 3.97916704e-01 2.92161554e-01 -2.16234136e+00
-8.94257843e-01 -5.58700085e-01 -7.20639169e-01 8.88468996e-02
-3.13866317e-01 -9.87358689e-01 -5.96953928e-01 6.84899151e-01
9.16113913e-01 -2.96184242e-01 1.11094582e+00 3.63362521e-01
-7.12934852e-01 4.52247977e-01 1.89758670e-02 -1.00513935e-01
5.68576455e-01 -7.21644640e-01 2.67394394e-01 7.29462266e-01
5.13252318e-01 -2.64352448e-02 8.21601331e-01 -6.46654606e-01
-1.50195193e+00 -7.35826254e-01 4.02196050e-01 -8.12192082e-01
6.65207803e-01 -1.57497078e-01 -8.41418684e-01 7.39910066e-01
-4.06701058e-01 2.47407913e-01 6.16375864e-01 -4.34584767e-01
1.80238008e-01 1.38734356e-01 -1.12565029e+00 5.90403974e-01
1.63649631e+00 -4.89634305e-01 -8.62760842e-01 6.43048167e-01
2.78426141e-01 -5.21447480e-01 -1.02360106e+00 6.28292501e-01
8.45019698e-01 -9.69455004e-01 8.91212642e-01 -1.16075814e+00
2.28759497e-01 2.18375749e-03 -5.73253483e-02 -1.14491808e+00
-9.58970860e-02 -7.72398293e-01 -4.07955170e-01 7.35967577e-01
-1.52274787e-01 -1.64529607e-01 8.99875581e-01 4.96032894e-01
-1.14802681e-01 -5.79119802e-01 -1.35146415e+00 -1.24940979e+00
-5.24474144e-01 -8.59027922e-01 1.19308114e-01 6.70673609e-01
2.62261271e-01 -2.72490054e-01 -6.57693088e-01 -3.91861767e-01
2.46370032e-01 -1.53024703e-01 8.75472486e-01 -8.78217220e-01
-3.77351850e-01 -3.14028502e-01 -1.41078913e+00 -5.08514822e-01
4.09416445e-02 -6.73751771e-01 1.26985222e-01 -1.43045545e+00
-8.72778669e-02 5.34161508e-01 -2.23188728e-01 5.41724503e-01
2.90870130e-01 1.84266150e-01 3.45652312e-01 4.05527681e-01
-7.53035605e-01 8.72916818e-01 1.01251507e+00 -2.12880462e-01
-3.87644559e-01 3.19157034e-01 2.16991916e-01 8.82326186e-01
4.88727838e-01 -3.39913994e-01 -4.75527197e-01 1.95628226e-01
-4.98859584e-01 2.96959043e-01 4.44174170e-01 -1.65324116e+00
5.48091978e-02 -3.12325865e-01 -4.57118042e-02 -7.72070050e-01
6.53239608e-01 -8.55282962e-01 3.11597079e-01 8.30956221e-01
-3.17486644e-01 -3.42370600e-01 1.51500687e-01 6.18728459e-01
-4.90497090e-02 -1.24302439e-01 8.12087834e-01 4.14539464e-02
-1.09166706e+00 1.71897322e-01 -4.63897169e-01 -5.55120520e-02
1.59660447e+00 -6.89440548e-01 -5.68143502e-02 -4.93651092e-01
-1.51007760e+00 -1.91844851e-01 2.66050249e-01 7.26188719e-01
5.91522038e-01 -1.63029706e+00 -4.60938036e-01 1.00019589e-01
6.47788823e-01 -7.89155185e-01 4.71310854e-01 1.56875861e+00
-3.46162587e-01 2.96719581e-01 -6.02440119e-01 -7.70414472e-01
-1.67452967e+00 5.77822328e-01 5.18144369e-01 -1.60766929e-01
-1.33770466e+00 3.72917712e-01 -3.26276779e-01 4.01832834e-02
5.76646745e-01 -3.56455386e-01 -5.39377630e-01 1.59465283e-01
1.04103732e+00 6.24330282e-01 1.62892208e-01 -1.17094159e+00
-7.55176365e-01 5.40729284e-01 1.76815882e-01 -3.07611883e-01
1.17641711e+00 1.07676618e-01 6.28108978e-01 9.64589238e-01
8.88285637e-01 -6.37764335e-01 -1.18091285e+00 3.67246605e-02
3.65129292e-01 -5.94895005e-01 -4.23509389e-01 -7.50198185e-01
-8.04978371e-01 6.79204881e-01 1.16755176e+00 -2.39452004e-01
1.14667213e+00 -2.87118815e-02 5.14032066e-01 6.20701075e-01
6.49481952e-01 -1.29096234e+00 4.29288298e-01 3.54352474e-01
1.23290992e+00 -1.02686167e+00 -2.93865260e-02 -1.73585624e-01
-9.35972512e-01 1.07795286e+00 4.42028791e-01 7.81110078e-02
4.20766383e-01 2.53111988e-01 6.90116435e-02 -2.16067821e-01
-5.61002314e-01 -3.61125916e-01 3.78384471e-01 7.11080849e-01
2.76000500e-01 5.64575335e-03 -5.57555735e-01 5.83965898e-01
3.11941057e-01 5.56242943e-01 4.69734758e-01 1.36396575e+00
-2.29585513e-01 -1.00224113e+00 -3.05881321e-01 2.90968418e-01
-1.54718608e-01 5.76728821e-01 -5.97680449e-01 8.37380052e-01
-2.63879150e-01 7.51353085e-01 -1.63054001e-02 -6.50061786e-01
7.65019417e-01 4.20462459e-01 7.67088771e-01 -6.89703405e-01
-7.07822025e-01 -1.61244810e-01 3.38703424e-01 -1.63239169e+00
-9.06321704e-01 -9.62965310e-01 -1.34838545e+00 3.13099951e-01
2.17366591e-01 -4.10173714e-01 3.83189231e-01 1.17487597e+00
3.17405701e-01 7.04511881e-01 5.03613293e-01 -1.18807614e+00
-7.28181422e-01 -1.21353781e+00 -4.99081284e-01 8.88819575e-01
1.16881058e-01 -1.00224149e+00 -2.15883523e-01 4.17170040e-02] | [8.084908485412598, 0.6032102704048157] |
8cc7fc8d-430e-4bde-ba30-439ed6285510 | ontology-based-production-simulation-with | null | null | https://www.mdpi.com/2076-3417/12/3/1608 | https://www.mdpi.com/2076-3417/12/3/1608 | Ontology-Based Production Simulation with OntologySim | Imagine the possibility to save a simulation at any time, modify or analyze it, and restart again with exactly the same state. The conceptualization and its concrete manifestation in the implementation OntologySim is demonstrated in this paper. The presented approach of a fully ontology-based simulation can solve current challenges in modeling and simulation in production science. Due to the individualization and customization of products and the resulting increase in complexity of production, a need for flexibly adaptable simulations arises. This need is exemplified in the trend towards Digital Twins and Digital Shadows. Their application to production systems, against the background of an ever increasing speed of change in such systems, is arduous. Moreover, missing understandability and human interpretability of current approaches hinders successful, goal oriented applications. The OntologySim can help solving this challenge by providing the ability to generate truly cyber physical systems, both interlocked with reality and providing a simulation framework. In a nutshell, this paper presents a discrete-event-based open-source simulation using multi-agency and ontology.
Keywords: ontology; production simulation; multi-agent; digital twin | ['Gisela Lanza', 'Andreas Kuhnle', 'Lars Kiefer', 'Marvin Carl May'] | 2022-02-03 | null | null | null | mdpi-2022-2 | ['manufacturing-simulation'] | ['knowledge-base'] | [-2.27795482e-01 2.37134606e-01 3.20626318e-01 4.20109555e-02
5.26207507e-01 -8.34255934e-01 1.11117923e+00 4.60362256e-01
-1.53024659e-01 5.06706834e-01 -1.63938388e-01 -1.75037578e-01
-8.56627524e-01 -1.17288244e+00 -3.30760568e-01 -3.41145098e-01
-1.89523071e-01 9.45398748e-01 3.45548511e-01 -9.47174013e-01
-3.11655272e-02 9.67967808e-01 -2.24740481e+00 1.04206249e-01
8.14435482e-01 6.18414462e-01 6.03554428e-01 6.70154035e-01
-1.87800333e-01 7.17198670e-01 -5.93277931e-01 -6.24151006e-02
-9.78224501e-02 -4.66877043e-01 -5.32843888e-01 1.00388452e-01
-4.88170475e-01 -1.65241193e-02 2.54665196e-01 7.64149427e-01
2.72404760e-01 1.56110361e-01 3.22049767e-01 -1.69489694e+00
-1.08497165e-01 3.71609271e-01 3.48993689e-01 -3.03878546e-01
8.45165610e-01 1.57591283e-01 2.09086031e-01 -2.59061992e-01
1.10512841e+00 1.30878663e+00 1.98657900e-01 6.55467659e-02
-9.99871671e-01 -2.27885872e-01 -1.57005385e-01 1.77844584e-01
-1.24158978e+00 -2.93297563e-02 4.76050615e-01 -4.88126636e-01
1.02516627e+00 5.50283968e-01 1.21602643e+00 7.96418846e-01
5.10480940e-01 -5.79791591e-02 1.06870651e+00 -7.78748214e-01
5.12920678e-01 4.93197292e-01 -1.68818429e-01 3.05735648e-01
7.96567082e-01 1.44930899e-01 -1.32127419e-01 8.56122524e-02
8.19655776e-01 7.32767805e-02 6.72802553e-02 -5.26778817e-01
-1.30555308e+00 1.86466798e-01 -4.07528222e-01 8.66464734e-01
-5.76116323e-01 5.31790331e-02 4.35222208e-01 4.01104003e-01
-2.97440261e-01 5.89294732e-01 -3.96805763e-01 -4.92745161e-01
-3.33369672e-01 6.76591396e-01 1.11470544e+00 8.27229559e-01
3.30793649e-01 2.35275060e-01 5.80355883e-01 2.83733737e-02
6.05587006e-01 4.09415066e-01 3.56541872e-01 -1.07937181e+00
-1.62433952e-01 9.79961336e-01 5.60383558e-01 -8.13464105e-01
-6.27641737e-01 -3.22572589e-01 -2.34603733e-01 1.01168811e+00
2.27952421e-01 1.92736946e-02 -5.03801286e-01 1.33163333e+00
8.91070426e-01 -1.15384743e-01 5.54128289e-01 7.32729495e-01
3.92603487e-01 6.64380848e-01 4.38524008e-01 -1.55770108e-01
1.61009037e+00 -4.46588963e-01 -1.46952462e+00 3.62258226e-01
4.96358633e-01 -8.14694941e-01 6.68440342e-01 6.19551301e-01
-1.08739972e+00 -3.61003548e-01 -1.30988824e+00 4.76357549e-01
-9.87337947e-01 -3.72667581e-01 8.34820747e-01 8.11208069e-01
-6.54131949e-01 7.00502276e-01 -6.91681862e-01 -8.45248997e-01
-3.25501263e-01 2.81041592e-01 -2.68145710e-01 2.74420112e-01
-1.25867987e+00 1.52341783e+00 6.77547216e-01 1.46889701e-01
-6.86038435e-01 -4.72391188e-01 -6.07443035e-01 9.05175209e-02
3.20398778e-01 -5.66694438e-01 1.19232380e+00 -1.06160498e+00
-1.87061226e+00 4.26904589e-01 6.22087240e-01 -3.31142843e-01
9.17380154e-01 3.09272110e-01 -1.25980175e+00 -8.86713341e-02
-1.18941329e-01 -1.15104266e-01 2.07876831e-01 -1.40297711e+00
-7.66869664e-01 -3.02173793e-01 4.49255347e-01 1.42678052e-01
1.12110578e-01 2.69959807e-01 2.00798482e-01 -7.35084340e-02
-7.73917437e-02 -7.10234225e-01 -4.58465070e-01 -3.91987115e-01
5.01386464e-01 1.14790194e-01 7.95086145e-01 -3.48839372e-01
1.11930954e+00 -1.89315140e+00 1.32580638e-01 1.55654699e-01
-2.07002684e-02 2.11677283e-01 2.97055244e-01 1.41181910e+00
2.79146954e-02 -4.31111827e-02 2.54698664e-01 3.48935217e-01
6.57853723e-01 4.40571457e-01 5.47461770e-02 1.23768687e-01
-2.68213302e-01 2.78172493e-01 -1.07854748e+00 -3.97175968e-01
8.23033690e-01 4.66958493e-01 1.59105298e-03 -1.26481608e-01
-4.67301607e-01 4.43664521e-01 -6.50150537e-01 5.45012355e-01
5.98688424e-01 1.13963947e-01 9.55258906e-01 1.09185800e-02
-7.40305603e-01 -2.12481961e-01 -1.84698594e+00 1.75264752e+00
-9.27432597e-01 3.91284488e-02 2.30323210e-01 -6.45206153e-01
8.55035663e-01 9.17692721e-01 5.04071832e-01 -1.03272402e+00
3.32579762e-01 6.18366182e-01 2.85146147e-01 -9.10389841e-01
6.99671924e-01 -2.25291118e-01 -1.94360346e-01 5.11353970e-01
-3.88086066e-02 -4.98318553e-01 5.18374145e-01 1.74337216e-02
7.25579917e-01 8.52387071e-01 4.20889020e-01 -4.36451614e-01
6.37151480e-01 1.87467620e-01 3.72487992e-01 1.81390554e-01
-4.11710106e-02 -4.79876436e-02 4.51800257e-01 -7.35330045e-01
-1.14509165e+00 -1.11980903e+00 -7.86831006e-02 5.41572869e-01
4.24756885e-01 -5.79038143e-01 -6.41861618e-01 -1.78165704e-01
2.21395493e-02 1.06804931e+00 -2.95217961e-01 1.27161428e-01
-4.31697696e-01 -3.93141717e-01 1.91617638e-01 -2.35768631e-01
1.86990529e-01 -1.04918003e+00 -1.41164899e+00 8.19253802e-01
2.13315457e-01 -1.21850586e+00 8.37569296e-01 -2.64833659e-01
-8.62855911e-01 -1.00638533e+00 6.47549778e-02 -4.41125512e-01
3.05132866e-01 -2.26802200e-01 1.03381276e+00 1.96607500e-01
-3.16047579e-01 4.08407658e-01 -5.38237393e-01 -9.27007556e-01
-1.15572858e+00 -2.97504276e-01 3.09653603e-03 -3.15970808e-01
-1.88066304e-01 -8.54675174e-01 -3.24687600e-01 1.71872020e-01
-1.41406465e+00 2.20145121e-01 7.88908899e-02 -3.69520895e-02
5.84747978e-02 4.02772158e-01 9.53752398e-01 -5.55021763e-01
7.72191763e-01 -4.54409987e-01 -9.89868224e-01 4.56344873e-01
-7.55867720e-01 -1.71327651e-01 7.63662100e-01 -8.91925469e-02
-1.34667373e+00 -1.59048244e-01 4.24425043e-02 1.82720557e-01
-4.30907816e-01 4.89745170e-01 -4.06280249e-01 1.24111474e-01
3.41082066e-01 -2.04132855e-01 4.75028723e-01 -4.42844212e-01
2.86927551e-01 4.60196137e-01 1.38133422e-01 -5.45214832e-01
5.27687311e-01 5.37787974e-01 4.25859660e-01 -6.12076163e-01
4.40648884e-01 2.31239513e-01 -4.04483169e-01 -9.16398764e-01
7.03313172e-01 -4.03185010e-01 -1.03079045e+00 3.61372679e-01
-1.15951836e+00 -2.32531101e-01 -7.34096110e-01 6.02052569e-01
-5.59601724e-01 1.93135008e-01 9.85584036e-02 -1.02174914e+00
1.46011800e-01 -1.08546257e+00 4.63523686e-01 3.35933030e-01
-3.35269719e-01 -1.03087711e+00 1.49594113e-01 1.56942546e-01
4.55109060e-01 8.13937306e-01 7.14625120e-01 -4.93712574e-01
-7.51792610e-01 -5.21717072e-01 4.17060673e-01 3.59986722e-02
1.83391154e-01 4.62219983e-01 -4.63130772e-01 1.26583830e-01
-1.19963564e-01 2.94323653e-01 -6.66222870e-01 -3.03811759e-01
3.08242381e-01 1.91292450e-01 -2.04727411e-01 -1.98147148e-01
1.87788379e+00 6.80516362e-01 8.87440860e-01 7.90573597e-01
-8.39019865e-02 9.00622487e-01 1.13212693e+00 7.65659451e-01
5.57922482e-01 9.89808917e-01 6.12569213e-01 2.21308604e-01
-2.53524870e-01 8.39403793e-02 5.34172319e-02 5.82858562e-01
-5.57021677e-01 -1.55590102e-01 -1.02344429e+00 3.65335613e-01
-2.06316710e+00 -1.12781847e+00 -5.68373322e-01 2.26760840e+00
1.15075983e-01 -4.38170554e-03 -1.91313580e-01 1.70363739e-01
6.47877276e-01 -7.01241419e-02 2.65600592e-01 -9.84021544e-01
-7.44817592e-03 2.17958644e-01 2.13492379e-01 4.55696583e-01
-3.51528347e-01 6.58158839e-01 5.56856871e+00 4.80980814e-01
-9.62713361e-01 4.50071245e-01 -4.45161492e-01 8.96762013e-02
-4.72521842e-01 4.05265421e-01 -2.55503505e-01 5.54583609e-01
1.40944409e+00 -8.45217288e-01 6.44353032e-01 4.23231393e-01
8.47475529e-01 -4.79519665e-01 -6.39360785e-01 4.65647191e-01
-1.91187188e-01 -1.52877915e+00 1.14979511e-02 1.00702062e-01
6.23869240e-01 -2.95732141e-01 -7.10568845e-01 -9.73387659e-02
3.45080256e-01 -7.11305678e-01 1.33575869e+00 8.67400825e-01
1.84582695e-01 -7.97986150e-01 7.61980653e-01 3.02535594e-01
-1.15380526e+00 -1.87155157e-01 2.67511934e-01 -5.48204541e-01
8.09309840e-01 3.01052541e-01 -4.54669982e-01 1.27861702e+00
4.59906697e-01 -2.98588157e-01 -3.63210551e-02 1.00990283e+00
6.78238645e-02 -1.46884292e-01 -5.14962018e-01 -3.14072549e-01
-6.95016906e-02 -7.58440077e-01 5.89341164e-01 9.96399701e-01
5.04613578e-01 -7.00138733e-02 -7.98914582e-02 6.02302670e-01
7.76149988e-01 1.22103408e-01 -7.90999472e-01 -1.19011223e-01
5.20722330e-01 1.27620888e+00 -9.78220642e-01 -4.36236680e-01
-1.58472732e-01 5.29379964e-01 -5.95899522e-01 1.68870956e-01
-1.10753095e+00 -5.45211196e-01 6.31123722e-01 4.32203442e-01
8.25669989e-03 -4.30288285e-01 -5.54433875e-02 -8.10483396e-01
-1.30519211e-01 -9.01891410e-01 -1.59739405e-02 -8.84222090e-01
-5.51944077e-01 4.80378091e-01 4.47622478e-01 -1.20887005e+00
-5.90409458e-01 -3.89086068e-01 -2.71100163e-01 7.05327392e-01
-1.11647975e+00 -1.41279411e+00 -4.83863175e-01 1.56795487e-01
8.85874406e-02 -1.31496368e-02 1.21934223e+00 6.13609195e-01
-2.01291025e-01 -4.50812608e-01 2.87862331e-01 -8.06859791e-01
2.15719268e-01 -1.06901217e+00 7.90139101e-03 6.39853179e-01
-4.41587836e-01 2.44630516e-01 1.29622555e+00 -7.05707014e-01
-1.64734805e+00 -3.73025119e-01 1.14529836e+00 -2.37625241e-01
9.84578848e-01 -3.23011428e-01 -5.45537472e-01 5.76968074e-01
5.04090905e-01 -2.65271783e-01 2.67654419e-01 -4.55713034e-01
3.84864628e-01 -3.87696266e-01 -1.42211008e+00 7.37196982e-01
9.52856302e-01 -1.17695838e-01 -6.16424084e-01 1.99523389e-01
4.81311172e-01 -2.45016411e-01 -1.35340834e+00 1.58702388e-01
8.88554692e-01 -1.26785910e+00 7.16814399e-01 -3.06449860e-01
-1.16283745e-01 -6.08966529e-01 8.55634362e-02 -9.92017388e-01
9.74264219e-02 -8.52923810e-01 1.06892146e-01 1.31038678e+00
1.16154879e-01 -1.21982825e+00 2.71457136e-01 6.41154051e-01
-3.43184203e-01 -1.26422480e-01 -9.97344553e-01 -1.11589396e+00
-2.71746397e-01 -4.51082498e-01 1.33313012e+00 1.08559859e+00
4.10352230e-01 -3.34986836e-01 3.23826641e-01 2.83167094e-01
5.29731929e-01 -5.66961206e-02 8.49134386e-01 -1.70509207e+00
-1.28647566e-01 -1.56660095e-01 -8.02370489e-01 3.06717604e-01
-2.84779847e-01 -4.12618876e-01 -4.31269199e-01 -2.08923411e+00
-5.78079998e-01 -4.29208905e-01 9.96328890e-02 -2.69101977e-01
8.96510839e-01 -2.75114179e-01 6.36782885e-01 3.76830138e-02
-3.25265884e-01 3.01682830e-01 1.32951796e+00 5.53848088e-01
-8.29467401e-02 -3.86163175e-01 -5.49934730e-02 7.40437984e-01
8.00504982e-01 -5.13408065e-01 -6.15874588e-01 -4.80858609e-02
7.22671866e-01 3.00777406e-01 4.45987403e-01 -1.45925009e+00
1.66992769e-01 -4.81714040e-01 -2.67836928e-01 -2.53771186e-01
3.47801298e-01 -1.59684300e+00 1.45963871e+00 7.84865022e-01
4.69949961e-01 4.23269957e-01 6.88298643e-02 2.33719513e-01
-1.19594917e-01 -6.60125673e-01 4.68435407e-01 -1.94106728e-01
-8.41826618e-01 -4.14004236e-01 -9.45360243e-01 -7.27907658e-01
1.66556609e+00 -6.14538074e-01 -2.97158062e-01 9.03649852e-02
-1.08683908e+00 4.03497461e-03 8.91761184e-01 5.97133577e-01
-1.36922851e-01 -9.56238627e-01 -2.18027964e-01 2.34069140e-03
-2.51720734e-02 -3.57330918e-01 5.86017072e-01 4.33846563e-01
-1.23417449e+00 2.85450339e-01 -8.40077579e-01 -5.08304946e-02
-9.29601014e-01 5.36349177e-01 5.38190424e-01 -2.74001807e-01
-5.60786009e-01 -3.74572843e-01 -3.39394897e-01 -4.09962147e-01
-2.49034360e-01 -3.24888438e-01 -2.79283136e-01 1.75745457e-01
2.75473803e-01 7.37186551e-01 3.08166683e-01 -4.80931580e-01
-3.29144299e-01 3.39693695e-01 7.03418076e-01 -5.69825411e-01
1.42970622e+00 -3.40501308e-01 -4.35745269e-01 6.60576761e-01
2.33785912e-01 6.65168911e-02 -9.00268912e-01 7.16510117e-01
1.36273980e-01 -5.15894830e-01 -1.40036657e-01 -1.18839085e+00
-4.39483047e-01 1.70045182e-01 7.54201531e-01 9.27804232e-01
7.90357947e-01 -1.54890910e-01 2.43011236e-01 1.38188362e-01
8.61330688e-01 -1.55462372e+00 -4.19097185e-01 1.19477883e-01
1.03847766e+00 -5.26095569e-01 2.65726238e-01 -7.08689392e-01
-3.83255482e-01 1.36528516e+00 3.72612089e-01 1.79231800e-02
4.87505764e-01 6.02759719e-01 1.68238264e-02 -5.62977254e-01
-6.15677714e-01 -2.38255620e-01 -7.04092264e-01 1.02901208e+00
1.63791806e-01 2.21043706e-01 -9.75799739e-01 5.48587382e-01
7.43197650e-02 6.38758659e-01 1.06163681e+00 1.40781093e+00
-3.43864411e-01 -1.57738340e+00 -8.37232471e-01 -3.23311687e-01
-2.83040792e-01 7.83953965e-01 4.93026301e-02 1.59586561e+00
6.31512702e-01 8.51932526e-01 2.62988985e-01 1.51635334e-01
9.37312484e-01 6.72459081e-02 7.91088104e-01 -1.73287153e-01
-1.13310528e+00 -2.88148731e-01 6.95849895e-01 -3.18191200e-01
-3.11443925e-01 -8.39405358e-01 -1.76694500e+00 -6.03563011e-01
-6.77272379e-02 3.39316815e-01 1.55442870e+00 8.03618550e-01
5.20445585e-01 9.38765705e-01 2.82448322e-01 -7.71696389e-01
-4.25217628e-01 -6.39131129e-01 -8.04899335e-01 3.25374037e-01
-2.79932290e-01 -8.46012235e-01 -8.47063214e-02 1.65681671e-02] | [8.824394226074219, 6.94346809387207] |
7e905474-31d2-4a1a-b0bf-c9b5c705baa6 | neural-approaches-to-entity-centric | 2304.07625 | null | https://arxiv.org/abs/2304.07625v1 | https://arxiv.org/pdf/2304.07625v1.pdf | Neural Approaches to Entity-Centric Information Extraction | Artificial Intelligence (AI) has huge impact on our daily lives with applications such as voice assistants, facial recognition, chatbots, autonomously driving cars, etc. Natural Language Processing (NLP) is a cross-discipline of AI and Linguistics, dedicated to study the understanding of the text. This is a very challenging area due to unstructured nature of the language, with many ambiguous and corner cases. In this thesis we address a very specific area of NLP that involves the understanding of entities (e.g., names of people, organizations, locations) in text. First, we introduce a radically different, entity-centric view of the information in text. We argue that instead of using individual mentions in text to understand their meaning, we should build applications that would work in terms of entity concepts. Next, we present a more detailed model on how the entity-centric approach can be used for the entity linking task. In our work, we show that this task can be improved by considering performing entity linking at the coreference cluster level rather than each of the mentions individually. In our next work, we further study how information from Knowledge Base entities can be integrated into text. Finally, we analyze the evolution of the entities from the evolving temporal perspective. | ['Klim Zaporojets'] | 2023-04-15 | null | null | null | null | ['entity-linking'] | ['natural-language-processing'] | [-9.92126837e-02 4.00742531e-01 -2.28163943e-01 -3.59731942e-01
-4.81627546e-02 -8.56803179e-01 8.20573032e-01 5.77464104e-01
-5.86937964e-01 1.07726419e+00 4.02219802e-01 -1.27536893e-01
-2.60898679e-01 -8.96097481e-01 -3.89100790e-01 -3.89027655e-01
1.47676095e-01 9.49313045e-01 5.71791947e-01 -6.45391047e-01
1.57433003e-01 6.56257451e-01 -1.66001141e+00 1.98183671e-01
6.29386246e-01 3.64084482e-01 7.46118575e-02 3.02100062e-01
-7.85221696e-01 6.70854568e-01 -6.08492732e-01 -7.17012048e-01
-1.84622645e-01 -1.59527168e-01 -1.38260365e+00 -2.98838645e-01
1.59241125e-01 4.01625872e-01 5.64055964e-02 1.15068245e+00
1.83395833e-01 1.96128607e-01 5.55043399e-01 -1.48281491e+00
-2.09687874e-01 1.11429405e+00 -4.35440361e-01 1.64752051e-01
5.22284627e-01 -5.57534814e-01 1.02878165e+00 -6.56269729e-01
1.20835328e+00 1.39843559e+00 4.95554745e-01 3.32126945e-01
-7.65198946e-01 -5.85401773e-01 2.76315421e-01 4.83324260e-01
-1.35395682e+00 -2.36429587e-01 5.19544542e-01 -5.77038288e-01
9.60685313e-01 2.56091326e-01 1.95559874e-01 6.69108450e-01
-2.93901414e-01 6.24213159e-01 6.18526578e-01 -7.74594963e-01
-1.71204567e-01 5.87445736e-01 8.13445807e-01 4.39748287e-01
5.16742766e-01 -3.68764430e-01 -4.15494770e-01 -1.68692209e-02
3.12200606e-01 -3.38199526e-01 -1.89136509e-02 -3.02798599e-01
-1.32214022e+00 8.87315154e-01 2.62025535e-01 1.17352653e+00
-4.23885673e-01 -1.65917277e-01 3.64705026e-01 -1.72610802e-03
2.20871896e-01 5.48471510e-01 -7.51130819e-01 -2.42467657e-01
-6.93189621e-01 1.79083273e-01 1.35435736e+00 1.02803695e+00
8.35487306e-01 -6.03463054e-01 2.71162987e-01 6.74515724e-01
2.80946761e-01 2.89566755e-01 3.79995227e-01 -8.01581800e-01
5.52689791e-01 8.26388001e-01 2.76928157e-01 -1.17885685e+00
-6.83806121e-01 -1.45183891e-01 -5.24914980e-01 -4.43124980e-01
5.10948956e-01 -3.44892293e-01 -5.33299029e-01 1.91647923e+00
5.61962306e-01 1.08012341e-01 4.36291784e-01 4.34454262e-01
1.06590784e+00 4.94386822e-01 3.86715978e-01 -4.54553246e-01
1.88534045e+00 -8.18088412e-01 -1.14249325e+00 -1.65271908e-01
8.07594001e-01 -6.57705724e-01 1.71524942e-01 -7.03975409e-02
-7.00457454e-01 -2.98241973e-01 -5.93553543e-01 -1.36048257e-01
-1.36132300e+00 1.48075730e-01 6.70938075e-01 4.30770099e-01
-7.75600731e-01 4.47646379e-01 -6.65296316e-01 -1.11350358e+00
-1.17424972e-01 5.78117609e-01 -6.81945086e-01 3.46509725e-01
-1.66193056e+00 1.32672131e+00 1.08150327e+00 -1.66797917e-02
2.96339929e-01 -4.41655427e-01 -9.06150758e-01 1.26614459e-02
7.92837858e-01 -6.41544044e-01 1.05359554e+00 -9.05210614e-01
-9.37832355e-01 1.10301423e+00 -5.10255754e-01 -6.40930116e-01
9.89006311e-02 -1.71403363e-01 -7.58819461e-01 3.35514313e-03
3.90676230e-01 6.24173522e-01 1.53349414e-01 -1.36127746e+00
-1.10987818e+00 -6.08584583e-01 2.17833176e-01 9.59388614e-02
-1.76301345e-01 4.00588810e-01 -5.17776251e-01 -3.85722965e-01
-6.18012473e-02 -1.08241105e+00 9.49137509e-02 -6.12856030e-01
-3.66498321e-01 -6.70690715e-01 9.63338673e-01 -5.80358863e-01
1.55903518e+00 -1.97179151e+00 3.53034377e-01 2.77799517e-01
2.23397657e-01 3.25747758e-01 3.04266572e-01 8.42554033e-01
-1.16574258e-01 4.23609108e-01 -2.35333145e-01 -1.09958962e-01
1.41474202e-01 5.48211753e-01 -2.69139051e-01 -6.82861656e-02
1.23228937e-01 8.77908647e-01 -1.02933979e+00 -7.92153060e-01
5.51505107e-03 2.87949115e-01 -1.36913791e-01 -3.85955930e-01
-2.11273320e-02 3.08172017e-01 -6.27095044e-01 4.96313274e-01
3.27175438e-01 1.64956115e-02 4.15993869e-01 -3.19875419e-01
-4.36214626e-01 3.64114791e-02 -1.36796391e+00 1.50085568e+00
-3.68626922e-01 8.41966450e-01 2.04699486e-01 -1.18061364e+00
7.55219936e-01 4.86760139e-01 5.70626020e-01 -2.73510605e-01
2.62134131e-02 2.75722593e-01 9.79118347e-02 -7.69233048e-01
8.76920342e-01 -2.02452838e-01 -3.52580667e-01 3.18753690e-01
1.71099082e-01 1.27358779e-01 6.81193888e-01 3.75925153e-01
8.31350505e-01 1.90079007e-02 7.26673305e-01 -2.37456039e-01
9.20913756e-01 5.03651738e-01 4.95029956e-01 4.22133863e-01
-1.62969545e-01 2.77150515e-02 4.82451141e-01 -3.58466923e-01
-9.59605277e-01 -5.95763385e-01 -3.49291474e-01 1.05521286e+00
2.14725941e-01 -4.41830665e-01 -7.45377839e-01 -7.56787896e-01
3.64199206e-02 9.43643749e-01 -5.78010380e-01 9.88109782e-02
-8.19276989e-01 -7.42215872e-01 6.50660217e-01 3.72011006e-01
4.09225434e-01 -1.22941005e+00 -6.27955556e-01 3.44680846e-01
-5.13275504e-01 -1.50398862e+00 1.35339454e-01 1.06789403e-01
-4.96283233e-01 -9.75042582e-01 -2.91817844e-01 -9.60753024e-01
3.46474111e-01 -1.49257198e-01 1.30939829e+00 6.15935586e-02
-1.09145164e-01 5.48849463e-01 -6.98254108e-01 -8.76527905e-01
-4.02892113e-01 4.74105418e-01 2.15910494e-01 2.49740612e-02
9.59238112e-01 -5.72385907e-01 5.01865335e-02 2.59939194e-01
-9.59440231e-01 -2.38602027e-01 4.05112028e-01 5.04493892e-01
1.38089865e-01 2.70292461e-01 6.36574447e-01 -1.34412980e+00
6.27386689e-01 -7.27338493e-01 -1.95399553e-01 6.86982155e-01
-3.03129405e-01 2.47313157e-01 2.86041737e-01 -3.05112630e-01
-1.25645030e+00 2.05656305e-01 -8.30810219e-02 1.67143598e-01
-4.92367566e-01 7.78414249e-01 -3.08546156e-01 2.68001705e-01
4.31116045e-01 -1.28414810e-01 -3.31878692e-01 -3.78615737e-01
6.47322118e-01 8.05751562e-01 7.53061712e-01 -7.83404589e-01
6.65707529e-01 5.10363340e-01 9.73173231e-02 -9.73957896e-01
-7.71001637e-01 -9.44254696e-01 -1.35612321e+00 -1.70616537e-01
9.87783909e-01 -5.94014585e-01 -7.79943705e-01 -3.58695574e-02
-1.60137844e+00 2.60324478e-01 -3.19395781e-01 4.83121127e-01
-3.89146626e-01 4.31266814e-01 -2.19577163e-01 -8.02226305e-01
-1.13539077e-01 -6.60838425e-01 1.03470004e+00 4.84078079e-01
-4.94403332e-01 -1.29341686e+00 2.65029669e-01 4.35049415e-01
7.09525570e-02 3.16643089e-01 1.06761515e+00 -1.43908715e+00
-9.06262770e-02 -9.99442786e-02 -1.09125696e-01 -2.35439003e-01
2.88659632e-01 4.20077406e-02 -7.28609443e-01 1.35848999e-01
-1.74988687e-01 3.41346532e-01 4.33497399e-01 -8.23327228e-02
2.30947286e-01 -2.37338051e-01 -9.04371023e-01 -9.88063887e-02
1.34727895e+00 4.45826203e-01 6.93319917e-01 5.97928464e-01
6.51628315e-01 1.40808487e+00 8.71176243e-01 1.92585856e-01
6.38510704e-01 8.17739546e-01 9.70597267e-02 1.50992855e-01
6.45607635e-02 1.80553813e-02 -6.75018877e-03 8.02245438e-01
-3.39720309e-01 -3.81050408e-01 -1.29570651e+00 8.19213271e-01
-2.34873605e+00 -1.29695296e+00 -4.94365335e-01 1.87405419e+00
7.75250912e-01 -1.66082785e-01 1.34279862e-01 -9.74764749e-02
1.06724393e+00 -3.85331631e-01 -1.44742712e-01 -2.97651440e-01
-2.77721971e-01 2.92296894e-02 4.72224653e-01 6.40336633e-01
-1.20167089e+00 1.31553686e+00 5.79814005e+00 6.24798536e-01
-8.01824987e-01 1.58938691e-01 -8.98360908e-02 4.37033474e-01
1.10162487e-02 2.25116462e-01 -1.21554339e+00 3.85256022e-01
9.82564509e-01 -4.33997959e-01 1.14180751e-01 3.85695815e-01
2.01586470e-01 -2.84578085e-01 -1.16088533e+00 7.73128092e-01
1.02019213e-01 -1.10569060e+00 3.97129916e-02 8.24733526e-02
5.19227028e-01 -2.08127484e-01 -6.16824687e-01 2.14427650e-01
4.00179863e-01 -8.22510242e-01 5.21619797e-01 7.51751304e-01
1.06966503e-01 -6.52252674e-01 1.19367325e+00 5.06998658e-01
-1.38532174e+00 -8.79740342e-03 -1.71857759e-01 1.58388838e-01
4.88896579e-01 4.27740008e-01 -8.05195391e-01 1.16544104e+00
6.04896963e-01 6.59807861e-01 -4.19582576e-01 8.29023838e-01
-2.25719109e-01 7.04504922e-02 -4.26924556e-01 -1.20500185e-01
2.16992661e-01 -2.91901201e-01 6.70197308e-01 1.48221040e+00
2.58947134e-01 5.52754343e-01 -6.02278486e-03 7.52429128e-01
-1.02286763e-01 2.95074999e-01 -9.02622461e-01 -5.95689826e-02
5.83895922e-01 1.31581926e+00 -8.70285273e-01 -6.42739713e-01
-3.55659127e-01 6.88918889e-01 2.28072181e-01 1.81856737e-01
-6.70464754e-01 -7.00222611e-01 5.06351709e-01 -3.10615338e-02
2.71244347e-01 -2.13167027e-01 7.24474937e-02 -1.08695400e+00
-9.21357423e-02 -5.56200385e-01 5.54164529e-01 -8.53860199e-01
-1.16962385e+00 6.31315708e-01 4.18314308e-01 -9.66098309e-01
-5.07065654e-01 -5.26523650e-01 -4.24097329e-01 7.08527029e-01
-1.39304388e+00 -1.18579638e+00 -2.58465875e-02 6.41838491e-01
3.61913472e-01 7.43698478e-02 6.62738383e-01 4.26502287e-01
-5.69274783e-01 1.92965567e-01 -4.16237004e-02 5.14608443e-01
8.72980058e-01 -1.19449580e+00 2.11132038e-03 7.98508167e-01
4.13784862e-01 8.61147761e-01 8.92523706e-01 -7.87737668e-01
-9.19741511e-01 -8.62037063e-01 1.73056018e+00 -7.41929889e-01
1.10077071e+00 5.67353405e-02 -9.15138423e-01 8.72224629e-01
5.32666206e-01 -3.57167691e-01 6.94398999e-01 2.71072388e-01
-8.75604153e-02 1.19816646e-01 -1.23880625e+00 3.69161099e-01
1.00019801e+00 -4.06349361e-01 -1.26148725e+00 3.63795429e-01
8.26484919e-01 -1.38338104e-01 -1.18624032e+00 3.73069614e-01
3.59498203e-01 -4.42798883e-01 8.02718997e-01 -8.65984678e-01
-6.61813319e-02 -5.87638557e-01 -9.10479296e-03 -1.09212804e+00
-5.13364151e-02 -3.72407317e-01 6.38646558e-02 1.80158556e+00
7.33610392e-01 -6.88945591e-01 5.47217965e-01 7.95879841e-01
7.35829547e-02 -5.89494333e-02 -8.82727623e-01 -6.76485658e-01
1.50874862e-02 -2.76573539e-01 5.53590298e-01 1.37458980e+00
5.28721213e-01 7.53241420e-01 -1.00944519e-01 2.68285066e-01
2.39622667e-01 1.32144332e-01 4.50319678e-01 -1.87018275e+00
2.05480054e-01 -3.46717656e-01 -6.03417099e-01 -5.57751596e-01
4.53122288e-01 -6.81766629e-01 3.61619927e-02 -1.72696662e+00
-1.04343018e-03 -3.95493180e-01 1.41899273e-01 6.14735067e-01
1.27595842e-01 -5.55042811e-02 4.03147370e-01 3.12351495e-01
-6.23756945e-01 -5.04220165e-02 6.86246216e-01 -1.50493205e-01
-2.95228630e-01 -1.42629996e-01 -4.65338528e-01 8.85116220e-01
7.21238196e-01 -6.29073262e-01 4.94028665e-02 -2.43884847e-01
5.16161680e-01 -1.43842608e-01 -1.32202860e-02 -5.90148211e-01
9.10160363e-01 -2.69776464e-01 -3.68167549e-01 -6.01132274e-01
2.13083282e-01 -1.22002053e+00 2.98534065e-01 3.08295310e-01
-9.43171978e-02 2.34004289e-01 2.19643086e-01 3.76950532e-01
-7.02368081e-01 -6.94996178e-01 2.27121651e-01 -3.83877963e-01
-1.11923552e+00 -1.37135819e-01 -3.45969081e-01 4.26422469e-02
1.26998162e+00 -1.32834554e-01 -3.97138834e-01 -1.52733058e-01
-1.15442836e+00 5.42756081e-01 2.76807576e-01 6.11446917e-01
-5.46626933e-02 -1.11043370e+00 -5.07708251e-01 -5.31239450e-01
7.03832880e-02 -1.65876374e-02 3.73198278e-02 9.10946846e-01
-3.75378460e-01 8.18665147e-01 -1.66378558e-01 -2.75110751e-01
-1.57825482e+00 8.19663107e-01 1.87125549e-01 -4.88603830e-01
-1.16985798e-01 3.24896038e-01 2.05153041e-03 -4.60575789e-01
1.89457715e-01 -6.81275800e-02 -1.09865320e+00 7.36760199e-01
3.78772289e-01 2.68432617e-01 -2.04289295e-02 -1.28290951e+00
-6.50401533e-01 9.65316772e-01 5.99742793e-02 -2.00496987e-01
1.42698681e+00 -4.75289345e-01 -6.57550454e-01 6.40510499e-01
8.41649234e-01 2.50030309e-01 -7.91527480e-02 -2.94690758e-01
7.94222951e-01 2.44360730e-01 -4.19883400e-01 -7.95087814e-01
-7.40423858e-01 6.18529797e-01 2.07736477e-01 6.96431041e-01
9.05059218e-01 4.41825747e-01 5.22604048e-01 7.12330878e-01
4.41435933e-01 -1.27855146e+00 -7.30179071e-01 7.72651076e-01
6.09702289e-01 -1.19270921e+00 1.66457612e-02 -8.37408125e-01
-7.19773233e-01 1.42071795e+00 4.01302159e-01 4.62798476e-01
7.70361960e-01 1.06793098e-01 -1.17065430e-01 -5.07229805e-01
-5.73092699e-01 -8.10010552e-01 1.75257832e-01 6.59788549e-01
5.00152230e-01 3.71040478e-02 -7.71886706e-01 6.40204906e-01
-3.26684058e-01 -1.17021792e-01 5.47567666e-01 9.61656094e-01
-5.49947202e-01 -1.54396915e+00 -4.20999199e-01 8.86015221e-02
-6.00473464e-01 -1.49305552e-01 -9.35188770e-01 1.18287051e+00
5.61073959e-01 1.03058028e+00 2.22116172e-01 -1.86096013e-01
4.89510775e-01 4.15251613e-01 1.25741288e-01 -8.03166986e-01
-7.29629040e-01 -4.76517856e-01 4.84360754e-01 -4.87177372e-02
-1.24984145e+00 -8.09604704e-01 -1.50914252e+00 -2.31515244e-01
-3.63891095e-01 6.42255068e-01 8.79062653e-01 1.34954095e+00
2.39515021e-01 3.11700225e-01 2.16492847e-01 -3.53368551e-01
2.39785105e-01 -8.05935144e-01 -4.18594897e-01 4.82855976e-01
-6.36434332e-02 -7.98043191e-01 -2.06089914e-01 1.26204029e-01] | [9.500386238098145, 9.101840019226074] |
a94fd564-4dbe-4637-b615-424556430ebf | generating-negative-samples-by-manipulating | null | null | https://aclanthology.org/2021.naacl-main.120 | https://aclanthology.org/2021.naacl-main.120.pdf | Generating Negative Samples by Manipulating Golden Responses for Unsupervised Learning of a Response Evaluation Model | Evaluating the quality of responses generated by open-domain conversation systems is a challenging task. This is partly because there can be multiple appropriate responses to a given dialogue history. Reference-based metrics that rely on comparisons to a set of known correct responses often fail to account for this variety, and consequently correlate poorly with human judgment. To address this problem, researchers have investigated the possibility of assessing response quality without using a set of known correct responses. RUBER demonstrated that an automatic response evaluation model could be made using unsupervised learning for the next-utterance prediction (NUP) task. For the unsupervised learning of such model, we propose a method of manipulating a golden response to create a new negative response that is designed to be inappropriate within the context while maintaining high similarity with the original golden response. We find, from our experiments on English datasets, that using the negative samples generated by our method alongside random negative samples can increase the model{'}s correlation with human evaluations. The process of generating such negative samples is automated and does not rely on human annotation. | ['Jong Park', 'Wonsuk Yang', 'Eugene Jang', 'ChaeHun Park'] | 2021-06-01 | null | null | null | naacl-2021-4 | ['dialogue-evaluation'] | ['natural-language-processing'] | [ 5.34540772e-01 4.34086412e-01 1.14352621e-01 -8.61599743e-01
-1.05971849e+00 -7.02788949e-01 6.44296229e-01 2.80848920e-01
-4.94168043e-01 9.04204607e-01 5.28924286e-01 -2.59115219e-01
-1.90686863e-02 -6.75496459e-01 -8.73706676e-03 -3.87726635e-01
6.52267814e-01 7.03422248e-01 2.43608251e-01 -4.60319668e-01
7.83528626e-01 1.15919700e-02 -1.48536968e+00 6.63879752e-01
8.95321012e-01 7.07298458e-01 7.64177963e-02 9.10923839e-01
-3.57474893e-01 1.08672369e+00 -1.17772114e+00 -3.61465961e-01
-1.67912561e-02 -9.36381280e-01 -1.27784681e+00 6.88229650e-02
8.98369327e-02 -3.95884365e-01 3.66493791e-01 8.62568617e-01
5.13540685e-01 3.89065206e-01 6.64053798e-01 -1.13678789e+00
-5.24736404e-01 6.49575472e-01 2.01993302e-01 -3.69473025e-02
1.09518397e+00 2.27192149e-01 1.10768545e+00 -7.13897824e-01
7.60433495e-01 1.27337325e+00 5.78092098e-01 9.75810468e-01
-1.40984213e+00 -2.39906624e-01 -2.84810424e-01 9.46742762e-03
-8.80527198e-01 -6.19065344e-01 5.74857771e-01 -5.31705320e-01
8.73529673e-01 6.75200522e-01 1.91960081e-01 1.16870511e+00
-5.62135987e-02 3.03823709e-01 1.35248864e+00 -6.41583264e-01
3.83693755e-01 6.52039707e-01 3.19254100e-01 1.72663093e-01
-2.40787417e-01 -8.86747688e-02 -4.32003677e-01 -3.92738879e-01
1.17159307e-01 -4.36238974e-01 -3.77636701e-01 8.70223716e-02
-8.65209758e-01 1.06771970e+00 -5.79978302e-02 4.43883806e-01
-4.11126316e-01 -5.68328857e-01 4.07807738e-01 6.61183119e-01
6.91951036e-01 1.06484389e+00 -6.35221243e-01 -5.40110826e-01
-6.88112259e-01 4.27995592e-01 1.53592646e+00 5.26637256e-01
8.98144245e-01 -3.34606081e-01 -3.61128688e-01 1.23651063e+00
2.06431091e-01 1.94552422e-01 7.49334693e-01 -1.11173713e+00
2.40587056e-01 9.70512927e-01 5.55803120e-01 -9.80394959e-01
-3.07114094e-01 3.16934884e-01 -2.93992877e-01 1.54131517e-01
9.25995767e-01 -3.52497190e-01 -3.10056895e-01 1.58173442e+00
4.72165138e-01 -7.71996498e-01 2.24972606e-01 9.37873304e-01
8.25051486e-01 5.03530622e-01 -8.76076892e-02 -5.54742336e-01
8.73464882e-01 -7.24358320e-01 -7.11358666e-01 -1.41875803e-01
9.78783607e-01 -9.27481174e-01 1.55446422e+00 4.95767236e-01
-8.09022605e-01 -3.86390567e-01 -8.14219534e-01 1.69756636e-01
-5.04046194e-02 -2.63377666e-01 2.04702750e-01 7.49372721e-01
-9.56355035e-01 5.92818797e-01 1.40015846e-02 -5.36597073e-01
-4.03452694e-01 3.20055634e-01 -3.95586938e-01 1.81429118e-01
-1.22866166e+00 1.23422527e+00 2.50320081e-02 -1.51988566e-01
-2.74686813e-01 -2.82141060e-01 -6.29933417e-01 -1.07547939e-01
3.11955780e-01 -3.32005203e-01 1.79447293e+00 -1.58766937e+00
-1.85154915e+00 8.02799821e-01 -2.09068716e-01 -1.90447852e-01
5.86122930e-01 -2.48788279e-02 -2.77507126e-01 7.18183294e-02
1.08045079e-01 2.70288795e-01 6.53676331e-01 -1.10580719e+00
-3.07557464e-01 -2.73185074e-01 1.48220658e-01 1.53272763e-01
-1.45142943e-01 2.92997032e-01 3.86643916e-01 -1.94675431e-01
-3.50889377e-02 -1.03865063e+00 -2.39050776e-01 -5.60677469e-01
-1.68043882e-01 -6.70721352e-01 2.27874726e-01 -5.37712634e-01
1.40393341e+00 -1.75988746e+00 -2.39142209e-01 2.53664017e-01
1.13218009e-01 4.25267667e-01 -1.21030636e-01 7.98077464e-01
2.81853061e-02 3.88362497e-01 -3.73708047e-02 6.61224350e-02
8.21174756e-02 3.28168720e-02 -1.36267349e-01 -6.64080828e-02
1.73366129e-01 3.53017569e-01 -1.06320894e+00 -4.64030176e-01
-1.23695157e-01 -7.98392966e-02 -7.12922871e-01 7.96579421e-01
-4.05124605e-01 4.89286870e-01 -4.33372378e-01 4.29376550e-02
1.96684062e-01 -1.93083346e-01 4.95623767e-01 2.43936300e-01
6.25352338e-02 8.85587275e-01 -9.50091004e-01 9.61506486e-01
-4.99473035e-01 5.26996076e-01 -7.72937685e-02 -6.51594818e-01
1.43273544e+00 5.07312477e-01 7.64091611e-02 -5.76334178e-01
1.28985882e-01 3.55909079e-01 4.52756196e-01 -8.39455545e-01
7.37358928e-01 -4.40970749e-01 -1.26633689e-01 1.03925908e+00
5.74744120e-02 -3.73933256e-01 1.54695526e-01 2.67513126e-01
1.35635972e+00 -5.01721688e-02 6.05478704e-01 -3.69259082e-02
7.18503773e-01 1.07807651e-01 5.52725255e-01 9.43561792e-01
-3.72911274e-01 4.50606853e-01 6.98343277e-01 -3.52626026e-01
-1.02665186e+00 -5.36240697e-01 1.63655862e-01 1.17276073e+00
-3.69455576e-01 -3.75710934e-01 -9.73197162e-01 -6.71350658e-01
-4.17277992e-01 1.03163576e+00 -4.16835696e-01 -1.64869651e-02
-2.84157038e-01 -3.79642576e-01 4.61651266e-01 8.08710754e-02
1.17664322e-01 -1.24782300e+00 -6.03951812e-01 4.76399034e-01
-7.09581256e-01 -7.91710138e-01 -2.67827392e-01 3.31498384e-02
-4.57914680e-01 -1.09780014e+00 -2.11404353e-01 -4.73248869e-01
4.81109321e-01 -1.00761624e-02 1.34297276e+00 4.69924539e-01
2.86881953e-01 4.33476716e-01 -8.59765828e-01 -2.23010927e-01
-1.33116293e+00 -1.59993395e-01 1.19029604e-01 5.80344489e-03
7.69483209e-01 -2.53852785e-01 -2.45627344e-01 6.90375149e-01
-7.50348568e-01 -5.71790710e-02 1.75055847e-01 1.05169749e+00
3.28780934e-02 -5.20235062e-01 1.13940406e+00 -1.25406551e+00
1.34661806e+00 -4.89664942e-01 -1.26825109e-01 3.80697459e-01
-8.62127066e-01 1.26865268e-01 7.79846847e-01 -6.03574574e-01
-1.25856078e+00 -2.21867174e-01 -3.51383179e-01 2.52168953e-01
-4.24399823e-01 4.08681363e-01 4.35968600e-02 2.06452645e-02
1.16991842e+00 -7.92966709e-02 3.14703345e-01 -2.48450100e-01
1.50242135e-01 1.23586106e+00 1.24773957e-01 -7.30084777e-01
1.39949545e-01 -1.72988668e-01 -6.39774621e-01 -7.90863752e-01
-8.89876962e-01 -5.19242227e-01 -4.20311362e-01 -5.85402131e-01
5.48884332e-01 -3.54497463e-01 -6.78280056e-01 1.61016002e-01
-1.31998825e+00 -5.57349205e-01 -5.07836007e-02 4.04285491e-01
-7.15240419e-01 4.82335269e-01 -6.27508521e-01 -1.28548920e+00
-3.11829180e-01 -1.00462246e+00 5.15810192e-01 1.84906512e-01
-1.29769611e+00 -8.64758611e-01 3.49038005e-01 6.30639672e-01
4.50887829e-01 -1.18196882e-01 9.14972544e-01 -1.56154716e+00
9.66497287e-02 -4.56578761e-01 2.68605918e-01 6.20017946e-01
1.30882531e-01 1.33026272e-01 -1.02089989e+00 1.27652377e-01
4.66622531e-01 -8.35598409e-01 1.52701542e-01 -2.09502593e-01
5.87882221e-01 -7.07332730e-01 2.71978110e-01 -3.22306097e-01
9.79167759e-01 3.19254220e-01 7.35391915e-01 1.69890076e-01
8.38664845e-02 1.26795042e+00 8.60580802e-01 4.81576711e-01
2.52481699e-01 6.48969889e-01 -2.79306211e-02 4.51042503e-01
4.28810447e-01 -2.66644955e-01 3.59430939e-01 7.15668738e-01
2.62846082e-01 -4.03318912e-01 -7.81593800e-01 4.47085261e-01
-1.62528527e+00 -1.05991507e+00 -3.81203383e-01 2.31024671e+00
1.10672808e+00 2.45758280e-01 2.23833948e-01 2.43352845e-01
6.51782334e-01 -1.08598955e-01 -8.52024928e-02 -1.01501918e+00
1.27817914e-01 2.05930188e-01 -4.43640389e-02 7.04362214e-01
-4.44935083e-01 5.94988883e-01 6.45792150e+00 3.65867138e-01
-8.98332357e-01 -6.26432896e-02 6.40795231e-01 1.96040943e-01
-5.87791681e-01 1.88947722e-01 -5.50497234e-01 4.33328569e-01
1.36201239e+00 -2.95297891e-01 3.33807141e-01 6.39016688e-01
5.88598669e-01 -4.32616115e-01 -1.34832847e+00 5.09383917e-01
1.30118176e-01 -8.41633797e-01 -1.37921751e-01 -1.61801994e-01
4.82840002e-01 -5.06022394e-01 -5.42272687e-01 4.87638831e-01
5.07678449e-01 -8.43862236e-01 3.01041692e-01 5.16947985e-01
2.68271774e-01 -5.34432590e-01 9.36181664e-01 8.09841931e-01
-2.35548139e-01 -5.80782024e-03 -1.81586817e-01 -5.27953863e-01
1.47475572e-02 2.68699855e-01 -1.52389598e+00 -2.64189932e-02
2.40716472e-01 -3.08640534e-03 -4.36275750e-01 6.19918764e-01
-2.95099318e-01 7.92881131e-01 -9.65696201e-02 -6.78410709e-01
1.03579722e-02 -1.90875351e-01 5.40103912e-01 1.06712151e+00
3.83138619e-02 3.21078867e-01 1.70738220e-01 8.04156601e-01
1.26242802e-01 5.54160297e-01 -7.49603212e-01 -2.20702589e-01
6.41239643e-01 1.13713706e+00 -4.25822049e-01 -4.55039948e-01
-2.01904327e-01 7.46819794e-01 3.73193175e-01 5.25738597e-02
-2.90827751e-01 -2.39145324e-01 2.17037395e-01 -6.70660241e-03
-2.59790152e-01 3.34104210e-01 -3.12820762e-01 -7.44380116e-01
9.63986665e-02 -1.39072490e+00 2.14560017e-01 -8.07416379e-01
-1.53820467e+00 7.14958727e-01 -2.11531356e-01 -1.24326158e+00
-8.88762295e-01 -3.11877280e-01 -6.18726254e-01 1.07828164e+00
-7.40400553e-01 -3.79594058e-01 -1.98124215e-01 2.91888624e-01
7.92794168e-01 7.39438534e-02 1.22332418e+00 2.89472304e-02
-2.42434472e-01 5.33326268e-01 -4.31859821e-01 1.92206781e-02
1.12711740e+00 -1.34283257e+00 -2.13611145e-02 5.45591295e-01
-1.95732355e-01 7.69485116e-01 1.13271940e+00 -5.60895860e-01
-8.52162004e-01 -4.81110990e-01 1.45202959e+00 -7.28890896e-01
6.73869193e-01 1.60569150e-03 -1.32908165e+00 2.77987152e-01
2.83261210e-01 -6.36368871e-01 1.19163120e+00 2.29970559e-01
-3.35143924e-01 2.52638638e-01 -1.28604448e+00 4.34973270e-01
5.35028279e-01 -6.16871357e-01 -9.72862780e-01 3.76687974e-01
5.25688589e-01 -1.70666561e-01 -8.41244161e-01 1.56826433e-02
5.32924116e-01 -1.24318779e+00 3.63781095e-01 -8.22886825e-01
6.40835226e-01 -4.00806926e-02 -1.46408379e-01 -1.52328467e+00
7.14801773e-02 -7.00824857e-01 4.40532327e-01 1.38266015e+00
5.88181078e-01 -5.66861212e-01 4.80490953e-01 1.31150031e+00
4.00075950e-02 -5.63204050e-01 -5.46503961e-01 -4.61688429e-01
4.19662567e-03 -3.25745791e-01 4.26526755e-01 9.16846275e-01
6.34114861e-01 7.59941578e-01 -4.38069284e-01 -3.31210941e-01
9.44095701e-02 -1.64458662e-01 1.26116943e+00 -1.26721370e+00
-3.22264105e-01 -2.50895023e-01 -2.27714226e-01 -9.95108306e-01
2.14992359e-01 -4.79596674e-01 5.46891868e-01 -1.27660799e+00
3.98768671e-02 -4.63843554e-01 2.22075135e-01 2.21641615e-01
-3.65585655e-01 -5.56532703e-02 9.55900028e-02 1.96430728e-01
-5.00566661e-01 2.00839594e-01 1.00000989e+00 1.37869239e-01
-4.10010219e-01 2.39514351e-01 -8.36683929e-01 7.03477204e-01
8.29576671e-01 -6.58322036e-01 -3.68010253e-01 6.64088726e-02
4.29600894e-01 5.32735050e-01 8.37756395e-02 -6.18719459e-01
1.20089144e-01 -3.47137392e-01 -9.00135487e-02 -1.31516039e-01
8.33015591e-02 -4.80938822e-01 -1.68757159e-02 1.19143173e-01
-1.02788997e+00 1.68843418e-01 -3.05732518e-01 4.86309022e-01
-2.18875512e-01 -8.10389340e-01 6.74776495e-01 -3.81829768e-01
-5.61992288e-01 -5.61756253e-01 -7.69250214e-01 1.43463209e-01
5.58208466e-01 -2.60664850e-01 -3.05556536e-01 -8.39940488e-01
-6.62827969e-01 1.36842147e-01 5.85428953e-01 4.68334407e-01
5.48484087e-01 -8.89921963e-01 -8.05171430e-01 -8.67885202e-02
2.74197727e-01 -4.36892509e-01 -2.10910458e-02 7.20970094e-01
-3.26604843e-01 2.10457116e-01 -1.03156986e-02 -4.03812110e-01
-1.37486410e+00 2.85138369e-01 3.85067046e-01 -3.51773709e-01
-2.12559670e-01 6.46873295e-01 -1.65703103e-01 -8.76189291e-01
3.93123366e-02 -4.44697514e-02 -4.87643063e-01 1.47571027e-01
7.74962246e-01 2.34952599e-01 2.20297307e-01 -5.56610465e-01
-1.13758586e-01 -3.03021044e-01 -5.09176664e-02 -5.02655149e-01
1.00614882e+00 -1.97639346e-01 -7.26944059e-02 8.98599684e-01
1.01426387e+00 2.58620679e-01 -6.84861720e-01 -1.61460653e-01
4.60675448e-01 -7.27645218e-01 -5.75980842e-01 -1.02066362e+00
-2.34774753e-01 5.60034275e-01 2.25918159e-01 7.03163266e-01
7.59522498e-01 -4.20079589e-01 4.10811663e-01 6.82476163e-01
4.00028020e-01 -1.43823779e+00 3.45762342e-01 5.89339912e-01
8.55058014e-01 -1.52326226e+00 -2.95041591e-01 -1.99163318e-01
-1.02994335e+00 1.25180137e+00 7.95794368e-01 1.04675300e-01
9.98864025e-02 -1.79791152e-01 6.18764460e-01 -4.98949662e-02
-1.23797894e+00 1.07103698e-01 -3.31459902e-02 5.52201092e-01
9.38947678e-01 2.04035714e-01 -9.01775181e-01 5.78882992e-01
-3.43330920e-01 -6.41536340e-02 1.09570634e+00 8.18940639e-01
-6.22695446e-01 -1.34734857e+00 -3.64413470e-01 7.25880563e-01
-4.07321870e-01 6.53151944e-02 -1.05110133e+00 3.38394374e-01
-3.66630226e-01 1.78427184e+00 -2.05435365e-01 -5.85262656e-01
3.55282485e-01 5.12222588e-01 2.19631687e-01 -1.01581514e+00
-1.05289042e+00 -1.87624454e-01 8.44611704e-01 -3.42704237e-01
-5.62375307e-01 -6.12543702e-01 -9.19753611e-01 -3.00146252e-01
-5.76618731e-01 6.86102092e-01 4.15742189e-01 1.26588011e+00
-1.50933890e-02 3.73249091e-02 1.02860999e+00 -5.21131516e-01
-1.23090589e+00 -1.25782752e+00 -3.03544104e-01 8.91444027e-01
2.06201598e-01 -4.17669505e-01 -6.58526659e-01 -9.03761089e-02] | [12.7877197265625, 8.052569389343262] |
ae5a68e7-4bf7-4def-82ee-e75537888cac | dad-data-free-adversarial-defense-at-test | 2204.01568 | null | https://arxiv.org/abs/2204.01568v2 | https://arxiv.org/pdf/2204.01568v2.pdf | DAD: Data-free Adversarial Defense at Test Time | Deep models are highly susceptible to adversarial attacks. Such attacks are carefully crafted imperceptible noises that can fool the network and can cause severe consequences when deployed. To encounter them, the model requires training data for adversarial training or explicit regularization-based techniques. However, privacy has become an important concern, restricting access to only trained models but not the training data (e.g. biometric data). Also, data curation is expensive and companies may have proprietary rights over it. To handle such situations, we propose a completely novel problem of 'test-time adversarial defense in absence of training data and even their statistics'. We solve it in two stages: a) detection and b) correction of adversarial samples. Our adversarial sample detection framework is initially trained on arbitrary data and is subsequently adapted to the unlabelled test data through unsupervised domain adaptation. We further correct the predictions on detected adversarial samples by transforming them in Fourier domain and obtaining their low frequency component at our proposed suitable radius for model prediction. We demonstrate the efficacy of our proposed technique via extensive experiments against several adversarial attacks and for different model architectures and datasets. For a non-robust Resnet-18 model pre-trained on CIFAR-10, our detection method correctly identifies 91.42% adversaries. Also, we significantly improve the adversarial accuracy from 0% to 37.37% with a minimal drop of 0.02% in clean accuracy on state-of-the-art 'Auto Attack' without having to retrain the model. | ['Anirban Chakraborty', 'Ruchit Rawal', 'Gaurav Kumar Nayak'] | 2022-04-04 | null | null | null | null | ['adversarial-defense'] | ['adversarial'] | [ 5.05072057e-01 1.13858588e-01 3.22275937e-01 -2.43858635e-01
-9.30621803e-01 -1.15734160e+00 4.67430890e-01 -3.86551931e-03
-5.91228545e-01 7.84382284e-01 -3.75382900e-01 -3.48458022e-01
1.28598630e-01 -8.69568050e-01 -1.02972257e+00 -8.73074055e-01
-1.29948765e-01 3.05921078e-01 2.28101283e-01 -1.62006915e-01
5.69170201e-03 8.12540829e-01 -8.51252556e-01 1.53723478e-01
8.62291217e-01 1.19363046e+00 -3.91239494e-01 8.15627456e-01
3.00530672e-01 6.21970832e-01 -1.09814954e+00 -8.13602149e-01
7.49542892e-01 -1.05084516e-01 -4.54111725e-01 -3.70704114e-01
4.54178303e-01 -2.57009447e-01 -5.59426010e-01 1.66338563e+00
5.28220713e-01 -2.90518366e-02 6.08258665e-01 -1.22785318e+00
-8.13902020e-01 3.06847662e-01 -4.73326266e-01 1.12354778e-01
-3.51293795e-02 2.79583216e-01 3.07908803e-01 -6.11646235e-01
3.65966439e-01 9.69358027e-01 7.91090071e-01 1.04934311e+00
-1.35558021e+00 -1.30299592e+00 -1.86388806e-01 -1.08051300e-01
-1.47373068e+00 -5.53823352e-01 8.81188393e-01 -3.78001869e-01
4.50549871e-01 5.66208005e-01 -2.89796963e-02 1.58423436e+00
2.92291492e-01 1.11897223e-01 1.12290275e+00 -1.86194107e-01
3.38020742e-01 5.85252225e-01 -9.89358351e-02 3.82203996e-01
2.79192358e-01 4.62274164e-01 3.11675072e-02 -4.63788748e-01
6.06375873e-01 -9.69543010e-02 -2.48523146e-01 2.92091025e-03
-5.16716182e-01 8.20989668e-01 5.17275214e-01 5.49221039e-02
-3.97125781e-01 8.66848156e-02 4.07188088e-01 4.38200444e-01
4.41606849e-01 4.29878920e-01 -6.57665551e-01 4.68303204e-01
-6.54976606e-01 1.09609529e-01 8.01221609e-01 8.10989261e-01
3.33209068e-01 4.68841791e-01 1.93696126e-01 7.95768738e-01
2.10326508e-01 8.32307458e-01 4.10587639e-01 -3.31830829e-01
5.67097306e-01 5.98942116e-02 8.31446797e-02 -1.22959387e+00
-4.00270298e-02 -6.63617969e-01 -1.21140313e+00 4.08364594e-01
5.00913560e-01 -5.80389142e-01 -1.12535989e+00 1.71114445e+00
3.94903511e-01 4.73733813e-01 2.93696910e-01 6.85478330e-01
4.42028880e-01 4.51693803e-01 2.77856231e-01 -1.10561863e-01
1.04449451e+00 -4.29174274e-01 -4.45824802e-01 -2.24680975e-01
2.69635081e-01 -8.69222581e-01 7.50094473e-01 6.15383267e-01
-7.12513030e-01 -4.34363425e-01 -1.24721909e+00 4.52271491e-01
-5.91822982e-01 -1.20388351e-01 2.87756830e-01 1.24420726e+00
-5.61154783e-01 7.94988275e-01 -5.03757775e-01 1.60302013e-01
7.60903060e-01 7.26466358e-01 -6.98583543e-01 1.11766130e-01
-1.45180094e+00 7.15195119e-01 2.31994286e-01 1.07384779e-01
-1.19848239e+00 -7.69916117e-01 -5.43446958e-01 -1.45949662e-01
1.36820227e-01 -2.85544127e-01 8.70319486e-01 -1.26889980e+00
-1.27407038e+00 8.76165152e-01 3.53139192e-01 -1.02607238e+00
9.07835960e-01 -3.87921065e-01 -1.08177459e+00 3.84354778e-02
-2.83154666e-01 6.70267716e-02 1.39547038e+00 -1.21878362e+00
-3.62250298e-01 -2.90495634e-01 -4.42995951e-02 -3.66539955e-01
-6.34506643e-01 2.46087193e-01 5.00833206e-02 -1.10029054e+00
-2.14069366e-01 -1.04902828e+00 -3.12856913e-01 -9.75776166e-02
-5.89235246e-01 4.11940932e-01 1.09097421e+00 -8.15347791e-01
1.02256751e+00 -2.36814094e+00 -4.11394954e-01 5.97409844e-01
1.82833433e-01 8.95388067e-01 -2.52538826e-03 3.27452160e-02
-5.36365509e-01 4.44974661e-01 -3.98672998e-01 -1.80701599e-01
1.69997700e-02 -9.83195752e-03 -7.19696701e-01 8.30156863e-01
2.75563896e-01 4.06395406e-01 -5.52310228e-01 -9.92316455e-02
1.93938136e-01 6.54259503e-01 -6.18120551e-01 3.43119800e-01
3.90047766e-02 5.62440813e-01 -5.04590690e-01 5.54025531e-01
1.14702034e+00 2.93526322e-01 -1.12474822e-01 -1.45808682e-01
4.63103235e-01 -1.54339969e-01 -1.24598920e+00 9.36676800e-01
-4.47953254e-01 5.35665870e-01 2.92444438e-01 -1.13842559e+00
1.03331089e+00 4.11128223e-01 2.66537458e-01 -3.37163538e-01
3.37422431e-01 2.18294248e-01 7.31858239e-02 -3.46963942e-01
-1.39747811e-02 -1.28036916e-01 -2.59246349e-01 1.47952870e-01
8.20582360e-02 3.54841620e-01 -6.25576317e-01 5.02312481e-02
1.26459265e+00 -3.53692889e-01 2.45238673e-02 -2.44293943e-01
8.04991901e-01 -2.27293938e-01 6.23976290e-01 8.83814514e-01
-2.66350627e-01 4.58293676e-01 2.23146886e-01 -4.00206506e-01
-9.88686204e-01 -1.17378700e+00 -2.93646395e-01 7.69699275e-01
-3.97011749e-02 1.23221129e-01 -9.60164666e-01 -1.17120349e+00
1.14484638e-01 6.80609703e-01 -6.94588602e-01 -5.28386950e-01
-6.45859122e-01 -7.66385496e-01 1.05787969e+00 3.40633780e-01
6.96735203e-01 -8.99027705e-01 1.30796535e-02 1.40216872e-01
3.16424340e-01 -1.12599945e+00 -5.02658546e-01 2.94977993e-01
-5.53344309e-01 -1.10663319e+00 -3.55289131e-01 -6.18518412e-01
9.37203050e-01 -1.85749695e-01 7.51232564e-01 7.78675899e-02
-2.90821254e-01 1.48481980e-01 -3.10789406e-01 -8.09622645e-01
-9.06131446e-01 -1.60516202e-01 5.20531476e-01 4.04508173e-01
2.47533575e-01 -6.72913194e-01 -5.55942178e-01 3.13786566e-01
-1.01917315e+00 -7.45225191e-01 4.10557777e-01 9.10406053e-01
3.73438895e-01 3.95212561e-01 7.76310146e-01 -1.43153083e+00
6.72885358e-01 -5.35206139e-01 -7.68322170e-01 1.43001139e-01
-4.22857493e-01 -8.52713883e-02 1.38918424e+00 -9.42282081e-01
-7.96562135e-01 1.82064921e-01 -3.54919136e-01 -8.23205590e-01
-4.15987760e-01 -2.89689451e-02 -4.31430668e-01 -7.77117193e-01
1.22215736e+00 1.24434531e-01 -2.29143605e-01 -3.45135748e-01
3.61140119e-03 7.07901657e-01 8.09041739e-01 -4.90423143e-01
1.72004068e+00 2.66169488e-01 1.37905344e-01 -7.44457603e-01
-4.21425462e-01 5.40744476e-02 -3.66305619e-01 -1.54627515e-02
5.98695993e-01 -8.03053617e-01 -8.10922861e-01 6.67579055e-01
-9.67396677e-01 2.00858549e-03 -8.61688480e-02 2.95471132e-01
-3.32870744e-02 4.06701922e-01 -4.78411615e-01 -8.73518109e-01
-6.04112625e-01 -9.88708198e-01 4.30319607e-01 3.71776856e-02
6.24092110e-02 -1.10404813e+00 -2.24508092e-01 2.06614122e-01
6.23113751e-01 8.14217150e-01 5.36910832e-01 -1.33495057e+00
-2.75712162e-01 -9.85820472e-01 -5.68822434e-04 9.17398870e-01
5.06229922e-02 -1.15671791e-01 -1.43840134e+00 -5.13266265e-01
4.32684571e-01 -2.31778458e-01 4.99638885e-01 3.86326760e-02
1.47055984e+00 -8.23199630e-01 -1.36906773e-01 8.82428706e-01
1.48605824e+00 3.05551738e-01 5.95766604e-01 2.02258319e-01
7.75819063e-01 3.38145733e-01 4.95117486e-01 3.20160508e-01
-5.27983844e-01 4.24681544e-01 7.40452647e-01 -7.69910067e-02
3.80452096e-01 -1.82888359e-01 3.97378892e-01 2.39561468e-01
1.36938198e-02 -2.38227680e-01 -7.24680066e-01 2.01713637e-01
-1.35310793e+00 -9.59690273e-01 -6.86988309e-02 2.38827229e+00
8.05171251e-01 4.18335706e-01 -4.56272103e-02 3.15635055e-01
8.54458451e-01 -1.95882153e-02 -6.36397064e-01 -5.06306112e-01
6.68262914e-02 7.19534874e-01 1.09473670e+00 4.73211616e-01
-1.64169991e+00 1.06752110e+00 5.42312717e+00 9.33506131e-01
-1.30941284e+00 1.54995516e-01 6.53480291e-01 -1.95736177e-02
2.14645322e-02 -3.17465156e-01 -5.99990249e-01 5.78505516e-01
1.20767403e+00 -7.60403499e-02 5.59902072e-01 1.07265472e+00
-2.49063335e-02 4.79800016e-01 -8.13934028e-01 8.21564376e-01
-1.00929886e-01 -1.16498804e+00 -1.40770629e-01 1.43606022e-01
4.47080463e-01 -2.61674345e-01 3.43497753e-01 3.06001961e-01
5.31362057e-01 -1.27263820e+00 4.93529975e-01 3.76759589e-01
9.06921804e-01 -1.21214604e+00 6.71915412e-01 4.59762484e-01
-8.43760550e-01 -1.07087672e-01 -6.04035079e-01 3.66107792e-01
-3.18354130e-01 4.76238579e-01 -9.09461558e-01 3.31398517e-01
5.83276868e-01 1.58872440e-01 -4.09299731e-01 6.37857378e-01
-1.22193016e-01 8.69633973e-01 -3.94667149e-01 2.13820234e-01
-6.61773887e-03 9.81718525e-02 6.52253211e-01 1.08063209e+00
1.83762804e-01 7.21914619e-02 -4.18105535e-02 6.27263606e-01
-3.71834427e-01 -1.15794376e-01 -7.98739970e-01 8.58621448e-02
7.18577087e-01 1.13192618e+00 -3.01938385e-01 -8.26667249e-02
5.34515381e-02 1.13368642e+00 8.50547552e-02 4.00508136e-01
-1.16043961e+00 -5.44176400e-01 8.42026353e-01 5.26260100e-02
3.20595317e-02 9.99730378e-02 -1.65614665e-01 -1.07697058e+00
2.81599704e-02 -1.13381112e+00 2.68303752e-01 -7.76078552e-02
-1.58426344e+00 9.56558049e-01 -4.46239024e-01 -1.41858709e+00
-2.00807229e-01 -6.66329622e-01 -5.59682906e-01 1.10576689e+00
-1.07687187e+00 -1.08019423e+00 -9.92146786e-03 1.07442200e+00
1.47198111e-01 -6.67640388e-01 1.18964589e+00 4.85094130e-01
-6.24542117e-01 1.30650079e+00 2.83819348e-01 6.26998782e-01
7.74233401e-01 -1.11601424e+00 6.63871169e-01 1.22874820e+00
6.13967218e-02 5.85607767e-01 8.49485338e-01 -6.39705837e-01
-1.21389282e+00 -1.54291177e+00 3.57766330e-01 -5.18668532e-01
7.59492934e-01 -6.81715429e-01 -1.07862115e+00 7.03659534e-01
-2.30635956e-01 5.40746272e-01 7.84242213e-01 -3.43006909e-01
-4.93043274e-01 -3.12385947e-01 -1.90756440e+00 4.64573056e-01
7.04469681e-01 -6.56036735e-01 -2.70118654e-01 5.35809994e-01
6.72517955e-01 -4.87103730e-01 -9.89022851e-01 3.90049756e-01
4.40780342e-01 -7.63742864e-01 1.30904460e+00 -8.11548948e-01
-1.88884884e-02 -1.19476952e-01 -2.33412236e-01 -1.11494267e+00
-1.22157417e-01 -9.26353455e-01 -8.57016891e-02 1.43531334e+00
3.84715706e-01 -9.27942336e-01 9.17572916e-01 8.51718247e-01
1.19447194e-01 -4.85512555e-01 -9.11461532e-01 -7.08398342e-01
2.60977566e-01 -6.32949173e-01 5.52990496e-01 1.28098333e+00
-5.97686887e-01 -3.00501704e-01 -7.07134664e-01 9.31828737e-01
9.21400309e-01 -5.87132156e-01 8.70221853e-01 -1.09542143e+00
-3.64031643e-01 3.16555351e-02 -5.08367777e-01 -3.62647384e-01
2.19734043e-01 -7.18745768e-01 -1.37840658e-01 -4.22014326e-01
-5.01937091e-01 -6.65183902e-01 -4.16899651e-01 3.86528283e-01
-6.47224188e-02 5.18493831e-01 1.06562905e-01 2.75524892e-02
5.31170666e-02 6.59926981e-02 7.77726769e-01 -1.40529558e-01
2.61083785e-02 4.17075515e-01 -6.75604820e-01 8.09057176e-01
1.10659707e+00 -9.28117633e-01 -3.97743702e-01 -1.66315109e-01
-2.33457565e-01 -1.08869672e-01 6.37608945e-01 -1.36002862e+00
1.59018442e-01 -9.26406458e-02 7.53610730e-01 4.34243716e-02
1.85930625e-01 -1.30922508e+00 4.48859781e-01 4.38727051e-01
-3.17473203e-01 -1.86207369e-01 3.73698711e-01 7.63976216e-01
7.19149038e-02 -2.41219223e-01 1.29087985e+00 1.25112295e-01
-1.49054363e-01 4.21008438e-01 -5.04376041e-03 -1.77634433e-02
1.26763904e+00 -2.40897983e-02 -3.73598635e-01 -1.83084801e-01
-9.93529677e-01 -1.65028349e-01 2.85455376e-01 2.42987320e-01
6.36311233e-01 -1.14856648e+00 -6.23953819e-01 7.07331657e-01
-3.07179391e-01 -1.75787896e-01 2.89400339e-01 2.61938334e-01
-5.06954789e-01 6.34818226e-02 -1.38160169e-01 -1.43246487e-01
-1.40672815e+00 8.98771703e-01 4.56304848e-01 -2.06783935e-01
-4.37500924e-01 9.33995783e-01 1.18591860e-01 -2.94919521e-01
3.56192946e-01 7.84660131e-02 -6.46927431e-02 -3.51321340e-01
4.50310141e-01 1.00733869e-01 8.31746906e-02 -7.09126174e-01
-4.75661635e-01 2.81522006e-01 -2.99488962e-01 9.57909524e-02
1.14876759e+00 4.36520159e-01 1.97353870e-01 -2.75162935e-01
1.35496533e+00 3.73634338e-01 -1.11811423e+00 -8.34948048e-02
-3.36814553e-01 -5.77837825e-01 -1.55110583e-01 -8.07109714e-01
-1.32475364e+00 8.25927734e-01 9.01651263e-01 5.34780622e-01
1.29909217e+00 -5.34045577e-01 8.60381961e-01 1.72040641e-01
2.28766546e-01 -8.15780520e-01 -1.56451970e-01 2.85050124e-01
8.63688946e-01 -1.17752719e+00 -1.59527436e-01 -3.43160689e-01
-5.80304503e-01 9.00189936e-01 4.51448113e-01 -6.62852526e-01
9.66644704e-01 2.89600939e-01 2.43606567e-01 2.28690833e-01
-3.89208138e-01 5.32000124e-01 3.63877505e-01 8.83893907e-01
-6.35671467e-02 5.72149493e-02 8.55861530e-02 9.82803166e-01
-4.69789743e-01 -4.52551633e-01 3.18991154e-01 6.42770886e-01
-8.76763314e-02 -1.10423064e+00 -7.17677593e-01 4.76523668e-01
-1.14749181e+00 -7.82757401e-02 -4.05862272e-01 7.58472562e-01
2.30108157e-01 9.44172502e-01 -3.21612924e-01 -7.83882558e-01
4.63588327e-01 1.39265759e-02 5.29358946e-02 -3.73114794e-01
-1.00308776e+00 -1.09051764e-01 -4.25511189e-02 -3.78462523e-01
3.24600562e-02 -4.92183536e-01 -8.73858511e-01 -5.83922744e-01
-3.12677860e-01 1.07819475e-01 6.50133193e-01 7.71300495e-01
2.89945215e-01 5.20291567e-01 1.17108941e+00 -5.50114632e-01
-1.05410278e+00 -8.30452621e-01 -5.93875110e-01 6.21190965e-01
5.10106921e-01 -3.77744198e-01 -7.05842137e-01 4.68823947e-02] | [5.600977420806885, 7.830865859985352] |
5ab8fcac-7db3-44be-9f03-7114610a28bb | situational-grounding-within-multimodal | 1902.01886 | null | http://arxiv.org/abs/1902.01886v1 | http://arxiv.org/pdf/1902.01886v1.pdf | Situational Grounding within Multimodal Simulations | In this paper, we argue that simulation platforms enable a novel type of
embodied spatial reasoning, one facilitated by a formal model of object and
event semantics that renders the continuous quantitative search space of an
open-world, real-time environment tractable. We provide examples for how a
semantically-informed AI system can exploit the precise, numerical information
provided by a game engine to perform qualitative reasoning about objects and
events, facilitate learning novel concepts from data, and communicate with a
human to improve its models and demonstrate its understanding. We argue that
simulation environments, and game engines in particular, bring together many
different notions of "simulation" and many different technologies to provide a
highly-effective platform for developing both AI systems and tools to
experiment in both machine and human intelligence. | ['Nikhil Krishnaswamy', 'James Pustejovsky'] | 2019-02-05 | null | null | null | null | ['novel-concepts'] | ['reasoning'] | [-3.84893030e-01 1.88616648e-01 2.99338609e-01 -1.53379902e-01
-2.65042782e-01 -9.44228530e-01 8.67630899e-01 3.03266346e-01
-5.61224401e-01 6.55380130e-01 8.69832188e-02 -6.28645301e-01
-2.95501202e-01 -1.34866309e+00 -4.83674973e-01 -2.40829796e-01
-5.65041065e-01 6.24015629e-01 2.83564270e-01 -7.18827426e-01
3.00855935e-01 6.36102617e-01 -2.04962730e+00 -6.87116608e-02
8.63334894e-01 6.71394527e-01 4.03310031e-01 7.58300364e-01
-1.70409549e-02 1.40902030e+00 -5.47156334e-01 -1.23572275e-02
1.37885392e-01 -2.17139035e-01 -8.00444067e-01 -7.43929923e-01
-5.80757201e-01 -3.25789541e-01 -4.22765762e-01 9.75451529e-01
1.63141474e-01 6.06710136e-01 3.69976610e-01 -1.51588249e+00
-5.66985250e-01 5.39784610e-01 3.08384210e-01 1.68561801e-01
9.85777378e-01 7.07090080e-01 4.22443509e-01 -2.49491915e-01
9.57703650e-01 1.18017876e+00 5.26675642e-01 5.52789986e-01
-9.39810872e-01 -5.37885785e-01 -4.07888517e-02 2.76804507e-01
-1.42009807e+00 -2.04437375e-01 6.48020566e-01 -3.25384438e-01
1.14615023e+00 5.38594961e-01 1.46797144e+00 6.84826374e-01
1.30122811e-01 5.94802439e-01 1.12756634e+00 -5.06533325e-01
9.53171909e-01 1.66795790e-01 -2.62654394e-01 8.10169637e-01
6.69984054e-03 9.21622753e-01 -8.21606696e-01 -2.41976976e-02
1.15145099e+00 -2.22736284e-01 4.96268384e-02 -6.59245789e-01
-1.43437088e+00 6.11642897e-01 6.18130684e-01 4.64636296e-01
-6.26011312e-01 6.83455110e-01 1.52116567e-01 2.23776102e-01
-1.58137113e-01 1.22282553e+00 -3.72474223e-01 -8.12366426e-01
-5.38571656e-01 8.64572406e-01 9.54228461e-01 7.75490880e-01
5.82421720e-01 1.43024161e-01 2.75320947e-01 -1.76660299e-01
6.82098091e-01 4.10754293e-01 4.45430130e-01 -1.45472181e+00
-1.54837191e-01 6.17472887e-01 4.09208745e-01 -1.00016189e+00
-4.73532259e-01 -2.48859435e-01 3.87422629e-02 8.92636716e-01
4.10438329e-01 -1.72780007e-01 -5.29989600e-01 1.90032315e+00
5.05298018e-01 3.15075815e-01 2.99940914e-01 1.10254455e+00
5.63047469e-01 6.59262657e-01 6.03644371e-01 3.41199398e-01
1.29596174e+00 -2.76726335e-01 -3.94257814e-01 -3.21269661e-01
9.88555014e-01 2.97987819e-01 1.29582202e+00 2.87559509e-01
-1.56937838e+00 -1.69985384e-01 -1.21776319e+00 -1.49023578e-01
-1.08141518e+00 -1.00283194e+00 1.38967800e+00 5.01307547e-01
-1.32427025e+00 6.05967760e-01 -1.02978325e+00 -3.80442291e-01
5.50654888e-01 2.53537178e-01 -6.13912493e-02 2.65376627e-01
-1.50254750e+00 1.34884608e+00 7.27006018e-01 -3.18220466e-01
-9.69500601e-01 -9.35520411e-01 -1.04260862e+00 2.05773607e-01
2.21279606e-01 -9.33865190e-01 1.57263792e+00 -6.58213556e-01
-1.33830214e+00 8.90967250e-01 4.91920531e-01 -5.69414675e-01
4.36220497e-01 3.33973110e-01 -3.24873626e-01 2.06651419e-01
-1.19568631e-02 8.17700088e-01 -1.90077111e-01 -1.07068050e+00
-4.88883317e-01 -6.06007457e-01 4.60787147e-01 5.76737285e-01
3.12843531e-01 2.33104482e-01 1.79615781e-01 -3.30449611e-01
-2.88527850e-02 -3.56197774e-01 -5.69999337e-01 3.34773988e-01
5.55482686e-01 6.54669106e-02 4.64376181e-01 -2.88999289e-01
7.30337143e-01 -1.86698818e+00 -2.32278109e-02 2.98527002e-01
4.17837411e-01 -7.22563043e-02 1.88967541e-01 6.42674327e-01
2.86416411e-01 2.73184091e-01 3.10565829e-01 4.02965635e-01
6.41602993e-01 1.23847745e-01 -2.48662740e-01 1.49823967e-02
-1.27395838e-01 1.41250730e+00 -1.51758778e+00 -5.03845394e-01
6.81598186e-01 3.21788371e-01 -4.78938162e-01 2.01114699e-01
-5.14459252e-01 4.84229982e-01 -7.88356066e-01 4.36001360e-01
1.94419563e-01 -2.50527650e-01 2.18060151e-01 5.47784030e-01
-3.65533590e-01 3.25123906e-01 -1.23664129e+00 2.03989792e+00
-6.28490031e-01 6.40625715e-01 -8.30470473e-02 -4.74090636e-01
5.34311473e-01 4.03589368e-01 9.59427580e-02 -1.20771563e+00
3.86618674e-01 1.62338410e-02 -3.27069946e-02 -4.88637865e-01
4.94146168e-01 -4.70282346e-01 -3.89159411e-01 7.40070999e-01
-1.36611285e-02 -9.69735444e-01 1.73352826e-02 2.41387829e-01
1.19400656e+00 3.63835722e-01 4.16925341e-01 -5.33117056e-01
-2.87792981e-02 6.30181909e-01 1.33316308e-01 9.59649503e-01
-4.18873608e-01 -1.34288445e-01 1.29699437e-02 -5.92504621e-01
-1.00805199e+00 -1.52626801e+00 2.16097742e-01 1.15377200e+00
4.63542104e-01 -3.60614806e-01 -8.53946328e-01 1.30192861e-01
-1.25118285e-01 1.20940006e+00 -4.77776498e-01 -4.07958567e-01
-2.61567950e-01 3.18489480e-03 6.96150064e-01 8.81702363e-01
5.25915384e-01 -1.45987797e+00 -1.63549137e+00 2.79871106e-01
1.12651423e-01 -6.44786656e-01 3.60934138e-01 3.43280107e-01
-7.67184556e-01 -7.12237656e-01 8.39795768e-02 -6.71217263e-01
1.76406607e-01 -9.58810896e-02 1.30060494e+00 3.03483069e-01
-3.08352530e-01 6.15451813e-01 -2.05850661e-01 -8.30018938e-01
-4.07056093e-01 -5.01676261e-01 -6.13118969e-02 -1.14528501e+00
4.52937543e-01 -8.62466872e-01 -3.93285960e-01 -2.44458709e-02
-9.01819587e-01 5.08405447e-01 -3.94532345e-02 3.72897476e-01
9.57366899e-02 2.71076292e-01 5.64063966e-01 -2.11020082e-01
8.35142851e-01 -5.29367507e-01 -7.82538950e-01 3.13343465e-01
-5.18842578e-01 2.30455965e-01 4.61024344e-01 -4.58726078e-01
-1.23030972e+00 -4.19171780e-01 3.08277756e-01 1.17070809e-01
-3.18864137e-01 9.07949269e-01 -4.42762017e-01 -2.85861343e-01
1.00876272e+00 1.46788388e-01 -8.08357447e-02 7.77296796e-02
8.48756611e-01 2.65601188e-01 8.95794213e-01 -1.09888446e+00
7.49526143e-01 3.97563159e-01 -1.19963162e-01 -2.10917890e-01
3.99686433e-02 4.14249860e-02 -3.18669200e-01 -3.91588956e-01
7.81922758e-01 -7.85730898e-01 -1.36129797e+00 3.15343499e-01
-7.87707806e-01 -1.01676047e+00 -1.03835142e+00 6.00712538e-01
-1.16158760e+00 -4.60639864e-01 -2.74763376e-01 -9.76658523e-01
2.54254967e-01 -8.35486710e-01 7.56986320e-01 6.09512746e-01
-7.08460331e-01 -1.16408873e+00 2.71655649e-01 -9.69256610e-02
5.51882148e-01 3.08082134e-01 8.77311885e-01 -6.40248954e-01
-9.04198825e-01 -1.08163022e-01 -4.19340841e-02 -6.47125423e-01
-4.77165669e-01 -1.42612725e-01 -9.07070041e-01 2.95802593e-01
5.87200411e-02 -5.26081502e-01 -1.88521832e-01 1.92008093e-02
9.37321365e-01 -1.13570005e-01 -3.91732514e-01 5.08553624e-01
1.38237846e+00 7.56346464e-01 8.09300482e-01 7.47775257e-01
-1.33971646e-02 5.03660262e-01 7.31178522e-01 5.63892186e-01
7.76362956e-01 4.13557112e-01 2.92560577e-01 1.40970603e-01
3.42209786e-01 -6.31826282e-01 -4.71230820e-02 1.68169469e-01
-1.98604271e-01 -1.29274160e-01 -1.43786311e+00 5.56133151e-01
-2.00475526e+00 -1.20249915e+00 4.34334248e-01 1.80078208e+00
9.91324127e-01 3.35617103e-02 -1.80081408e-02 2.22829804e-02
2.85948336e-01 -3.89557108e-02 -4.96164680e-01 -5.58928430e-01
1.28690228e-01 6.29268467e-01 1.51654273e-01 3.77658218e-01
-4.96619225e-01 1.23635876e+00 7.68461704e+00 5.85938931e-01
-7.29978561e-01 -5.64764105e-02 1.37748972e-01 -9.63979885e-02
-6.86156571e-01 -2.91994289e-02 2.42130160e-01 1.85334802e-01
1.37680054e+00 -7.82639802e-01 9.27014291e-01 7.74304926e-01
2.95993060e-01 -4.73421454e-01 -1.31684864e+00 8.44985127e-01
-5.01279891e-01 -1.90632641e+00 -1.52837664e-01 2.76227500e-02
4.09753203e-01 -1.87599748e-01 5.43074273e-02 4.00229454e-01
1.22460270e+00 -1.52390885e+00 1.23774374e+00 8.31641614e-01
4.39822882e-01 -7.97947586e-01 2.64281988e-01 7.21656621e-01
-1.08004034e+00 -1.16202816e-01 3.06318521e-01 -9.23225880e-01
-6.37302324e-02 -2.55940080e-01 -6.11877739e-01 1.04229592e-01
5.88485181e-01 2.82086972e-02 -3.82613271e-01 1.12760508e+00
-2.80105826e-02 -6.64411262e-02 -4.41198587e-01 -6.90541685e-01
1.70113236e-01 -2.70740818e-02 4.26538020e-01 5.76865792e-01
2.45175570e-01 8.12791109e-01 -2.65486658e-01 1.59708107e+00
3.71719122e-01 -4.11939770e-01 -9.54679906e-01 -2.30029523e-01
9.28092718e-01 7.36425817e-01 -9.16093528e-01 -2.95883030e-01
4.80210371e-02 2.97838509e-01 1.27110764e-01 4.29791242e-01
-8.80897760e-01 -2.98260510e-01 9.61082220e-01 -6.84248284e-02
-1.99554190e-01 -5.90297461e-01 -6.38183951e-01 -1.04882598e+00
-1.89032242e-01 -1.05469847e+00 9.71248522e-02 -1.71426630e+00
-5.61303914e-01 2.28417858e-01 2.98433006e-01 -4.83906329e-01
-9.04559433e-01 -6.38056397e-01 -6.16298378e-01 8.31979632e-01
-8.13260794e-01 -1.05931520e+00 -4.14206207e-01 6.77046597e-01
-1.65988743e-01 3.09333839e-02 1.15796924e+00 -3.79636526e-01
1.44230306e-01 -2.55092308e-02 -1.91818580e-01 9.86784324e-02
-2.94553369e-01 -1.29790831e+00 6.93777442e-01 4.60160911e-01
2.32277468e-01 7.05668271e-01 1.02983940e+00 -5.82794011e-01
-1.72325063e+00 -4.16553915e-01 3.37140113e-01 -8.48259151e-01
8.21935117e-01 -4.62183058e-01 -6.32648230e-01 8.03203702e-01
-1.69495001e-01 -1.77352689e-02 4.83271420e-01 -4.33731377e-02
-2.34229177e-01 3.68006021e-01 -1.49410117e+00 1.18013763e+00
1.37259257e+00 -1.03287542e+00 -1.07130504e+00 -3.16635147e-02
8.93828928e-01 -5.93759060e-01 -7.95748830e-01 1.07276864e-01
6.57240212e-01 -8.44502211e-01 1.21751916e+00 -9.56937790e-01
7.48058632e-02 -4.67108518e-01 -2.49305069e-01 -1.23536992e+00
-1.01509541e-01 -7.70092070e-01 -2.32727587e-01 6.75312757e-01
9.85370725e-02 -7.99376428e-01 7.93036461e-01 1.34736764e+00
1.22264393e-01 -3.53675604e-01 -7.34498799e-01 -6.41178071e-01
3.30219179e-01 -1.10959148e+00 1.34360683e+00 8.11844587e-01
8.47480893e-01 -4.53228176e-01 7.47501791e-01 1.06403969e-01
3.01107556e-01 -3.70541774e-02 4.59604621e-01 -1.34750867e+00
-4.96836677e-02 -6.69977725e-01 -9.47824836e-01 -4.96745229e-01
1.05233051e-01 -7.12005198e-01 8.37851018e-02 -1.54997289e+00
-1.65935203e-01 -6.61866307e-01 -4.71648350e-02 2.25887984e-01
3.54474843e-01 -1.79022834e-01 2.73933470e-01 -1.86306179e-01
-7.24527717e-01 3.05569142e-01 1.13415301e+00 2.98291743e-01
-2.56660700e-01 -7.01729536e-01 -1.04130924e+00 1.00998354e+00
5.97958982e-01 -1.09191418e-01 -6.56466424e-01 -2.95587599e-01
8.52542400e-01 4.06369567e-01 1.14301944e+00 -1.34274435e+00
6.49323702e-01 -8.23500752e-01 5.57030857e-01 -1.70069888e-01
3.32020283e-01 -9.87515867e-01 3.36374342e-01 4.47104037e-01
-4.72968400e-01 1.37558784e-02 6.99167609e-01 2.13596806e-01
6.76862374e-02 -3.96081693e-02 2.71850348e-01 -4.30008531e-01
-1.27463377e+00 -1.78393006e-01 -7.45209575e-01 3.44371170e-01
1.45173478e+00 -4.73844409e-01 -4.51213956e-01 -5.36796510e-01
-9.50872242e-01 3.35387945e-01 9.86826181e-01 -1.32208467e-02
5.67646384e-01 -1.27311254e+00 -1.52911440e-01 2.49210477e-01
5.70268817e-02 -7.39602000e-02 4.64691371e-02 7.57354870e-02
-9.00731385e-01 2.59995759e-01 -7.24335134e-01 -1.25307322e-01
-5.04845738e-01 6.19173944e-01 7.77743220e-01 7.99117908e-02
-5.64774156e-01 7.92948306e-01 1.12352677e-01 -6.76507592e-01
7.52785131e-02 -5.38158000e-01 1.91433892e-01 -3.94828767e-01
7.01284230e-01 9.00863558e-02 -1.90773278e-01 -1.40790567e-01
-4.81425822e-01 -7.08367899e-02 8.19250882e-01 -9.59596753e-01
1.22854471e+00 -1.05212547e-01 5.33065237e-02 6.00566268e-01
5.17728090e-01 -3.53210807e-01 -1.19505394e+00 1.42326638e-01
8.85086060e-02 -4.71351862e-01 3.13670546e-01 -1.30097198e+00
-2.12063491e-01 6.81119740e-01 3.68377388e-01 3.40084314e-01
1.07431555e+00 1.02403373e-01 4.24040139e-01 5.62687755e-01
1.10534608e+00 -1.11449122e+00 -1.36326537e-01 3.60394716e-01
6.41595006e-01 -8.73976171e-01 -3.04034829e-01 5.52049093e-02
-5.33696532e-01 9.14613008e-01 6.31949723e-01 -9.16992575e-02
5.77049613e-01 7.49009669e-01 -8.09199363e-02 -5.53712130e-01
-8.53124559e-01 -3.66847217e-01 -1.02746151e-01 1.37849498e+00
-6.10342585e-02 1.41358957e-01 4.19731587e-01 7.86388099e-01
-7.60617316e-01 7.20316470e-01 4.63751346e-01 1.37498987e+00
-5.00215769e-01 -6.00476205e-01 -4.19455260e-01 -1.15010723e-01
1.56899020e-01 -7.30310427e-03 -2.52287567e-01 1.19041741e+00
1.47475243e-01 8.32136631e-01 4.40682709e-01 -2.64676780e-01
9.93916839e-02 1.86992630e-01 8.98888290e-01 -6.23300791e-01
-8.18085730e-01 -8.55117977e-01 5.87215424e-02 -9.70099747e-01
-4.29241806e-02 -6.09838843e-01 -2.11513281e+00 -8.09817076e-01
9.92580727e-02 3.49525601e-01 8.09758782e-01 9.63965297e-01
3.50375503e-01 5.45433164e-01 2.75935400e-02 -7.67745256e-01
-2.75096059e-01 -2.65999883e-01 -7.07274258e-01 3.03965062e-02
-5.31830676e-02 -7.72223890e-01 -2.09568441e-01 -2.75945991e-01] | [4.082743167877197, 1.187160611152649] |
b687fa9c-d68f-4ccb-8736-6d9857d19c39 | two-level-graph-neural-network | 2201.01190 | null | https://arxiv.org/abs/2201.01190v1 | https://arxiv.org/pdf/2201.01190v1.pdf | Two-level Graph Neural Network | Graph Neural Networks (GNNs) are recently proposed neural network structures for the processing of graph-structured data. Due to their employed neighbor aggregation strategy, existing GNNs focus on capturing node-level information and neglect high-level information. Existing GNNs therefore suffer from representational limitations caused by the Local Permutation Invariance (LPI) problem. To overcome these limitations and enrich the features captured by GNNs, we propose a novel GNN framework, referred to as the Two-level GNN (TL-GNN). This merges subgraph-level information with node-level information. Moreover, we provide a mathematical analysis of the LPI problem which demonstrates that subgraph-level information is beneficial to overcoming the problems associated with LPI. A subgraph counting method based on the dynamic programming algorithm is also proposed, and this has time complexity is O(n^3), n is the number of nodes of a graph. Experiments show that TL-GNN outperforms existing GNNs and achieves state-of-the-art performance. | ['Edwin R Hancock', 'Zhihong Zhang', 'Chengyu Sun', 'Xing Ai'] | 2022-01-03 | null | null | null | null | ['subgraph-counting'] | ['graphs'] | [ 3.89445841e-01 1.62870675e-01 -4.12979931e-01 -1.37820318e-01
1.87959090e-01 -6.51187375e-02 2.34708250e-01 3.19150776e-01
-4.16631758e-01 6.78926766e-01 -7.18396679e-02 -3.70614439e-01
-7.18379438e-01 -1.42802846e+00 -6.06763124e-01 -6.97710752e-01
-6.13225043e-01 1.35498032e-01 2.81986624e-01 -1.44765675e-01
7.98497573e-02 6.05718017e-01 -1.52494347e+00 -1.00182839e-01
7.94600010e-01 7.55391300e-01 8.05680454e-02 3.17076683e-01
-3.66779685e-01 7.25156367e-01 -4.68490988e-01 -1.91853493e-01
4.80571032e-01 -3.23927909e-01 -5.29742062e-01 -1.47496998e-01
3.46930027e-01 -8.59470069e-02 -8.03023756e-01 1.36212337e+00
3.86361301e-01 2.92378426e-01 2.51235902e-01 -1.65188158e+00
-5.10727286e-01 9.13337111e-01 -7.38019705e-01 1.34138867e-01
6.11627884e-02 -5.09378135e-01 1.14309478e+00 -4.52616215e-01
6.57495618e-01 1.17151642e+00 9.56753731e-01 2.92340010e-01
-9.30072427e-01 -6.06700599e-01 4.49302286e-01 1.75999105e-01
-1.50744677e+00 1.18667960e-01 1.15268421e+00 2.08024345e-02
8.65138888e-01 2.81355381e-01 8.00183773e-01 6.12930655e-01
2.16036625e-02 6.04489386e-01 7.58859158e-01 -4.74739760e-01
9.76753607e-02 -4.65485215e-01 5.20123065e-01 1.05865920e+00
9.53733504e-01 -6.11504307e-04 -3.53448361e-01 8.49590003e-02
1.02692187e+00 1.01770833e-01 -1.49207771e-01 -6.05725944e-01
-8.65385652e-01 8.24081123e-01 9.26928341e-01 5.58804214e-01
-3.79700869e-01 2.99569696e-01 4.77439702e-01 4.02336717e-01
3.68074179e-01 2.35680431e-01 -1.93032116e-01 3.53243291e-01
-7.09902823e-01 -7.89892301e-02 8.58927727e-01 1.00294876e+00
8.61151576e-01 3.49100351e-01 -4.21962813e-02 8.12035382e-01
1.72907084e-01 6.92824125e-02 2.46981904e-01 -5.63194692e-01
5.63460410e-01 1.36002171e+00 -7.37147570e-01 -1.78203392e+00
-7.76906550e-01 -9.41892505e-01 -1.63885880e+00 -2.13221014e-01
1.88031048e-01 9.31315473e-04 -1.05482197e+00 1.99166107e+00
1.17445074e-01 7.37124607e-02 -7.95456469e-02 3.24751139e-01
1.23206735e+00 4.92744714e-01 -9.00548995e-02 -2.57855088e-01
9.91907001e-01 -1.00879431e+00 -6.32295907e-01 -1.77822337e-01
7.13028610e-01 1.94494441e-01 5.63423395e-01 1.09600283e-01
-1.00680768e+00 -4.81575161e-01 -1.12335837e+00 1.79034203e-01
-8.21918368e-01 -6.17517345e-02 9.59562361e-01 8.25297058e-01
-1.55340064e+00 7.11490452e-01 -5.73864102e-01 -4.80367839e-01
3.96887094e-01 7.39894032e-01 -5.17592490e-01 -1.45436630e-01
-1.14693630e+00 4.47887510e-01 9.61443305e-01 4.37165797e-01
-3.19451898e-01 -3.64188284e-01 -1.15444469e+00 4.62665826e-01
7.16179788e-01 -4.76617008e-01 6.33951187e-01 -7.25401461e-01
-8.62859905e-01 2.16798559e-01 -1.00560457e-01 -4.92718816e-01
3.30359861e-02 3.57552201e-01 -5.68335593e-01 2.46354520e-01
-1.68069601e-02 5.12088656e-01 4.12167549e-01 -1.09893847e+00
-4.15545672e-01 -3.65781933e-01 3.64910156e-01 1.28373235e-01
-7.23942935e-01 -2.53197610e-01 -7.24435627e-01 -5.99943161e-01
5.87565839e-01 -6.32361174e-01 -5.27121365e-01 -2.42026940e-01
-6.25771999e-01 -4.61095095e-01 8.49174380e-01 -3.64042670e-01
1.79986167e+00 -1.91275215e+00 -9.78899747e-02 8.53053331e-01
9.54576135e-01 5.85463464e-01 -4.35115397e-01 7.14456856e-01
-1.46985605e-01 8.84353071e-02 -1.68716773e-01 5.09861996e-03
2.67435238e-02 3.73613536e-01 2.90080965e-01 3.31130981e-01
-4.89273667e-02 9.94626045e-01 -7.78616846e-01 -5.37986398e-01
1.99023411e-01 3.09616894e-01 -4.89667475e-01 -2.37264499e-01
3.86675783e-02 -2.27128431e-01 -3.55200469e-01 5.77694833e-01
9.84661937e-01 -5.07812083e-01 6.04252458e-01 -3.74099731e-01
7.63491243e-02 -7.59491101e-02 -1.34167683e+00 1.21194017e+00
-1.87384412e-02 3.44330013e-01 9.30820107e-02 -1.35325694e+00
9.97057855e-01 -7.15917945e-02 4.44302171e-01 -7.13505566e-01
2.68577516e-01 5.21495342e-02 2.50607461e-01 -1.80964783e-01
3.61818373e-01 3.25201273e-01 -1.14129610e-01 2.98615277e-01
1.64928630e-01 7.57559717e-01 7.64335692e-01 4.58542019e-01
1.44251895e+00 -2.09493548e-01 6.66581452e-01 -5.13776183e-01
5.70822656e-01 -2.99137533e-01 7.10030854e-01 1.14642835e+00
-1.23963699e-01 1.00122139e-01 8.15812230e-01 -7.92909026e-01
-7.27476835e-01 -7.62202382e-01 3.95744711e-01 9.99088943e-01
1.35885015e-01 -6.93959236e-01 -9.69159722e-01 -5.23002744e-01
-1.00336127e-01 1.40559569e-01 -7.08568573e-01 -2.30495259e-01
-6.99667037e-01 -9.77494717e-01 6.54757261e-01 6.23061359e-01
7.69754589e-01 -1.12072742e+00 -3.53220522e-01 4.09103662e-01
9.03786495e-02 -1.17186725e+00 -1.84046701e-01 2.50044197e-01
-1.11651850e+00 -1.16367483e+00 -4.10492748e-01 -1.13050115e+00
1.08286798e+00 4.59357619e-01 1.15270627e+00 5.27362466e-01
-3.63590047e-02 -1.97120551e-02 -3.38391840e-01 -7.36463815e-02
-9.32062492e-02 4.17611480e-01 -4.25581913e-03 -8.21821317e-02
3.84566963e-01 -1.05909514e+00 -2.94325113e-01 5.80235422e-02
-9.44711208e-01 1.75675467e-01 9.68011439e-01 7.93949604e-01
4.63218361e-01 6.05589390e-01 6.62124634e-01 -1.11359501e+00
8.72084916e-01 -2.60830134e-01 -6.64960802e-01 3.08563679e-01
-7.83265769e-01 1.64587289e-01 9.19829428e-01 -2.15757117e-01
-6.46264315e-01 -6.31008595e-02 2.13124212e-02 -1.99174970e-01
-1.88909676e-02 1.03553164e+00 -4.22666967e-01 -4.30068314e-01
1.50209397e-01 2.16114312e-01 -1.20613351e-01 -3.06712896e-01
4.54782322e-03 2.18113542e-01 4.70452845e-01 -3.26829463e-01
8.36672843e-01 2.92900145e-01 6.93379939e-01 -9.11877811e-01
-5.84432542e-01 -3.46447945e-01 -6.02829933e-01 -2.33371720e-01
4.08987969e-01 -6.31264150e-01 -9.94085729e-01 6.29879594e-01
-9.67319489e-01 7.64699094e-03 -3.70039195e-02 3.19452286e-01
3.56762335e-02 6.93507612e-01 -7.81291485e-01 -8.30543399e-01
-4.07392085e-01 -8.50704491e-01 4.13927078e-01 2.24878892e-01
2.22068712e-01 -1.11949825e+00 -1.89096108e-01 -1.34691507e-01
4.70431894e-01 5.86061478e-01 1.30630100e+00 -9.41433847e-01
-6.55115128e-01 -2.91542768e-01 -7.68798292e-01 1.21927515e-01
-2.07295939e-02 -3.42408717e-01 -3.58593941e-01 -5.64475358e-01
-2.74445832e-01 1.58150911e-01 8.66603851e-01 4.67244387e-01
1.37427986e+00 -5.64561248e-01 -4.58815902e-01 6.61725402e-01
1.76801693e+00 2.47496098e-01 5.15093267e-01 2.79830575e-01
1.09784794e+00 3.82745028e-01 -8.74479860e-03 2.02470586e-01
4.23000216e-01 1.60050631e-01 6.59609437e-01 -3.03590775e-01
-4.01781239e-02 -3.14348549e-01 -1.25185326e-01 1.30644965e+00
-1.64649814e-01 -6.59151495e-01 -6.70744002e-01 5.55057287e-01
-1.97633111e+00 -6.90546811e-01 -3.62127215e-01 1.92311823e+00
1.26976356e-01 3.09791893e-01 7.83292577e-02 4.66990143e-01
1.06377375e+00 4.89278436e-01 -4.67348576e-01 -4.22925472e-01
-1.41867071e-01 2.21258342e-01 7.27573097e-01 1.34166181e-01
-1.01350617e+00 8.80991399e-01 5.80764914e+00 9.37951028e-01
-6.14484429e-01 -3.04405093e-01 3.27163339e-01 3.59662324e-01
-2.46118680e-01 -1.73476383e-01 -5.25037944e-01 2.87349671e-01
8.31718087e-01 -2.27529615e-01 4.97225523e-01 6.67329848e-01
-1.18228696e-01 1.70471698e-01 -7.44878173e-01 8.34867060e-01
1.16146736e-01 -1.04556072e+00 5.00438869e-01 3.27337682e-01
5.96377492e-01 -8.15395936e-02 -3.09175193e-01 4.82304454e-01
3.34951878e-01 -9.98016059e-01 -4.98795649e-04 1.95311934e-01
7.46138334e-01 -1.06935406e+00 1.00595081e+00 3.27307224e-01
-1.75919485e+00 -2.75149673e-01 -4.95644301e-01 -3.24177504e-01
-7.09461197e-02 6.59273267e-01 -5.31358361e-01 1.11472130e+00
6.91492260e-01 6.08940721e-01 -7.04867005e-01 1.04065895e+00
6.41434938e-02 2.94054687e-01 -5.11386693e-01 -3.71329874e-01
5.57481289e-01 -4.26530838e-01 4.48021472e-01 9.26623523e-01
3.78175139e-01 3.57785337e-02 2.05656722e-01 6.95545733e-01
-4.00792092e-01 4.61994112e-02 -7.42790997e-01 -2.81155854e-01
5.16367495e-01 1.18173289e+00 -1.21306610e+00 -2.04641357e-01
-3.78656089e-01 5.37432194e-01 5.86877167e-01 3.05311918e-01
-4.99728709e-01 -9.73398328e-01 2.09592879e-01 -1.35633618e-01
4.32294637e-01 -2.13660538e-01 2.01007780e-02 -8.33335161e-01
2.09380597e-01 -7.70502388e-01 6.09596193e-01 -3.97379100e-01
-1.07320416e+00 8.79276752e-01 1.87521577e-01 -1.05764687e+00
5.85109368e-03 -8.38276684e-01 -6.09455407e-01 3.28120261e-01
-1.29407728e+00 -1.15980542e+00 -4.72572058e-01 6.50999248e-01
2.56438348e-02 -1.64843142e-01 6.57159626e-01 4.57561225e-01
-6.41322017e-01 7.49592602e-01 -5.56706414e-02 4.95455325e-01
-1.45028487e-01 -1.06908166e+00 5.97878993e-01 1.18428016e+00
1.14083722e-01 8.57634783e-01 3.59301835e-01 -7.09441483e-01
-1.40280676e+00 -1.25272584e+00 1.02355945e+00 3.46187472e-01
4.85568613e-01 -4.12407398e-01 -7.73242712e-01 5.55453777e-01
-1.30218193e-01 1.02532595e-01 6.36094689e-01 1.89355984e-01
-2.84773141e-01 -3.59892875e-01 -1.13726175e+00 7.37188160e-01
1.66991103e+00 -3.23477238e-01 -3.28171074e-01 1.13743030e-01
9.78923738e-01 -2.93102443e-01 -6.73483551e-01 6.87708974e-01
4.87783402e-01 -1.11556935e+00 8.83761585e-01 -4.14354652e-01
3.69426794e-02 -2.93682486e-01 6.68926761e-02 -1.06946611e+00
-6.25737667e-01 -4.17537093e-01 -2.82272607e-01 8.93303812e-01
1.67116940e-01 -9.17745173e-01 1.12704754e+00 2.75748130e-02
-2.79250983e-02 -8.37158799e-01 -8.86366844e-01 -9.78636801e-01
-3.92449290e-01 -2.70606369e-01 9.11453784e-01 8.81337285e-01
-2.06964195e-01 3.67553771e-01 -3.34867269e-01 2.41682678e-01
8.87850225e-01 8.48115012e-02 4.96201217e-01 -1.68623507e+00
4.67939638e-02 -5.81823349e-01 -7.86702931e-01 -8.62744272e-01
1.57064259e-01 -9.94759321e-01 -2.74238437e-01 -1.89498973e+00
2.28880405e-01 -1.02697201e-01 -7.10781932e-01 5.96213877e-01
1.52492255e-01 2.58062035e-01 2.17720866e-01 -1.72107965e-01
-7.45127618e-01 3.04937541e-01 1.14163232e+00 -2.47035138e-02
-3.57475162e-01 -1.61652759e-01 -7.65174091e-01 7.73913980e-01
8.34573865e-01 -3.61032873e-01 -5.53506613e-01 -2.90074259e-01
3.51997495e-01 -5.57994023e-02 3.46687257e-01 -1.42893553e+00
5.55365503e-01 2.17086866e-01 2.48951718e-01 -9.87186432e-01
2.02575419e-02 -9.55622196e-01 1.99459046e-01 6.75796151e-01
-1.72227159e-01 3.62268329e-01 4.18897346e-02 7.77263284e-01
-3.25302720e-01 -1.05927482e-01 3.27078760e-01 -2.31474370e-01
-7.52213955e-01 6.42387450e-01 -2.06695989e-01 -3.03581685e-01
7.16660500e-01 -6.23945236e-01 -4.90740389e-01 -4.08904880e-01
-4.97493684e-01 3.43225420e-01 -7.31538162e-02 1.86007783e-01
5.97989619e-01 -1.43352771e+00 -3.19721162e-01 3.80781233e-01
7.49490410e-02 1.64365396e-01 3.09876978e-01 6.93832636e-01
-5.75533450e-01 5.99119425e-01 -3.19622308e-01 -2.57716596e-01
-1.28444541e+00 7.05457211e-01 2.88508385e-02 -7.80577302e-01
-5.89050889e-01 7.20937312e-01 1.49141103e-01 -8.29232454e-01
4.27138120e-01 -3.05350631e-01 -4.65340942e-01 -7.63093978e-02
1.05649732e-01 6.45957470e-01 2.08112985e-01 -6.31030560e-01
-2.89248139e-01 5.15132606e-01 -1.45646736e-01 4.97446299e-01
1.47072124e+00 4.09664363e-02 -6.49867356e-01 3.68123800e-02
1.19950330e+00 -3.97820711e-01 -6.68218732e-01 -4.52729344e-01
1.89071655e-01 7.31446734e-03 -9.82455015e-02 -3.72990221e-01
-1.30966318e+00 6.13484144e-01 2.33243510e-01 4.86428708e-01
1.42792714e+00 -3.77952844e-01 9.23558116e-01 8.86876762e-01
3.87867600e-01 -9.50181961e-01 -1.92769572e-01 6.90276206e-01
4.18964207e-01 -6.29748166e-01 1.24489196e-01 -6.54950857e-01
1.83976248e-01 1.05155444e+00 8.59254003e-01 -3.04684997e-01
7.17963636e-01 3.69854644e-02 -4.67525423e-01 -3.75559092e-01
-3.56458455e-01 -3.68341058e-01 2.11398810e-01 6.59221113e-01
-1.09920532e-01 6.58675730e-02 -5.42790711e-01 5.56809366e-01
-1.05175510e-01 -6.57115132e-02 3.97409469e-01 8.18234980e-01
-3.32332313e-01 -1.08982837e+00 2.10707188e-01 7.56364465e-01
-2.24912032e-01 -3.42154264e-01 -3.98624510e-01 1.10917914e+00
8.68579894e-02 7.59182274e-01 -1.04427198e-02 -5.83658695e-01
1.61749572e-01 -3.38749319e-01 2.52070516e-01 -3.58348817e-01
-4.45244819e-01 -2.60681778e-01 9.49564576e-02 -6.00623965e-01
-5.59988737e-01 7.28056720e-03 -1.04350388e+00 -4.12526280e-01
-2.73879230e-01 2.33095676e-01 4.19267803e-01 7.11465836e-01
4.96895015e-01 7.66523123e-01 4.00656313e-01 -6.94240749e-01
-2.47416303e-01 -8.07322204e-01 -7.65746653e-01 8.63857344e-02
2.53761590e-01 -4.87707287e-01 -3.82600665e-01 -7.18604445e-01] | [7.022201061248779, 6.214372634887695] |
6e48f2dd-5d42-4ed5-bab5-a48520e60d86 | improving-scene-text-recognition-for | 2304.08592 | null | https://arxiv.org/abs/2304.08592v1 | https://arxiv.org/pdf/2304.08592v1.pdf | Improving Scene Text Recognition for Character-Level Long-Tailed Distribution | Despite the recent remarkable improvements in scene text recognition (STR), the majority of the studies focused mainly on the English language, which only includes few number of characters. However, STR models show a large performance degradation on languages with a numerous number of characters (e.g., Chinese and Korean), especially on characters that rarely appear due to the long-tailed distribution of characters in such languages. To address such an issue, we conducted an empirical analysis using synthetic datasets with different character-level distributions (e.g., balanced and long-tailed distributions). While increasing a substantial number of tail classes without considering the context helps the model to correctly recognize characters individually, training with such a synthetic dataset interferes the model with learning the contextual information (i.e., relation among characters), which is also important for predicting the whole word. Based on this motivation, we propose a novel Context-Aware and Free Experts Network (CAFE-Net) using two experts: 1) context-aware expert learns the contextual representation trained with a long-tailed dataset composed of common words used in everyday life and 2) context-free expert focuses on correctly predicting individual characters by utilizing a dataset with a balanced number of characters. By training two experts to focus on learning contextual and visual representations, respectively, we propose a novel confidence ensemble method to compensate the limitation of each expert. Through the experiments, we demonstrate that CAFE-Net improves the STR performance on languages containing numerous number of characters. Moreover, we show that CAFE-Net is easily applicable to various STR models. | ['Jaegul Choo', 'Jungsoo Lee', 'Sunghyo Chung', 'Sunghyun Park'] | 2023-03-31 | null | null | null | null | ['scene-text-recognition'] | ['computer-vision'] | [ 3.07387531e-01 -5.80201983e-01 -8.54559839e-02 -2.73940653e-01
-2.84206390e-01 -4.46853936e-01 5.91338575e-01 -1.59160066e-02
-5.58398366e-01 6.86127305e-01 9.93956178e-02 -3.99619877e-01
2.68306017e-01 -8.13597500e-01 -7.66723752e-01 -6.01349175e-01
4.40453559e-01 2.98165709e-01 2.84160733e-01 -7.90031925e-02
2.29112521e-01 2.55474508e-01 -1.62016034e+00 5.10605276e-01
1.23978221e+00 8.26065302e-01 5.60505807e-01 4.28340197e-01
-5.00920177e-01 5.91030121e-01 -8.19550216e-01 -4.34999496e-01
-2.44016554e-02 -2.63756454e-01 -1.66506827e-01 3.05514276e-01
2.30125308e-01 -1.32389486e-01 -2.60866553e-01 1.05947375e+00
4.03807372e-01 9.88856703e-02 8.84800494e-01 -9.87800360e-01
-8.56107533e-01 7.39218056e-01 -5.96978188e-01 -6.80670440e-02
1.96275994e-01 6.07564561e-02 9.66223001e-01 -1.18136394e+00
3.58160466e-01 1.26866102e+00 7.39174843e-01 4.48763609e-01
-9.06227827e-01 -6.58234119e-01 6.91752315e-01 2.61824846e-01
-1.55549145e+00 1.80069078e-02 9.09445763e-01 -4.39830065e-01
7.94825077e-01 2.31839661e-02 3.76327157e-01 1.61462593e+00
1.13941438e-01 9.30882335e-01 1.07413602e+00 -6.56122208e-01
2.52284795e-01 3.29235047e-01 3.22225958e-01 2.98315465e-01
4.46708888e-01 -1.65902674e-01 -2.35891059e-01 1.07968122e-01
4.13761973e-01 3.89273427e-02 -1.66965097e-01 -1.13569483e-01
-1.16949105e+00 7.58982599e-01 -5.02783991e-02 5.10907710e-01
-6.90110549e-02 -1.49635702e-01 5.25178254e-01 -2.40241718e-02
2.91443735e-01 4.10176665e-02 -3.63050044e-01 2.02321936e-03
-7.68015802e-01 -1.17498472e-01 6.76912785e-01 1.10288548e+00
6.70074582e-01 4.33091313e-01 -2.43426934e-01 1.11623168e+00
4.33847532e-02 6.29196107e-01 7.23744094e-01 6.12845086e-03
6.82072937e-01 5.90878367e-01 2.03300312e-01 -1.12158132e+00
-2.90500104e-01 -7.35015094e-01 -1.12286067e+00 -5.17389961e-02
5.60590804e-01 -3.11282307e-01 -1.03850293e+00 1.89837897e+00
-2.83168461e-02 9.22817886e-02 1.98772356e-01 7.08159924e-01
6.57550991e-01 8.15493166e-01 2.82383293e-01 -5.18111587e-02
1.47203600e+00 -1.00417316e+00 -6.55659020e-01 -4.17981952e-01
5.39341748e-01 -7.83282995e-01 1.57313216e+00 5.16498983e-01
-4.03383046e-01 -8.17541122e-01 -1.08169913e+00 2.33798251e-01
-6.43498719e-01 7.41882205e-01 2.74236709e-01 9.98927057e-01
-5.11402607e-01 2.00686514e-01 -4.62893158e-01 -3.53108108e-01
1.93243697e-01 -1.10127479e-01 -3.13868910e-01 -2.34285936e-01
-1.29324162e+00 7.78447092e-01 7.18618870e-01 5.62877133e-02
-6.04846060e-01 -2.96522081e-01 -7.90409446e-01 6.52611777e-02
5.36625087e-01 -4.69671220e-01 8.38524580e-01 -1.48816597e+00
-1.17915630e+00 3.79646927e-01 -1.18080996e-01 -3.03672314e-01
8.40131223e-01 -4.10725147e-01 -8.01958203e-01 8.13163072e-03
1.03415381e-02 3.38193417e-01 9.75383341e-01 -1.38459337e+00
-6.16224587e-01 -1.23981513e-01 -2.20805660e-01 2.04191968e-01
-6.83350086e-01 -6.38143495e-02 -5.57794094e-01 -9.95028973e-01
-1.93369925e-01 -6.97699606e-01 1.03089295e-01 -1.10358216e-01
-6.01658106e-01 -1.29721254e-01 8.60963702e-01 -5.71475148e-01
1.24244702e+00 -2.24712515e+00 -2.47764036e-01 1.43085301e-01
-1.93971112e-01 3.58306110e-01 -2.35118493e-01 4.24468517e-01
-1.17597885e-01 2.21442267e-01 -2.42630556e-01 -3.55529845e-01
-7.11875036e-02 2.78455645e-01 -2.45511487e-01 9.86657441e-02
2.41525292e-01 4.62072164e-01 -8.16489637e-01 -5.45960069e-01
1.63693622e-01 5.05370021e-01 -2.70630360e-01 1.25024259e-01
-3.39973986e-01 1.61425009e-01 -5.81779659e-01 5.71852386e-01
8.19393158e-01 -2.25651056e-01 2.54136741e-01 -1.57454506e-01
-6.91578239e-02 -3.05583358e-01 -1.53338647e+00 1.19830227e+00
-6.27967358e-01 5.08051693e-01 -4.18264657e-01 -1.01650512e+00
1.16336846e+00 1.69777960e-01 -1.51093511e-04 -5.25177300e-01
1.07635692e-01 2.20008820e-01 5.00328280e-02 -4.50557768e-01
6.29125595e-01 -1.69798136e-01 -2.47281604e-02 1.75211564e-01
-2.62122124e-01 1.76979303e-01 4.38593358e-01 8.73538181e-02
8.82127643e-01 6.68027028e-02 3.39612216e-01 2.88710482e-02
7.31992722e-01 -2.50297993e-01 6.78695142e-01 8.53110135e-01
-1.04676552e-01 7.59053469e-01 4.88857269e-01 -4.08312798e-01
-1.18366122e+00 -7.87649393e-01 -2.35022590e-01 1.01443970e+00
2.00547114e-01 -4.85436499e-01 -5.91736794e-01 -8.28416884e-01
-1.61496177e-01 1.07974350e+00 -7.19190419e-01 -4.12213653e-02
-2.79102355e-01 -9.51424360e-01 5.99445343e-01 7.85984516e-01
6.95103467e-01 -1.15575385e+00 -5.06836534e-01 1.75323620e-01
-9.44534391e-02 -1.40684497e+00 -4.38738346e-01 2.17742592e-01
-4.76874560e-01 -9.61656332e-01 -8.39629292e-01 -7.43840635e-01
6.78089559e-01 2.19152406e-01 1.10470998e+00 -8.39357972e-02
-9.61143300e-02 3.36941212e-01 -7.12460160e-01 -4.63272989e-01
-3.17640066e-01 -2.00550258e-02 -1.45136923e-01 4.79885697e-01
4.53396678e-01 -3.94745857e-01 -3.75334173e-01 5.11148870e-01
-9.96436357e-01 3.80523264e-01 7.26603389e-01 1.06969976e+00
4.37015533e-01 2.27896288e-01 6.93109632e-01 -1.08514297e+00
5.94960034e-01 -5.25719881e-01 -3.42862427e-01 6.33029819e-01
-3.64459991e-01 5.84699959e-03 1.13298881e+00 -1.04598379e+00
-1.15020585e+00 -1.28280953e-01 -1.91013083e-01 -3.15882236e-01
-3.59645128e-01 5.90578079e-01 -4.62439239e-01 3.89063001e-01
5.02421319e-01 7.10750520e-01 -4.34447855e-01 -4.07204181e-01
1.16723463e-01 6.96007550e-01 3.66518974e-01 -8.48217428e-01
7.61955500e-01 1.91939592e-01 -3.03381801e-01 -9.39502537e-01
-5.69803059e-01 -2.61592031e-01 -4.70889360e-01 -5.67572750e-02
8.32012415e-01 -9.32808459e-01 -2.74285436e-01 7.91076720e-01
-1.03621304e+00 -1.77996904e-01 -3.29879634e-02 6.05522513e-01
-2.49529302e-01 6.85578644e-01 -2.81188011e-01 -1.02824688e+00
-1.97676778e-01 -9.97315049e-01 8.61548901e-01 2.36176893e-01
-1.92548651e-02 -9.75468814e-01 -4.57023270e-02 2.16912962e-02
2.40284830e-01 1.80986643e-01 1.30264962e+00 -1.04627466e+00
-2.63987124e-01 -3.49603504e-01 -3.08589220e-01 6.24122977e-01
1.79351717e-01 3.03478718e-01 -8.46861243e-01 -1.09897211e-01
-2.56121904e-01 -3.71156961e-01 7.71393895e-01 4.29930687e-02
1.39944482e+00 -3.77499238e-02 -1.72152430e-01 3.54594201e-01
1.44531083e+00 3.19988549e-01 6.74728274e-01 2.40316942e-01
6.94930017e-01 4.84395593e-01 6.06822371e-01 5.87905049e-01
3.10878903e-01 4.91270542e-01 3.29649448e-01 8.51987228e-02
-8.34517032e-02 -4.75317180e-01 3.79006356e-01 8.27022374e-01
5.79502471e-02 -6.76099062e-01 -9.58698809e-01 5.49690127e-01
-1.85265958e+00 -6.93273365e-01 8.81148726e-02 2.23587012e+00
8.31082523e-01 2.63051003e-01 -6.56565353e-02 2.37297505e-01
1.13263166e+00 2.09178016e-01 -6.28840327e-01 -2.29378626e-01
-6.12308323e-01 -9.64708030e-02 8.55524614e-02 7.18707293e-02
-1.08541048e+00 1.00191295e+00 5.28704405e+00 1.44063711e+00
-1.12355042e+00 -2.74291605e-01 6.77565992e-01 4.04776216e-01
-4.97848451e-01 -1.55560032e-01 -9.57560897e-01 8.58140409e-01
5.84102392e-01 1.60486195e-02 1.39872596e-01 9.63853598e-01
2.52605900e-02 -9.82119963e-02 -8.63499224e-01 1.12638533e+00
3.78195226e-01 -9.65191424e-01 4.57897335e-01 -3.82421136e-01
7.65287101e-01 -3.50764126e-01 4.09549586e-02 4.77186501e-01
1.54564437e-02 -1.09128940e+00 9.20714378e-01 3.90780121e-01
9.42097008e-01 -8.10274780e-01 8.12098205e-01 7.69838750e-01
-1.21125805e+00 -2.07982063e-02 -6.07518077e-01 1.49187967e-01
-1.54633120e-01 7.27618992e-01 -4.60621446e-01 6.67078733e-01
3.71222705e-01 6.63302600e-01 -7.60351598e-01 9.38901067e-01
-3.21557641e-01 6.66424632e-01 -1.98830426e-01 -2.93152660e-01
3.44701976e-01 -2.60587662e-01 4.31502312e-01 1.56574893e+00
4.85884994e-01 -3.59538496e-02 2.59163558e-01 5.91885090e-01
1.30699314e-02 4.30082619e-01 -6.25401676e-01 -4.47092280e-02
3.92610222e-01 1.13391018e+00 -8.11916649e-01 -5.01651943e-01
-7.82189369e-01 8.49542797e-01 3.11558574e-01 6.54011607e-01
-8.64693820e-01 -4.80283350e-01 1.34967580e-01 -1.86171662e-02
5.05348682e-01 -1.67611197e-01 -5.04621387e-01 -1.39159703e+00
1.80462420e-01 -1.10006928e+00 2.91096658e-01 -8.09216440e-01
-1.48859441e+00 8.60314667e-01 -9.23630148e-02 -1.38148057e+00
-1.76274255e-02 -9.08269703e-01 -7.42492974e-01 8.64265203e-01
-1.52525866e+00 -1.17239141e+00 -3.93016815e-01 7.61081219e-01
7.80033886e-01 -3.56347352e-01 5.80633104e-01 2.12246880e-01
-8.76421988e-01 9.49677348e-01 3.44241261e-01 3.72873515e-01
8.11529696e-01 -1.14407206e+00 8.67082253e-02 9.24099863e-01
2.73537338e-01 5.90580523e-01 5.67013383e-01 -8.15533817e-01
-1.15263546e+00 -1.09049857e+00 7.63677478e-01 -1.53763533e-01
5.33969402e-01 -5.31478047e-01 -9.52194095e-01 5.35860419e-01
9.60825384e-02 1.63131170e-02 6.25060201e-01 5.69212856e-03
-6.34787142e-01 -3.05623151e-02 -9.59318638e-01 9.04472351e-01
8.89221191e-01 -4.23831254e-01 -7.07616448e-01 1.88541263e-01
3.87883514e-01 -9.86574218e-02 -2.93543935e-01 5.17889261e-01
5.94549417e-01 -9.27900195e-01 6.64044797e-01 -5.33133268e-01
5.26728570e-01 -4.37066108e-01 -4.22078133e-01 -1.23543441e+00
-1.10193625e-01 -7.96042681e-02 3.71495970e-02 1.27323198e+00
3.73345762e-01 -7.28085220e-01 6.52113914e-01 1.94390386e-01
-9.15450826e-02 -6.84213161e-01 -7.46946514e-01 -9.67711627e-01
1.86284631e-01 -6.58823431e-01 4.16442782e-01 7.57700861e-01
-4.07688409e-01 3.07459384e-01 -6.30996943e-01 1.11019313e-01
2.45105043e-01 1.42834976e-01 7.46029437e-01 -9.48402286e-01
-2.83117175e-01 -2.53067106e-01 -2.18408749e-01 -1.20241261e+00
2.59353310e-01 -6.04103446e-01 3.62306871e-02 -1.19661796e+00
4.14043635e-01 -4.86108929e-01 -1.55024588e-01 3.28856409e-01
-5.08759320e-01 1.05661519e-01 2.78561920e-01 -4.88451906e-02
-5.07855833e-01 7.08898723e-01 1.09719539e+00 -2.44302690e-01
1.41912445e-01 1.75071150e-01 -5.77787697e-01 9.76153672e-01
6.81656718e-01 -2.39666283e-01 -5.43709040e-01 -3.11159372e-01
3.70055377e-01 -2.98453391e-01 2.45395333e-01 -1.11051714e+00
1.37362942e-01 -1.97895601e-01 7.19350159e-01 -8.48821819e-01
2.31367692e-01 -1.03175139e+00 -9.20673981e-02 2.29337171e-01
-2.19745427e-01 1.09202094e-01 1.95658103e-01 8.29817235e-01
-3.85458261e-01 -4.92685944e-01 6.93196833e-01 -7.09334761e-02
-9.13783729e-01 3.71216796e-02 -4.78210360e-01 2.18305066e-01
9.83540833e-01 -6.24502599e-01 -4.39531237e-01 -4.16229159e-01
-5.63760519e-01 2.16036644e-02 4.63943809e-01 4.21827763e-01
6.04064941e-01 -1.22533453e+00 -7.51264274e-01 2.95565695e-01
3.19619775e-01 -1.06573418e-01 4.91591215e-01 4.39484298e-01
-4.83842701e-01 1.75986245e-01 -8.62707421e-02 -5.50000370e-01
-1.07575321e+00 7.63086140e-01 2.30583787e-01 -4.23819989e-01
-5.32129467e-01 4.24891829e-01 5.05215824e-01 -3.50814015e-01
4.41675484e-01 -4.47147846e-01 -4.98583823e-01 2.34977320e-01
4.95398462e-01 1.27846211e-01 -8.92559439e-02 -5.04405677e-01
-3.37742746e-01 9.11861062e-01 -2.00685546e-01 8.91251117e-02
1.01778030e+00 -6.38809660e-03 4.08382654e-01 7.21187890e-01
8.09741437e-01 3.64519417e-01 -1.42091882e+00 -3.97217214e-01
-1.00184277e-01 -5.04746556e-01 -4.08078879e-01 -9.59933341e-01
-8.92079771e-01 1.10075426e+00 4.44938391e-01 -4.81243581e-02
1.13964117e+00 -5.08685887e-01 5.28206944e-01 4.76105601e-01
3.44587356e-01 -1.26216483e+00 3.47710758e-01 7.52441764e-01
8.39162648e-01 -1.18677115e+00 -8.14510435e-02 -3.84388357e-01
-1.04447281e+00 1.24153066e+00 7.07894325e-01 3.43758166e-02
4.67728943e-01 1.99444905e-01 1.31066493e-03 4.62474108e-01
-7.01372683e-01 -2.48474568e-01 3.08928162e-01 7.45069504e-01
3.23257834e-01 9.56714749e-02 -3.25350314e-01 9.38679338e-01
-5.83234103e-03 -2.62675166e-01 5.25002360e-01 7.46241748e-01
-4.21107918e-01 -1.19998085e+00 -4.52389240e-01 2.80853808e-01
-3.21868330e-01 -4.69722420e-01 -2.35405728e-01 9.14692819e-01
3.19745988e-01 8.97611439e-01 1.74369607e-02 -2.49971524e-01
2.98571616e-01 3.21676970e-01 9.10573676e-02 -5.24755538e-01
-4.59892571e-01 6.67870045e-02 7.98105374e-02 8.41086432e-02
-8.92762840e-02 -4.59759355e-01 -8.92464042e-01 -8.40872750e-02
-2.81686425e-01 5.86225390e-02 5.98664165e-01 9.12829697e-01
5.66201061e-02 5.96839845e-01 5.91542840e-01 -3.50808591e-01
-7.17446387e-01 -1.12668061e+00 -8.08640122e-01 5.02084315e-01
-6.36822311e-04 -6.50601923e-01 -4.54565942e-01 -1.73079129e-02] | [11.895709037780762, 2.198019027709961] |
683b89b3-c133-4db8-89e6-57aa4b9fb682 | open-vocabulary-detr-with-conditional | 2203.11876 | null | https://arxiv.org/abs/2203.11876v2 | https://arxiv.org/pdf/2203.11876v2.pdf | Open-Vocabulary DETR with Conditional Matching | Open-vocabulary object detection, which is concerned with the problem of detecting novel objects guided by natural language, has gained increasing attention from the community. Ideally, we would like to extend an open-vocabulary detector such that it can produce bounding box predictions based on user inputs in form of either natural language or exemplar image. This offers great flexibility and user experience for human-computer interaction. To this end, we propose a novel open-vocabulary detector based on DETR -- hence the name OV-DETR -- which, once trained, can detect any object given its class name or an exemplar image. The biggest challenge of turning DETR into an open-vocabulary detector is that it is impossible to calculate the classification cost matrix of novel classes without access to their labeled images. To overcome this challenge, we formulate the learning objective as a binary matching one between input queries (class name or exemplar image) and the corresponding objects, which learns useful correspondence to generalize to unseen queries during testing. For training, we choose to condition the Transformer decoder on the input embeddings obtained from a pre-trained vision-language model like CLIP, in order to enable matching for both text and image queries. With extensive experiments on LVIS and COCO datasets, we demonstrate that our OV-DETR -- the first end-to-end Transformer-based open-vocabulary detector -- achieves non-trivial improvements over current state of the arts. | ['Chen Change Loy', 'Chen Huang', 'Kaiyang Zhou', 'Wei Li', 'Yuhang Zang'] | 2022-03-22 | null | null | null | null | ['open-vocabulary-object-detection'] | ['computer-vision'] | [ 3.75289649e-01 1.04024813e-01 5.67640513e-02 -3.80457252e-01
-1.02574134e+00 -6.23671710e-01 6.20035768e-01 1.53157249e-01
-5.13090789e-01 2.54103094e-01 -2.26406828e-01 -1.54493898e-01
3.38050544e-01 -5.93395293e-01 -1.01529908e+00 -3.37819815e-01
1.30877405e-01 5.84881604e-01 4.78122830e-01 -6.95767552e-02
-3.91467661e-02 2.66963750e-01 -1.75585151e+00 4.60365862e-01
5.85651040e-01 1.31155121e+00 5.66913128e-01 5.32582581e-01
-6.51514009e-02 4.35743719e-01 -2.58265793e-01 -5.52607656e-01
4.88771021e-01 -6.12673536e-02 -5.24047613e-01 3.81455719e-01
9.34545636e-01 -3.17394614e-01 -4.14564937e-01 1.10535502e+00
3.59341621e-01 1.58937082e-01 1.03014338e+00 -1.09820664e+00
-1.03416348e+00 3.48176330e-01 -3.71093422e-01 3.15507382e-01
3.13753515e-01 5.04985213e-01 1.18421340e+00 -1.64428961e+00
8.77964377e-01 1.15958607e+00 3.78456086e-01 7.13284075e-01
-1.43763340e+00 -5.61930776e-01 2.97557563e-01 1.80169702e-01
-1.91124678e+00 -4.40892428e-01 4.68529999e-01 -6.23278022e-01
8.45044374e-01 1.89495206e-01 3.71452302e-01 1.12470078e+00
-1.01969935e-01 1.11755085e+00 5.90517282e-01 -4.96813685e-01
2.11346433e-01 7.22738206e-01 -1.91438990e-03 7.67245948e-01
1.67605892e-01 7.87981041e-03 -2.43584350e-01 8.54333788e-02
4.81945723e-01 2.21616462e-01 -3.75072837e-01 -8.77341688e-01
-1.21911514e+00 8.70340824e-01 9.18322325e-01 1.49766505e-01
-2.10369736e-01 -6.36358261e-02 3.24950159e-01 3.27851355e-01
5.32388806e-01 4.40409213e-01 -4.05682832e-01 4.17214870e-01
-8.83618593e-01 1.51917368e-01 5.34140468e-01 1.34534669e+00
7.22807646e-01 -2.53188074e-01 -4.34392005e-01 7.78797567e-01
3.64700615e-01 7.30021060e-01 4.37680185e-01 -2.05375761e-01
4.64877039e-01 6.54443622e-01 -4.64895070e-02 -6.23486161e-01
-3.76249552e-02 -6.66223884e-01 -6.18085623e-01 -2.05124449e-02
1.92050129e-01 3.00798893e-01 -1.09122419e+00 1.61572015e+00
3.48643661e-01 1.24448262e-01 2.26039559e-01 9.48806822e-01
8.23029637e-01 7.26841629e-01 -1.04020230e-01 -2.40984187e-01
1.55625498e+00 -9.75219488e-01 -2.61145085e-01 -4.21660155e-01
6.95580304e-01 -5.15767992e-01 1.45368171e+00 1.64279014e-01
-7.91332245e-01 -7.74952829e-01 -9.84608293e-01 -2.37749696e-01
-6.11698925e-01 1.30148679e-01 -9.01365504e-02 3.43991071e-01
-8.66673708e-01 2.10338477e-02 -3.87683421e-01 -6.30050361e-01
5.58470607e-01 2.55555332e-01 -3.57730836e-01 -3.01274061e-01
-7.91619599e-01 7.88924277e-01 5.71355760e-01 -3.01322401e-01
-1.05888069e+00 -6.73863769e-01 -1.07821798e+00 2.05245867e-01
7.43303955e-01 -7.62559116e-01 1.37608278e+00 -9.70897913e-01
-7.25281656e-01 1.18950117e+00 -1.98059678e-01 -6.63998783e-01
4.48798209e-01 3.59970509e-05 -3.64324510e-01 6.52201921e-02
4.24031079e-01 1.15471005e+00 1.28014791e+00 -1.17462015e+00
-8.97016168e-01 -4.87613648e-01 6.23463169e-02 1.57099038e-01
-5.67714751e-01 -1.03105098e-01 -7.41793931e-01 -7.08131373e-01
4.86483090e-02 -9.89766598e-01 -5.26863001e-02 4.64239448e-01
-3.81662995e-01 -5.66642880e-01 9.79201138e-01 -2.72494167e-01
8.83738577e-01 -2.52225041e+00 -8.24110880e-02 -1.36422347e-02
3.80185008e-01 3.52909148e-01 -1.47135541e-01 8.46564993e-02
5.42107411e-02 -1.48218483e-01 -2.24492535e-01 -3.06986004e-01
-2.08045766e-02 1.33474022e-01 -7.73321807e-01 3.96480531e-01
6.80870295e-01 1.07343280e+00 -9.75470006e-01 -5.94961286e-01
1.45708203e-01 2.46179640e-01 -5.36337614e-01 2.81286597e-01
-6.88348532e-01 1.60186291e-01 -3.88796508e-01 5.27312696e-01
5.46831191e-01 -4.89913583e-01 -3.10503542e-01 -1.01398155e-01
7.79449716e-02 -2.39173487e-01 -1.17035913e+00 1.63862658e+00
-4.78638113e-01 8.57626975e-01 -3.12664926e-01 -9.02719080e-01
9.44967985e-01 1.47466436e-01 -1.81503296e-02 -5.92998564e-01
8.66742805e-02 2.56280124e-01 -1.77173316e-01 -5.29269338e-01
3.88655245e-01 -6.09792992e-02 -2.13965565e-01 1.48953512e-01
3.50552469e-01 -8.11904110e-03 3.02456409e-01 3.92693907e-01
9.68298316e-01 -1.25560641e-01 3.55290532e-01 -1.05119474e-01
6.66894495e-01 5.10697216e-02 1.78824425e-01 1.02564752e+00
-7.36333802e-02 7.13643789e-01 1.40670344e-01 -4.70806539e-01
-9.77797687e-01 -1.35315192e+00 -4.00551051e-01 1.29409766e+00
1.63352504e-01 -2.11331576e-01 -5.44588327e-01 -9.23840165e-01
1.49390578e-01 6.81330979e-01 -6.30755484e-01 -1.57699779e-01
-3.42591703e-01 1.80771425e-02 1.87970743e-01 5.29467583e-01
1.75790742e-01 -1.17086053e+00 -7.24621236e-01 8.67407098e-02
-5.66808060e-02 -1.36768806e+00 -9.04189825e-01 3.20112586e-01
-5.51436543e-01 -8.74187410e-01 -8.60469639e-01 -1.35197651e+00
8.01382005e-01 4.26924318e-01 1.04837370e+00 -2.72216916e-01
-6.95830584e-01 6.30775154e-01 -4.25966948e-01 -6.11781716e-01
-3.38997632e-01 -7.86244795e-02 1.95384920e-01 6.34112179e-01
4.98852879e-01 -9.05009285e-02 -5.83320439e-01 2.42232159e-01
-1.00271177e+00 -4.00057770e-02 6.58635259e-01 8.37874353e-01
9.31202531e-01 -3.92961621e-01 4.60938454e-01 -5.85132718e-01
3.89750689e-01 -3.40913832e-01 -6.81638896e-01 4.85561371e-01
-4.48554486e-01 2.84354538e-01 6.28424585e-01 -8.68069291e-01
-4.14432198e-01 4.65077370e-01 1.82800084e-01 -9.61542130e-01
-4.98421565e-02 2.30483159e-01 -1.25861883e-01 -8.57102647e-02
9.38316822e-01 7.25405395e-01 -2.49478921e-01 -2.92166144e-01
8.33759248e-01 1.03391254e+00 8.63946438e-01 -1.98782563e-01
9.37635660e-01 4.80242789e-01 -3.98786962e-01 -1.04581583e+00
-1.08028495e+00 -9.87110853e-01 -5.68022847e-01 -1.46588504e-01
9.01107550e-01 -1.24478137e+00 -4.51710403e-01 -1.66573688e-01
-1.24949503e+00 6.27048761e-02 -5.99291980e-01 2.21285388e-01
-5.43736398e-01 6.98488280e-02 2.72186492e-02 -7.75116086e-01
-3.32931101e-01 -1.20491230e+00 1.29872823e+00 1.31953910e-01
-2.44432781e-03 -6.10725701e-01 -2.37970918e-01 2.64552742e-01
1.82743356e-01 -1.31487936e-01 6.63672268e-01 -1.12363529e+00
-8.67321134e-01 -4.96743858e-01 -5.17695010e-01 4.63430911e-01
-2.68968195e-01 -5.43296337e-01 -1.01304853e+00 -5.08320928e-01
2.02903785e-02 -7.55436242e-01 9.88373339e-01 1.71666890e-02
1.14382625e+00 -1.83984712e-01 -5.75741410e-01 4.76520538e-01
1.41858196e+00 -1.04309611e-01 2.41914123e-01 5.53008635e-03
5.96924901e-01 3.28887582e-01 6.97234988e-01 3.30173761e-01
2.41879404e-01 8.01496148e-01 3.57443571e-01 8.57238546e-02
-1.23976834e-01 -4.57674623e-01 2.40340814e-01 2.23709404e-01
6.39754772e-01 -3.57613891e-01 -8.42557251e-01 9.15222585e-01
-1.68873477e+00 -7.04604566e-01 1.11968048e-01 2.26573920e+00
6.76515043e-01 3.54029387e-01 2.14271732e-02 -2.63414770e-01
6.63069904e-01 -8.44819099e-02 -9.14381683e-01 -4.16809656e-02
1.69989336e-02 1.28024697e-01 2.53820688e-01 1.08539298e-01
-1.25751734e+00 1.07969475e+00 4.73081398e+00 9.11209166e-01
-1.21561265e+00 3.32120538e-01 4.41466928e-01 -2.25640699e-01
6.80289939e-02 -1.40522838e-01 -1.18819904e+00 2.00081542e-01
6.28139257e-01 -2.23884508e-01 2.04145402e-01 1.09404290e+00
-9.77787524e-02 1.81116626e-01 -1.69906282e+00 1.29966497e+00
3.94878894e-01 -1.26724172e+00 4.72300202e-01 -1.17524333e-01
6.15416229e-01 2.24167109e-01 3.00732136e-01 7.83768952e-01
-1.06579944e-01 -5.98630428e-01 8.41731548e-01 3.73019695e-01
1.09399116e+00 -2.47218996e-01 3.06347430e-01 6.57025158e-01
-1.21775448e+00 -2.75455385e-01 -5.56141138e-01 1.62358642e-01
-1.34308398e-01 1.34632543e-01 -1.20718145e+00 9.90695208e-02
6.50046289e-01 5.56628168e-01 -6.25391424e-01 1.06326342e+00
-4.03758176e-02 3.99266839e-01 -3.22922409e-01 -1.94851473e-01
3.65389287e-01 2.69804746e-01 6.40604913e-01 1.18973422e+00
6.51798025e-02 -2.61530140e-03 6.38218939e-01 1.04916012e+00
-3.64288688e-01 2.95387626e-01 -9.82417643e-01 1.23048469e-01
2.78808713e-01 1.00268781e+00 -6.18160367e-01 -5.30351400e-01
-6.71784401e-01 1.17389011e+00 5.72336733e-01 2.68315375e-01
-7.35530138e-01 -3.01932663e-01 4.95246440e-01 3.17579031e-01
8.84673417e-01 1.65117010e-01 6.91815168e-02 -1.17595470e+00
4.92848843e-01 -6.66413307e-01 3.81719917e-01 -8.87212515e-01
-1.29918587e+00 7.22434759e-01 -1.70727953e-01 -1.43994915e+00
-1.36450365e-01 -7.38149941e-01 -1.82572678e-01 6.83746994e-01
-1.30612195e+00 -1.24187529e+00 -1.68623850e-01 7.22911000e-01
1.16942465e+00 -2.24263951e-01 5.97395718e-01 2.17303410e-01
-3.20656806e-01 8.95984411e-01 2.11659044e-01 2.63220638e-01
6.85665727e-01 -1.07060242e+00 5.06647944e-01 8.44706655e-01
8.55560422e-01 3.94588172e-01 7.20830202e-01 -4.73727971e-01
-1.34282982e+00 -1.64553952e+00 9.08096373e-01 -7.93259919e-01
6.28761828e-01 -8.47503364e-01 -1.01155210e+00 7.34405100e-01
-1.58127785e-01 7.94336259e-01 2.50751823e-01 -2.49227807e-01
-6.14363909e-01 -1.87104851e-01 -9.81335819e-01 6.61943674e-01
1.12756968e+00 -7.02567279e-01 -7.49435961e-01 7.16132104e-01
1.16410697e+00 -2.87428021e-01 -4.30661798e-01 4.25207585e-01
3.42912823e-01 -5.50889313e-01 9.98529017e-01 -7.80442536e-01
1.99387744e-01 -3.78357261e-01 -3.87270182e-01 -9.61214185e-01
-3.24775785e-01 -2.78389603e-01 -1.40626416e-01 9.26877320e-01
5.26507735e-01 -4.06634867e-01 5.73636174e-01 3.30702513e-01
-2.72818413e-02 -8.62548590e-01 -8.82912457e-01 -1.10408449e+00
-2.30115995e-01 -6.56289637e-01 1.61448553e-01 5.38357735e-01
-1.92132846e-01 7.39484489e-01 -1.42354295e-01 4.84699965e-01
5.12511909e-01 1.59287155e-01 9.77919757e-01 -1.18473017e+00
-2.66309053e-01 -2.01177150e-01 -8.46653759e-01 -1.52609956e+00
9.69950408e-02 -1.08891952e+00 3.55919868e-01 -1.23997724e+00
4.03146774e-01 -2.24901795e-01 -2.71628141e-01 3.21581900e-01
-9.62351039e-02 5.36292970e-01 4.18827236e-01 2.96884567e-01
-1.17867482e+00 6.88925624e-01 1.09322238e+00 -6.52022064e-01
-2.53770888e-01 2.50364421e-03 -6.80688858e-01 5.91361105e-01
1.38301939e-01 -6.83386266e-01 -4.62106943e-01 -3.95322889e-01
2.89183352e-02 8.24434385e-02 6.76144660e-01 -1.04131448e+00
3.76471817e-01 2.66728908e-01 2.13185430e-01 -6.61176562e-01
3.27559471e-01 -9.52370048e-01 -4.29292738e-01 3.78186673e-01
-5.80204964e-01 -3.79792809e-01 1.31133258e-01 9.92609620e-01
-1.23658240e-01 -2.61699706e-01 6.76137030e-01 -3.85324694e-02
-1.01821971e+00 5.59906721e-01 -1.56811699e-01 3.90369982e-01
1.34482479e+00 -3.69823545e-01 -2.87199602e-03 -8.91133547e-02
-9.47226822e-01 4.83992308e-01 3.67838532e-01 8.00449491e-01
8.96908104e-01 -1.19933963e+00 -8.74875188e-01 4.37621593e-01
1.06783497e+00 1.90935493e-01 4.79632132e-02 4.99928325e-01
-1.15202822e-01 5.97557127e-01 3.21942180e-01 -9.89195585e-01
-1.24408090e+00 1.16296387e+00 2.86507368e-01 -1.22261725e-01
-7.63624132e-01 1.09729624e+00 8.64750326e-01 -3.89871776e-01
5.04785299e-01 -5.07898867e-01 4.72808555e-02 -1.83199316e-01
6.71072304e-01 -3.88593733e-01 -1.21792248e-02 -6.75497770e-01
-3.88824731e-01 3.95448774e-01 -4.38537925e-01 7.97794983e-02
8.58672023e-01 -1.34337664e-01 3.26549411e-01 6.38678432e-01
1.40864360e+00 -4.72624123e-01 -1.19163954e+00 -9.85155582e-01
-5.24621159e-02 -3.60417724e-01 -6.35463968e-02 -5.16873121e-01
-5.94181895e-01 8.62831354e-01 1.07835233e+00 1.27678096e-01
8.88036847e-01 5.48609316e-01 6.58035636e-01 8.63802373e-01
4.86605167e-01 -6.65574372e-01 3.10658991e-01 4.51387048e-01
1.10434401e+00 -1.61685359e+00 -4.05860811e-01 -2.01767504e-01
-5.48565388e-01 9.26354289e-01 7.81385779e-01 -8.42852145e-02
6.10677719e-01 -2.87536889e-01 -5.07638864e-02 -2.46180922e-01
-8.05930972e-01 -5.23631692e-01 6.72655404e-01 5.84522903e-01
-9.33483765e-02 6.88578412e-02 2.42579758e-01 4.31863308e-01
-9.30022821e-03 -2.33154166e-02 1.59833640e-01 6.40553117e-01
-7.59048998e-01 -6.25945389e-01 -4.46869314e-01 7.84441769e-01
-3.53238173e-02 -2.17430651e-01 -2.65161484e-01 5.69770098e-01
2.74118900e-01 7.66598880e-01 2.48055547e-01 -2.62652427e-01
5.46001136e-01 1.42551765e-01 3.27599764e-01 -1.12772620e+00
-2.22977698e-01 -2.21160814e-01 -4.03437465e-01 -3.09862345e-01
9.18502584e-02 -6.43018544e-01 -9.28582370e-01 5.13996184e-01
-6.39076829e-01 -9.19759497e-02 5.07141113e-01 1.04777968e+00
3.17643166e-01 3.21989000e-01 5.89744329e-01 -7.74283290e-01
-9.94624555e-01 -9.73448455e-01 -4.26415622e-01 5.21930575e-01
6.01907969e-01 -6.58449233e-01 -1.63373753e-01 2.93389052e-01] | [9.726065635681152, 1.536392331123352] |
845aa6a3-3589-4d26-b5fb-cb4666197d90 | harmonious-feature-learning-for-interactive | null | null | http://openaccess.thecvf.com//content/CVPR2023/html/Lin_Harmonious_Feature_Learning_for_Interactive_Hand-Object_Pose_Estimation_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Lin_Harmonious_Feature_Learning_for_Interactive_Hand-Object_Pose_Estimation_CVPR_2023_paper.pdf | Harmonious Feature Learning for Interactive Hand-Object Pose Estimation | Joint hand and object pose estimation from a single image is extremely challenging as serious occlusion often occurs when the hand and object interact. Existing approaches typically first extract coarse hand and object features from a single backbone, then further enhance them with reference to each other via interaction modules. However, these works usually ignore that the hand and object are competitive in feature learning, since the backbone takes both of them as foreground and they are usually mutually occluded. In this paper, we propose a novel Harmonious Feature Learning Network (HFL-Net). HFL-Net introduces a new framework that combines the advantages of single- and double-stream backbones: it shares the parameters of the low- and high-level convolutional layers of a common ResNet-50 model for the hand and object, leaving the middle-level layers unshared. This strategy enables the hand and the object to be extracted as the sole targets by the middle-level layers, avoiding their competition in feature learning. The shared high-level layers also force their features to be harmonious, thereby facilitating their mutual feature enhancement. In particular, we propose to enhance the feature of the hand via concatenation with the feature in the same location from the object stream. A subsequent self-attention layer is adopted to deeply fuse the concatenated feature. Experimental results show that our proposed approach consistently outperforms state-of-the-art methods on the popular HO3D and Dex-YCB databases. Notably, the performance of our model on hand pose estimation even surpasses that of existing works that only perform the single-hand pose estimation task. Code is available at https://github.com/lzfff12/HFL-Net. | ['Shaoli Huang', 'Zengsheng Kuang', 'Huan Yao', 'Changxing Ding', 'Zhifeng Lin'] | 2023-01-01 | null | null | null | cvpr-2023-1 | ['hand-pose-estimation', 'hand-object-pose'] | ['computer-vision', 'computer-vision'] | [-3.62552732e-01 -2.79299527e-01 -1.36842981e-01 -1.55269429e-01
-5.45011342e-01 -3.36586982e-01 4.43402231e-01 -3.91947627e-01
-4.18290436e-01 3.83435100e-01 2.74141759e-01 4.18697000e-01
4.09701206e-02 -5.44702590e-01 -7.54521906e-01 -9.19252455e-01
2.64046490e-01 3.32919151e-01 5.46137393e-01 -3.05810589e-02
-1.11730054e-01 6.17627263e-01 -1.75629795e+00 2.52360165e-01
5.70674539e-01 1.22100317e+00 6.13247871e-01 4.11932558e-01
1.90223023e-01 6.63663089e-01 -4.07524496e-01 -2.64576852e-01
4.21594501e-01 2.16961149e-02 -8.28964055e-01 1.76972851e-01
6.29541755e-01 -8.90720963e-01 -9.00064528e-01 8.03371012e-01
9.90417123e-01 -4.61435271e-03 3.85637313e-01 -1.29927242e+00
-3.41272354e-01 3.92244995e-01 -9.37084734e-01 -1.35826468e-01
1.68011516e-01 4.77568239e-01 1.04630637e+00 -1.13757825e+00
6.52062297e-01 1.36594713e+00 3.94214898e-01 4.16030079e-01
-9.90091026e-01 -8.47926915e-01 6.45315826e-01 2.69776911e-01
-1.59777510e+00 -3.02149296e-01 9.64008570e-01 -3.30195874e-01
8.47989202e-01 3.84106375e-02 9.68972743e-01 1.11283100e+00
-1.74983680e-01 1.45914125e+00 7.95889735e-01 -1.10232584e-01
-3.37547749e-01 -9.36474577e-02 1.15438364e-01 5.87821186e-01
5.94741516e-02 3.32396887e-02 -7.08014846e-01 1.84762716e-01
9.74414766e-01 3.59399408e-01 -5.19719064e-01 -5.94431520e-01
-1.28098488e+00 3.64843577e-01 7.07937300e-01 4.43627477e-01
-6.99145734e-01 1.75212324e-01 1.71497792e-01 -2.49138996e-02
2.11958513e-01 -2.14545980e-01 -6.62589788e-01 8.43711197e-02
-8.72205675e-01 4.99191314e-01 5.71599543e-01 1.28057790e+00
6.65970445e-01 -3.38416517e-01 -5.68327427e-01 5.46171963e-01
5.36813140e-01 3.23588580e-01 1.42246187e-01 -5.67677677e-01
6.14123762e-01 5.54485559e-01 2.22841308e-01 -8.19450736e-01
-4.06717956e-01 -8.58860195e-01 -6.45897508e-01 3.25708002e-01
4.92533356e-01 -4.98732515e-02 -8.96834970e-01 1.67638171e+00
6.73105597e-01 1.04293160e-01 -3.98888201e-01 1.18662870e+00
1.00342190e+00 3.50812793e-01 1.13571763e-01 1.45224392e-01
1.39852870e+00 -1.43504226e+00 -5.66647887e-01 -5.77039272e-02
2.12649256e-01 -8.53844821e-01 1.08017755e+00 3.26807857e-01
-1.19998097e+00 -1.03534186e+00 -8.59037876e-01 -3.85459810e-01
-1.70524716e-01 4.61118996e-01 5.88210881e-01 4.86167297e-02
-6.84523940e-01 5.52162886e-01 -9.73355234e-01 -3.13848965e-02
7.24621117e-01 5.22099257e-01 -4.46249485e-01 1.29003720e-02
-8.11682701e-01 7.63858795e-01 3.28258991e-01 4.43431646e-01
-7.44265795e-01 -7.22610891e-01 -7.53161252e-01 1.69596169e-02
5.11640310e-01 -7.85121024e-01 1.15210283e+00 -7.60387480e-01
-1.42670977e+00 5.54387808e-01 -1.11320876e-01 2.62315750e-01
8.61198604e-01 -7.55745292e-01 3.76756564e-02 5.61691448e-02
-1.02916569e-03 8.99802983e-01 1.13290668e+00 -1.30068207e+00
-9.33727026e-01 -6.51664317e-01 1.19638443e-01 3.55707169e-01
-3.83670628e-01 -9.82087851e-03 -1.04303408e+00 -8.79222929e-01
1.41085133e-01 -8.00956726e-01 8.77546892e-02 2.93554813e-01
-5.84252894e-01 -5.50389767e-01 1.16041636e+00 -6.86867833e-01
1.10548425e+00 -2.22835040e+00 5.02324224e-01 3.94648537e-02
3.56639385e-01 4.14227605e-01 -3.78218889e-01 9.94466841e-02
-8.12684745e-02 -3.47122550e-01 1.25890851e-01 -6.22309387e-01
-3.13766040e-02 -9.94467735e-02 -2.83576604e-02 6.28427863e-01
3.69097799e-01 1.11172116e+00 -8.28237832e-01 -5.93049407e-01
4.15438533e-01 1.05013740e+00 -6.29758775e-01 3.58575970e-01
-1.85660034e-01 6.84716284e-01 -5.48013210e-01 6.59136117e-01
7.83623278e-01 -2.31004223e-01 -5.19970506e-02 -6.35500371e-01
-2.01027274e-01 2.88090587e-01 -1.54097199e+00 1.90785682e+00
-3.85032922e-01 2.03869402e-01 1.41639173e-01 -4.65308487e-01
4.93571311e-01 4.64248270e-01 5.58330536e-01 -4.37766552e-01
3.54777217e-01 1.59152493e-01 1.05137341e-01 -4.94004190e-01
1.21080108e-01 2.95534581e-01 3.18077505e-01 3.20844173e-01
2.51872927e-01 5.84277976e-03 3.94185632e-02 -8.11344478e-03
5.11792839e-01 5.61599135e-01 1.03166260e-01 4.11246456e-02
5.81769824e-01 -6.65528595e-01 3.55590582e-01 5.45587957e-01
-1.51738077e-01 8.28850329e-01 3.03337097e-01 -2.94023126e-01
-8.79255891e-01 -8.98417115e-01 -1.02162220e-01 1.21861458e+00
3.27383786e-01 -4.46861714e-01 -6.78828835e-01 -8.81563246e-01
3.81853670e-01 1.37642816e-01 -7.02487051e-01 1.28478810e-01
-6.72402740e-01 -2.00172469e-01 7.83664733e-02 1.05207491e+00
5.70426583e-01 -1.27827740e+00 -6.50085986e-01 3.79314691e-01
-1.47603720e-01 -1.00095105e+00 -8.29915166e-01 7.13761523e-02
-5.35048127e-01 -1.11920893e+00 -1.12404203e+00 -8.37085783e-01
4.57002670e-01 3.33739907e-01 6.89946175e-01 3.16577762e-01
-3.45374376e-01 3.09407920e-01 -2.88664937e-01 -3.62897009e-01
3.01106840e-01 5.15489221e-01 -6.51265904e-02 2.84642786e-01
2.15071961e-01 -8.39745998e-01 -9.63097513e-01 4.21606362e-01
-6.43886387e-01 1.48451090e-01 6.79494381e-01 8.38854074e-01
5.57385147e-01 -2.15679616e-01 3.91930431e-01 -2.32478648e-01
6.61853775e-02 -9.68074352e-02 -4.02380377e-01 1.95388973e-01
-8.64320248e-02 -1.44835442e-01 1.69431314e-01 -6.00299776e-01
-1.12080133e+00 5.98098516e-01 -2.84219623e-01 -6.22437835e-01
-1.45441085e-01 -1.30250975e-01 -7.05268681e-01 -6.61513880e-02
8.98036882e-02 1.50887981e-01 -9.31015015e-02 -8.07800829e-01
3.78300965e-01 7.90703535e-01 5.74716151e-01 -5.16099811e-01
8.87849927e-01 5.87909639e-01 -2.99598306e-01 -6.21662319e-01
-9.33420777e-01 -5.46288133e-01 -1.10825992e+00 -2.92164564e-01
7.07093894e-01 -9.09880817e-01 -9.97099876e-01 1.10665393e+00
-1.42899597e+00 -1.92249030e-01 -3.43032479e-01 5.95945477e-01
-4.50668156e-01 2.27271721e-01 -5.97998798e-01 -5.78239262e-01
-4.64200318e-01 -1.36159360e+00 1.51571655e+00 3.76091033e-01
-6.14162832e-02 -4.47894424e-01 -3.62259626e-01 2.01778367e-01
2.36170992e-01 -4.09443416e-02 4.67933536e-01 -4.13259298e-01
-6.03493392e-01 -1.94062099e-01 -4.56238538e-01 3.70376855e-01
3.35712224e-01 -7.89274648e-02 -1.24361455e+00 -6.14200711e-01
-1.66960344e-01 -3.79715264e-01 8.94830227e-01 4.95528251e-01
1.26824677e+00 4.39773090e-02 -4.30283487e-01 6.93470836e-01
1.00367856e+00 -1.80557922e-01 4.70328748e-01 1.83025941e-01
1.18864989e+00 7.05290914e-01 4.61162925e-01 5.51376641e-01
4.60089087e-01 8.82347882e-01 5.29111922e-01 -3.45674396e-01
-5.21807492e-01 -8.35263655e-02 1.91110417e-01 5.15784264e-01
-5.98211050e-01 -4.29647462e-03 -5.09221256e-01 4.13380295e-01
-1.83664596e+00 -7.32911646e-01 -5.80585264e-02 1.97215235e+00
8.79386544e-01 1.37607828e-02 5.04856050e-01 2.36750737e-01
6.75609529e-01 3.16003293e-01 -6.77999616e-01 6.12997890e-01
-1.07372835e-01 2.92632341e-01 1.28931031e-02 3.10028762e-01
-1.36904299e+00 1.02472484e+00 4.65794420e+00 8.04893434e-01
-1.14022183e+00 2.42433399e-01 1.16972812e-01 -4.29843277e-01
1.72914267e-01 -2.44889319e-01 -1.06245792e+00 3.32462132e-01
-8.53120759e-02 3.43009472e-01 2.81041831e-01 8.03011179e-01
-8.49011689e-02 1.03834182e-01 -1.35809791e+00 9.31695282e-01
-6.71771839e-02 -7.30098844e-01 -8.56241658e-02 1.22552775e-01
5.04243016e-01 8.93605035e-03 9.01896656e-02 1.00052804e-01
-2.47517690e-01 -8.40669930e-01 1.07903183e+00 5.90194285e-01
6.85966611e-01 -7.75067449e-01 6.51857197e-01 1.78520188e-01
-1.74156153e+00 -9.66437235e-02 2.78984290e-02 6.26553968e-02
1.54887959e-01 2.22531602e-01 -2.09351540e-01 6.35703504e-01
9.09586549e-01 8.22700560e-01 -4.59040672e-01 1.01879072e+00
-4.53334719e-01 1.20968439e-01 -3.89851063e-01 4.43477809e-01
2.10115060e-01 3.69912922e-01 6.53838336e-01 1.15728116e+00
3.10810637e-02 -2.15688832e-02 4.65708673e-01 7.97929168e-01
-4.82198149e-02 9.07323658e-02 -1.30095378e-01 2.67315477e-01
3.42678964e-01 1.26252079e+00 -4.90773678e-01 -4.43039685e-01
-6.70807302e-01 1.19472456e+00 3.59048635e-01 3.14545572e-01
-8.64200413e-01 -5.17569602e-01 6.95856988e-01 1.88816205e-01
8.15285265e-01 -1.38164729e-01 3.56204435e-03 -1.18953228e+00
4.26537633e-01 -8.32565546e-01 2.44763508e-01 -4.85093623e-01
-1.19919503e+00 6.89897537e-01 -2.16987789e-01 -1.30750680e+00
6.88065663e-02 -6.54974043e-01 -3.17436129e-01 1.11584830e+00
-1.61406970e+00 -1.67864263e+00 -6.39039159e-01 1.04160643e+00
6.03815377e-01 1.31638154e-01 4.53945130e-01 4.01933640e-01
-5.75980425e-01 7.95941174e-01 -3.70350629e-01 3.85049164e-01
6.61287904e-01 -1.03903484e+00 2.73121864e-01 5.89588523e-01
9.09874216e-02 5.65414488e-01 2.23709911e-01 -6.90865457e-01
-1.29672456e+00 -8.67424369e-01 7.02865899e-01 -3.94985020e-01
2.85163730e-01 -4.18874949e-01 -9.02265131e-01 6.17750943e-01
4.29968946e-02 4.15503114e-01 1.05503350e-01 -1.04099493e-02
-4.64990497e-01 -1.95421085e-01 -8.04326952e-01 4.63329136e-01
1.40534961e+00 -5.96559107e-01 -5.52617550e-01 2.76065707e-01
4.47894841e-01 -6.00581288e-01 -8.45124900e-01 4.80303437e-01
1.11538982e+00 -9.33064282e-01 1.12545741e+00 -5.41375458e-01
3.15046310e-01 -4.31452960e-01 -8.44141617e-02 -8.88426781e-01
-4.33410287e-01 -4.58707780e-01 -5.50991833e-01 1.25818229e+00
-9.80364904e-02 -4.21109945e-01 6.57973349e-01 3.08662057e-01
1.16776198e-01 -1.00423241e+00 -7.00554252e-01 -7.60027170e-01
-1.25533491e-01 -3.21576953e-01 7.47220397e-01 5.07794321e-01
-3.02217096e-01 2.79959470e-01 -3.89915735e-01 2.15012223e-01
6.82213128e-01 2.29679912e-01 1.01512253e+00 -1.29670143e+00
-3.94475132e-01 -5.44084966e-01 -2.45685667e-01 -1.34778154e+00
1.23809636e-01 -7.81400561e-01 1.59228276e-02 -1.30777931e+00
4.70185041e-01 -3.38231564e-01 -3.68876815e-01 7.95519829e-01
-3.64324480e-01 3.59944731e-01 5.56660950e-01 2.99915463e-01
-3.60032678e-01 7.67492771e-01 1.80203140e+00 -8.77695158e-02
-4.74835515e-01 1.57739744e-01 -5.02126932e-01 9.48012233e-01
5.16379654e-01 -4.05344278e-01 -1.30062819e-01 -4.09327745e-01
-4.55197006e-01 -2.79245406e-01 7.76780427e-01 -8.80858302e-01
3.56136709e-01 1.56629801e-01 7.14676678e-01 -9.65474129e-01
4.15702641e-01 -1.06296933e+00 7.91989788e-02 4.78216141e-01
-2.87365988e-02 -2.42619365e-01 9.49262157e-02 3.11317712e-01
-4.49617542e-02 2.75899041e-02 7.96214283e-01 4.82022054e-02
-5.49759507e-01 7.60996163e-01 2.18034059e-01 -3.00831467e-01
1.02887046e+00 -1.67494923e-01 3.33740674e-02 -2.14334399e-01
-7.61074126e-01 3.31252247e-01 2.38761440e-01 6.89502418e-01
5.16617060e-01 -1.20019245e+00 -8.28043461e-01 3.72529238e-01
-9.94794518e-02 4.84985888e-01 4.68601227e-01 1.16535592e+00
1.22236870e-02 2.92672843e-01 -3.15450162e-01 -7.44552255e-01
-1.31474948e+00 5.83403766e-01 4.17854130e-01 -1.65501699e-01
-9.53222036e-01 9.92920637e-01 5.69729209e-01 -2.12028354e-01
8.06365192e-01 -2.60402709e-01 -8.88400152e-02 4.15104121e-01
6.85200453e-01 4.57030624e-01 -1.02439284e-01 -9.00004566e-01
-4.58579361e-01 9.06025708e-01 -3.24619949e-01 1.26414850e-01
1.58448243e+00 4.40138318e-02 -1.37049183e-01 8.84987265e-02
1.32271707e+00 -2.13369937e-03 -1.73991168e+00 -6.15009129e-01
-4.64522421e-01 -5.81128418e-01 8.29858705e-02 -7.01612771e-01
-1.63100660e+00 1.03459573e+00 6.10862851e-01 -4.13641542e-01
1.18278205e+00 3.05226296e-01 7.29404509e-01 2.13400796e-01
2.76516855e-01 -9.61388707e-01 3.18372756e-01 3.29163641e-01
1.45149565e+00 -1.03943992e+00 -3.71089019e-02 -5.72438061e-01
-3.41980010e-01 1.01839316e+00 9.37257707e-01 -2.53331158e-02
7.00308681e-01 4.58255887e-01 -1.66331977e-01 -1.81346610e-01
-2.49384061e-01 -4.97862220e-01 5.07876933e-01 4.34672594e-01
3.56475264e-01 -1.04613505e-01 -7.26847798e-02 9.54686880e-01
-2.06032284e-02 9.86602008e-02 -3.80810142e-01 1.09565425e+00
-2.34836470e-02 -1.12857521e+00 -3.81906480e-01 3.74658018e-01
-2.30469853e-01 -6.38345629e-02 -1.44744545e-01 1.08274996e+00
5.29514551e-01 5.06333649e-01 1.82806998e-02 -5.07368028e-01
6.47379458e-01 -2.87397858e-02 7.95229793e-01 -4.37556148e-01
-8.69690537e-01 5.05626440e-01 -3.42577726e-01 -7.73635507e-01
-5.22149026e-01 -7.73274541e-01 -1.20650804e+00 -1.29986688e-01
-5.27262807e-01 -3.90576839e-01 2.93892711e-01 9.16371882e-01
3.52132976e-01 6.72703087e-01 5.09592116e-01 -1.64789724e+00
-6.73311114e-01 -1.11574566e+00 -7.27508962e-01 3.13061237e-01
4.49798197e-01 -1.19115043e+00 -3.82913812e-03 -4.22764905e-02] | [6.74315881729126, -0.7636508941650391] |
85b73227-6d5a-4648-88aa-6e44de1fe598 | improving-arabic-text-categorization-using | null | null | https://aclanthology.org/2020.wanlp-1.21 | https://aclanthology.org/2020.wanlp-1.21.pdf | Improving Arabic Text Categorization Using Transformer Training Diversification | Automatic categorization of short texts, such as news headlines and social media posts, has many applications ranging from content analysis to recommendation systems. In this paper, we use such text categorization i.e., labeling the social media posts to categories like ‘sports’, ‘politics’, ‘human-rights’ among others, to showcase the efficacy of models across different sources and varieties of Arabic. In doing so, we show that diversifying the training data, whether by using diverse training data for the specific task (an increase of 21% macro F1) or using diverse data to pre-train a BERT model (26% macro F1), leads to overall improvements in classification effectiveness. In our work, we also introduce two new Arabic text categorization datasets, where the first is composed of social media posts from a popular Arabic news channel that cover Twitter, Facebook, and YouTube, and the second is composed of tweets from popular Arabic accounts. The posts in the former are nearly exclusively authored in modern standard Arabic (MSA), while the tweets in the latter contain both MSA and dialectal Arabic. | ['Bernard J. Jansen', 'Joni Salminen', 'Jung Soon-Gyo', 'Kareem Darwish', 'Ahmed Abdelali', 'Shammur Absar Chowdhury'] | null | null | null | null | coling-wanlp-2020-12 | ['text-categorization'] | ['natural-language-processing'] | [-2.85842627e-01 1.56506434e-01 -2.10251063e-01 -2.62396872e-01
-4.52566713e-01 -7.78283358e-01 1.06320202e+00 8.29699397e-01
-6.40994310e-01 3.87403399e-01 6.66461587e-01 -4.54425573e-01
6.15942553e-02 -9.71372008e-01 -2.46107250e-01 -4.82806176e-01
4.38346043e-02 4.98589665e-01 3.12071383e-01 -9.66511846e-01
4.76734728e-01 1.12944528e-01 -1.54394233e+00 4.84467298e-01
1.07096720e+00 9.21032369e-01 -2.27335140e-01 2.71105438e-01
-3.76242548e-01 8.54112804e-01 -5.36293030e-01 -8.53801131e-01
-8.87649357e-02 -3.75821978e-01 -9.24470723e-01 2.39742309e-01
8.59522671e-02 -1.19640365e-01 -1.37645110e-01 7.49948800e-01
2.23898396e-01 -8.06764364e-02 8.60113204e-01 -9.65136588e-01
-5.02448440e-01 1.16921401e+00 -8.26138496e-01 -9.49274674e-02
3.34737182e-01 -3.58276308e-01 1.11440611e+00 -8.70637357e-01
8.44548762e-01 1.43452728e+00 7.14210570e-01 2.14534719e-02
-9.04523790e-01 -3.89881641e-01 1.65537104e-01 8.75599012e-02
-1.24110377e+00 -5.70199907e-01 4.23723608e-01 -6.32034183e-01
3.38032067e-01 3.74852598e-01 2.89653689e-01 9.36312139e-01
8.50886628e-02 7.35348403e-01 1.33625901e+00 -7.19922900e-01
5.89566603e-02 3.86546642e-01 6.29393041e-01 4.32505310e-01
6.07932471e-02 -7.05762088e-01 -3.77115637e-01 -2.27846056e-01
-7.16602057e-02 -2.15783283e-01 -6.94604442e-02 2.44391978e-01
-1.27982759e+00 1.19177115e+00 3.90269727e-01 5.29853284e-01
-3.05293232e-01 -5.35867155e-01 7.48614013e-01 6.17003798e-01
9.09737349e-01 5.79703271e-01 -3.45502377e-01 3.08482666e-02
-7.42939174e-01 2.19862267e-01 9.84668612e-01 5.88066280e-01
7.84401834e-01 -2.98828810e-01 1.12256698e-01 1.44434488e+00
4.56019372e-01 4.41889942e-01 9.68721032e-01 -4.43341672e-01
5.85704863e-01 8.77754569e-01 5.18146120e-02 -1.37367797e+00
-7.24236727e-01 -2.05223039e-01 -5.30360579e-01 -5.64388990e-01
8.58909905e-01 -4.86117661e-01 -7.77398527e-01 1.27509975e+00
3.34981859e-01 -7.43999898e-01 1.15279138e-01 7.21815348e-01
8.98696065e-01 9.11234498e-01 -1.09582864e-01 -2.31970936e-01
1.63911557e+00 -9.70005274e-01 -5.85037708e-01 -2.17976511e-01
8.31097364e-01 -1.09722722e+00 1.18039751e+00 3.30505908e-01
-6.54320478e-01 -2.13196799e-01 -8.98225844e-01 -6.88977018e-02
-8.19716036e-01 5.26367165e-02 1.78583413e-01 6.72700703e-01
-6.89446092e-01 3.27532470e-01 -4.79397565e-01 -6.78573787e-01
1.84322625e-01 4.67245430e-02 -4.03605044e-01 -1.03558309e-01
-1.33844423e+00 8.70494545e-01 2.77276278e-01 -5.23440719e-01
-3.92980605e-01 -1.60855398e-01 -6.76128566e-01 -1.67680830e-01
3.67596865e-01 2.49433473e-01 8.89082491e-01 -1.32425499e+00
-1.52786565e+00 1.05133057e+00 3.43954176e-01 -3.74927342e-01
4.08923060e-01 -1.00475103e-01 -5.98182082e-01 3.77216637e-02
2.41410419e-01 4.07173425e-01 7.51615703e-01 -1.07688332e+00
-9.23758328e-01 -5.01998961e-01 3.41361254e-01 -1.62586141e-02
-9.37963426e-01 4.93103772e-01 -2.95407504e-01 -8.66106808e-01
2.62892991e-01 -1.35734224e+00 1.19126514e-01 -6.67693377e-01
-4.90922838e-01 -3.05909157e-01 5.30118346e-01 -9.93341506e-01
1.60683084e+00 -2.05280781e+00 2.95793235e-01 5.46847880e-01
1.72667518e-01 -1.93637609e-01 1.54347479e-01 7.75106847e-01
3.76238912e-01 2.51486212e-01 -6.79802820e-02 -1.25892103e-01
4.83933687e-02 3.24562825e-02 -3.61159921e-01 5.06949067e-01
1.40725166e-01 4.26028967e-01 -7.73257613e-01 -4.48648483e-01
-3.79634917e-01 8.39765295e-02 -5.54200947e-01 -4.37873811e-01
-2.75326371e-01 3.10203105e-01 -3.19476128e-01 6.37587607e-01
3.05975795e-01 -2.94447899e-01 4.12225604e-01 -2.05741189e-02
-4.54449356e-01 5.15209019e-01 -8.71228635e-01 1.13508081e+00
-4.30284560e-01 7.72398531e-01 7.13920919e-03 -6.88642919e-01
7.51229167e-01 4.01007803e-03 4.63569582e-01 -5.40188909e-01
7.18653440e-01 4.16411638e-01 3.48185778e-01 -1.08264685e-01
9.07201290e-01 2.92140812e-01 -4.76849258e-01 9.69956100e-01
-7.29333311e-02 3.12149506e-02 6.54723108e-01 2.81413794e-01
5.42001843e-01 -3.05260062e-01 2.66294241e-01 -5.69899380e-01
5.44005394e-01 4.18816388e-01 -1.18343525e-01 4.75778788e-01
-4.11356450e-04 4.53600913e-01 7.76043892e-01 -2.16913387e-01
-8.33475649e-01 -4.08010840e-01 -3.96852940e-01 1.85247588e+00
1.59913041e-02 -8.32086146e-01 -8.39404643e-01 -8.77361417e-01
6.86487854e-02 4.87790257e-01 -6.21388376e-01 3.40358391e-02
-5.38438559e-01 -1.28513598e+00 5.91467798e-01 -7.25007579e-02
5.31586885e-01 -7.57487118e-01 -1.94072068e-01 5.94713129e-02
-6.02180839e-01 -9.20300186e-01 -3.05881798e-01 -3.50049101e-02
-3.38646948e-01 -9.82899487e-01 -8.41342628e-01 -7.28783250e-01
4.85870868e-01 2.89079368e-01 9.58529711e-01 1.52848333e-01
5.27250767e-01 9.22676846e-02 -1.09779656e+00 -6.21529758e-01
-8.12860131e-01 7.74797976e-01 1.70510247e-01 5.46152294e-01
2.97153473e-01 5.08595780e-02 -8.92802402e-02 6.26527369e-01
-9.45163846e-01 -4.11077105e-02 1.54333800e-01 7.16738999e-01
-2.57692719e-03 -2.59418309e-01 7.50680685e-01 -1.21972251e+00
5.86020708e-01 -1.02797830e+00 -4.33960557e-02 -7.74929002e-02
-5.90484500e-01 -2.84658492e-01 5.10042906e-01 -5.74317396e-01
-6.18945777e-01 -2.34315068e-01 -4.49626148e-01 6.07792258e-01
1.20625176e-01 1.25185430e+00 3.34713280e-01 1.00122385e-01
1.10462844e+00 1.47174271e-02 3.37097496e-01 -4.27330703e-01
1.97162285e-01 1.47754681e+00 -6.89617693e-02 -3.07053149e-01
5.41052699e-01 3.87420982e-01 -5.67253709e-01 -1.02720773e+00
-9.43253636e-01 -4.95449066e-01 -5.53767800e-01 -2.88186342e-01
6.68389440e-01 -8.31001341e-01 -3.41551960e-01 8.86782825e-01
-4.93129581e-01 -4.42168444e-01 2.18300611e-01 3.10227722e-01
-1.66416436e-01 2.85424829e-01 -9.54689085e-01 -2.75689036e-01
-8.96510705e-02 -1.09015751e+00 6.94349706e-01 -1.35702655e-01
-5.11986315e-01 -9.09346581e-01 -1.64299443e-01 3.89257342e-01
4.10364628e-01 3.02561402e-01 1.07803333e+00 -1.12238777e+00
4.19916481e-01 -3.04057539e-01 -1.58264801e-01 2.03077540e-01
4.60918844e-01 2.81848609e-01 -7.72225857e-01 -3.70994538e-01
-3.78171980e-01 -5.15436292e-01 6.81623220e-01 -5.16127087e-02
7.25323379e-01 -5.14615178e-01 -1.44762442e-01 -2.72765905e-01
8.59119236e-01 -4.90441248e-02 5.69283426e-01 8.93431962e-01
6.54437423e-01 9.95228291e-01 7.91032791e-01 4.87363160e-01
8.05881619e-01 6.96618676e-01 3.10563475e-01 6.49184585e-02
1.64369181e-01 1.11898214e-01 6.21066630e-01 1.17787409e+00
-2.99751014e-02 -2.36970529e-01 -1.32730484e+00 4.97745246e-01
-1.67114484e+00 -6.65764391e-01 -2.36343861e-01 2.03567147e+00
1.13902605e+00 6.48706406e-02 7.61232197e-01 5.23553371e-01
7.01496899e-01 6.01478154e-03 -3.80878374e-02 -3.94484997e-01
-2.99052954e-01 -1.23236008e-01 4.11588013e-01 5.48940539e-01
-1.29571807e+00 9.14232492e-01 5.56250238e+00 8.36350441e-01
-1.40578544e+00 2.11722791e-01 8.42596769e-01 2.46718988e-01
-3.85998338e-02 -2.97854632e-01 -7.40786076e-01 7.18159914e-01
1.27117074e+00 1.75510366e-02 1.57310188e-01 4.64661241e-01
-4.48304154e-02 -1.94599122e-01 -5.30682921e-01 5.21275401e-01
2.87767202e-01 -1.24684834e+00 2.11543605e-01 1.44244924e-01
6.74813867e-01 9.59525704e-02 -6.68343306e-02 5.11545122e-01
2.20353141e-01 -7.12227046e-01 1.24805880e+00 -6.63086697e-02
6.29880250e-01 -8.78329277e-01 8.61068606e-01 5.00313401e-01
-5.44725657e-01 -2.79857397e-01 -3.47123668e-02 -1.28815070e-01
-1.65371165e-01 3.29843640e-01 -6.13912523e-01 3.64760190e-01
6.94111764e-01 9.03689921e-01 -9.39440012e-01 5.60011089e-01
2.94321388e-01 9.29150939e-01 -2.09092543e-01 -2.89042443e-01
6.21169925e-01 -3.27720881e-01 3.40243220e-01 1.40658700e+00
2.31547937e-01 -1.88353688e-01 2.66654670e-01 -1.76714078e-01
-1.49311215e-01 8.82883132e-01 -1.50260434e-01 -2.80379891e-01
2.61173010e-01 1.18959427e+00 -1.18955684e+00 -2.67999172e-01
-4.64408159e-01 6.33595824e-01 1.97757065e-01 -6.03724383e-02
-7.52398670e-01 -6.82008028e-01 2.51535207e-01 5.95753849e-01
-1.29839480e-01 -2.61588871e-01 5.09144180e-02 -1.14666176e+00
-4.26240295e-01 -1.22050905e+00 5.55140555e-01 -3.86438221e-01
-1.39320910e+00 6.80939734e-01 -6.39321581e-02 -1.18696117e+00
-3.02765310e-01 -7.59335995e-01 7.76284263e-02 5.75224161e-01
-1.18335557e+00 -1.28100181e+00 -3.26757103e-01 5.06062984e-01
4.53246266e-01 -5.11215508e-01 6.32495940e-01 6.91317916e-01
-5.08800924e-01 7.62849510e-01 5.38264275e-01 5.27139366e-01
1.12723434e+00 -1.04657197e+00 1.29909873e-01 4.71314818e-01
7.29456097e-02 5.18334568e-01 6.19059026e-01 -4.31333452e-01
-1.14640999e+00 -1.03993261e+00 1.09244764e+00 -4.73010659e-01
1.22698140e+00 -3.72810632e-01 -7.29394436e-01 6.55305922e-01
2.50467002e-01 -6.40682936e-01 8.98907602e-01 2.34515488e-01
-4.29478794e-01 2.93397233e-02 -1.15890002e+00 8.94894898e-01
4.05223250e-01 -2.58300900e-01 -3.63373667e-01 7.32593894e-01
4.36373740e-01 -4.50459182e-01 -1.10693705e+00 1.08729728e-01
6.91754520e-01 -6.43649459e-01 6.77907765e-01 -7.52976060e-01
8.15889478e-01 -3.17118838e-02 -3.35208207e-01 -1.64389265e+00
-1.07212504e-03 -3.74065578e-01 2.00749367e-01 1.42748272e+00
6.47321224e-01 -8.82506669e-01 2.62038618e-01 -3.18272598e-02
-3.56780469e-01 -3.98773551e-01 -5.43933153e-01 -2.88396448e-01
5.47479510e-01 -2.90554613e-01 5.32366931e-01 1.41445327e+00
3.31858218e-01 5.68839967e-01 -1.88801184e-01 -2.82826781e-01
-2.23653615e-01 1.15509726e-01 7.92622924e-01 -1.41792870e+00
1.79739162e-01 -6.71297312e-01 -3.13749164e-01 -8.61684203e-01
5.82280494e-02 -1.00561810e+00 -7.61644542e-02 -1.31598651e+00
-1.35640070e-01 -9.41739738e-01 3.30330968e-01 4.22596157e-01
5.08088656e-02 7.01433480e-01 2.58872122e-01 6.99889481e-01
-3.75997603e-01 -6.04458041e-02 9.14983451e-01 -2.34867245e-01
-3.70087385e-01 4.18334678e-02 -1.01889205e+00 8.44622076e-01
7.62324631e-01 -3.97794187e-01 3.88118625e-02 -3.50237042e-01
6.57043159e-01 -4.50168908e-01 -2.98835278e-01 -6.52055740e-01
-2.01097384e-01 -1.15526989e-01 -2.97233611e-02 -1.88517123e-01
6.29114779e-03 -6.04461491e-01 -3.19078773e-01 5.34216464e-01
-4.38519299e-01 1.18557885e-01 4.38487567e-02 1.63527340e-01
-2.94364363e-01 -3.36453676e-01 8.99393022e-01 1.05982468e-01
-4.01025027e-01 3.59279453e-03 -9.61819410e-01 1.74286529e-01
7.93933153e-01 1.68106109e-01 -5.81848800e-01 -6.36981666e-01
-9.00281131e-01 8.92573297e-02 5.09690642e-01 5.20357251e-01
-1.23851202e-01 -1.14308858e+00 -1.18084180e+00 -9.96516347e-02
4.53527212e-01 -4.57981676e-01 -2.91585952e-01 1.05159378e+00
-8.32628369e-01 1.49855793e-01 -2.90341169e-01 -5.52074313e-01
-1.07954073e+00 3.80255096e-02 -2.33298633e-02 -1.99782010e-03
-1.50674358e-01 3.46196681e-01 -3.15580249e-01 -7.38796055e-01
1.64758842e-02 -1.17218405e-01 -8.35152566e-01 1.11520648e+00
6.01621628e-01 5.78516066e-01 3.60750526e-01 -1.34235001e+00
-1.20420195e-01 1.79890558e-01 -2.38746211e-01 -2.17414677e-01
1.19497764e+00 -4.73040968e-01 -5.88724315e-01 8.37638676e-01
9.80683982e-01 6.98949635e-01 -3.92853826e-01 -2.70193338e-01
4.38819557e-01 -2.30251685e-01 -1.12473696e-01 -8.11520875e-01
-8.43402445e-01 4.26483601e-01 2.38793179e-01 9.60522175e-01
7.94159889e-01 7.81915784e-02 6.24102294e-01 4.41510826e-01
3.68514597e-01 -1.27285993e+00 7.46328980e-02 1.15455306e+00
1.02505767e+00 -1.25137198e+00 -9.58922133e-02 -4.02532756e-01
-9.63906348e-01 1.15588605e+00 2.86315441e-01 4.36373428e-03
9.75757480e-01 -2.53106236e-01 2.86492616e-01 -7.09317327e-02
-1.21249989e-01 -3.16494554e-01 2.46149048e-01 8.81157294e-02
7.14683890e-01 -4.61742096e-02 -7.81841755e-01 8.39411914e-01
-6.62288964e-01 -5.74697018e-01 1.00110710e+00 8.23915660e-01
-4.63386446e-01 -9.11049783e-01 -4.55855161e-01 1.00803423e+00
-7.42591918e-01 -2.68375408e-02 -6.55493140e-01 8.85012746e-01
-3.87893058e-02 1.20235312e+00 4.46415007e-01 -5.35087168e-01
8.93244371e-02 1.31182447e-01 -2.11221538e-02 -7.16486037e-01
-1.04823518e+00 5.85269667e-02 5.80685914e-01 2.22909689e-01
-4.88345385e-01 -8.32263887e-01 -1.17771065e+00 -6.89843655e-01
-4.15930867e-01 3.49356025e-01 7.88221538e-01 9.60091949e-01
1.92603290e-01 7.29515627e-02 9.58897114e-01 -9.21803594e-01
-4.11024660e-01 -1.43442118e+00 -5.11033177e-01 5.24893105e-01
1.90173447e-01 -6.56165481e-01 -4.44979280e-01 1.22610986e-01] | [10.195062637329102, 10.060270309448242] |
9ffd554e-a545-4df6-a0ff-9c5c52ad27eb | using-multiple-instance-learning-for | 2203.13896 | null | https://arxiv.org/abs/2203.13896v2 | https://arxiv.org/pdf/2203.13896v2.pdf | Using Multiple Instance Learning for Explainable Solar Flare Prediction | In this work we leverage a weakly-labeled dataset of spectral data from NASAs IRIS satellite for the prediction of solar flares using the Multiple Instance Learning (MIL) paradigm. While standard supervised learning models expect a label for every instance, MIL relaxes this and only considers bags of instances to be labeled. This is ideally suited for flare prediction with IRIS data that consists of time series of bags of UV spectra measured along the instrument slit. In particular, we consider the readout window around the Mg II h&k lines that encodes information on the dynamics of the solar chromosphere. Our MIL models are not only able to predict whether flares occur within the next $\sim$25 minutes with accuracies of around 90%, but are also able to explain which spectral profiles were particularly important for their bag-level prediction. This information can be used to highlight regions of interest in ongoing IRIS observations in real-time and to identify candidates for typical flare precursor spectral profiles. We use k-means clustering to extract groups of spectral profiles that appear relevant for flare prediction. The recovered groups show high intensity, triplet red wing emission and single-peaked h and k lines, as found by previous works. They seem to be related to small-scale explosive events that have been reported to occur tens of minutes before a flare. | ['Martin Melchior', 'Cédric Huwyler'] | 2022-03-25 | null | null | null | null | ['solar-flare-prediction'] | ['time-series'] | [ 3.64405990e-01 -1.21163949e-01 -4.22619969e-01 -3.63597184e-01
-7.88843274e-01 -8.34493756e-01 6.70810103e-01 3.90524030e-01
2.40958452e-01 8.39792788e-01 -8.74907337e-03 -2.62242913e-01
-5.30488729e-01 -7.78871536e-01 -4.24130619e-01 -1.02480245e+00
-3.07615310e-01 5.47455847e-01 9.85976309e-02 -3.25032502e-01
1.06892072e-01 8.29345465e-01 -1.93214846e+00 4.99925911e-01
9.98092473e-01 1.05332017e+00 2.69099195e-02 4.78692830e-01
2.65998244e-02 1.06311619e+00 -4.29514885e-01 3.33050966e-01
2.30922490e-01 -7.04746664e-01 -4.72310692e-01 2.17581168e-01
7.05933690e-01 2.62968779e-01 -5.20280451e-02 8.82268131e-01
3.44815820e-01 1.91340387e-01 8.54564130e-01 -9.47427273e-01
5.57773888e-01 2.71303684e-01 -6.60124958e-01 6.69681072e-01
-3.54257785e-02 1.45009592e-01 1.06550586e+00 -1.82701990e-01
6.00254118e-01 4.29643750e-01 6.86992586e-01 -7.37796677e-03
-1.31643093e+00 -3.94754410e-01 -4.83008057e-01 4.88377005e-01
-9.32005525e-01 -4.02501047e-01 8.47531557e-01 -9.49082375e-01
1.24522555e+00 4.80482638e-01 6.26371920e-01 4.88040864e-01
-2.08184853e-01 4.67797935e-01 1.25877380e+00 -6.22693121e-01
1.56001121e-01 1.01160347e-01 4.49702382e-01 5.13104975e-01
2.94875521e-02 7.84326196e-01 -6.61537588e-01 -3.19195598e-01
1.80482045e-01 -1.98869169e-01 -4.74822938e-01 -1.23517543e-01
-9.76153195e-01 1.05969262e+00 5.30924439e-01 3.42500299e-01
-3.94970566e-01 -3.26090723e-01 2.32670382e-01 2.87629485e-01
5.02968013e-01 6.45631194e-01 -6.89314783e-01 1.87042862e-01
-1.18386340e+00 2.80056745e-01 3.22744042e-01 1.86415434e-01
1.17002559e+00 -1.96253578e-03 3.88227738e-02 5.76173902e-01
-8.90972689e-02 6.39336467e-01 2.61742353e-01 -5.99951506e-01
3.57351393e-01 6.84044719e-01 4.14909631e-01 -5.27039528e-01
-8.73467326e-01 -5.31237066e-01 -4.23073381e-01 2.86803871e-01
2.65145957e-01 -3.68793845e-01 -6.26433134e-01 1.11057782e+00
3.91706169e-01 2.61122197e-01 1.89677179e-01 9.55214262e-01
6.76010072e-01 8.53331149e-01 -2.51287997e-01 -7.49686301e-01
9.77848351e-01 -7.40741909e-01 -3.74375403e-01 -5.58629572e-01
8.57599676e-01 -5.23341417e-01 5.34903705e-01 3.87254119e-01
-5.30404687e-01 -5.83451986e-01 -9.11268651e-01 6.46771193e-01
-1.48372650e-01 1.70403823e-01 1.04834104e+00 5.46827972e-01
-3.40968370e-01 1.03268385e+00 -5.80226719e-01 -1.98652387e-01
1.07858973e-02 -2.36643285e-01 1.28658161e-01 4.96677905e-01
-9.01989818e-01 4.54694450e-01 6.07913554e-01 8.99716020e-02
-3.77654016e-01 -7.47946143e-01 -4.90707099e-01 -8.92370343e-02
1.50059953e-01 -3.22103649e-01 1.05761898e+00 -1.17426312e+00
-7.69159377e-01 9.42272782e-01 -3.93336475e-01 -1.01002848e+00
-5.35377935e-02 3.86820078e-01 -1.03064239e+00 4.76625472e-01
-2.16240510e-01 1.30612150e-01 1.16441870e+00 -9.06658530e-01
-9.69296157e-01 -5.49445808e-01 -4.07529414e-01 -1.04132093e-01
2.83330351e-01 2.41150066e-01 3.61307353e-01 -2.84945518e-01
2.14948520e-01 -9.76904869e-01 -3.31831090e-02 -8.59441698e-01
-2.31323764e-01 -2.41187960e-01 7.36125052e-01 -5.56881845e-01
1.29004049e+00 -2.00285745e+00 -1.58346206e-01 3.35972667e-01
-1.08590759e-01 3.78893405e-01 4.23186928e-01 7.03525245e-01
-6.50665462e-01 -1.18066728e-01 -4.31527108e-01 3.26244593e-01
-3.88061367e-02 -7.39474073e-02 -7.41289556e-01 4.12620157e-01
6.81856647e-02 4.44878608e-01 -5.49718142e-01 2.04912767e-01
4.66684610e-01 -4.12528813e-02 -1.29986167e-01 3.32177371e-01
-8.28795791e-01 6.00612640e-01 -7.94893056e-02 5.67625999e-01
6.64359391e-01 -3.35674584e-02 -9.02298316e-02 -3.99659306e-01
-4.78774846e-01 3.28639895e-01 -8.39668095e-01 8.11744213e-01
6.24413341e-02 6.94885135e-01 -1.47392422e-01 -1.12367594e+00
1.18726647e+00 8.51813927e-02 5.84230900e-01 -9.53444898e-01
-1.45658895e-01 1.98681816e-01 -1.64279307e-03 -8.39963078e-01
2.55199313e-01 -6.55615091e-01 2.04175040e-01 2.85033703e-01
-1.00637756e-01 -2.69564062e-01 3.36774170e-01 -1.54684395e-01
9.60106969e-01 -1.31225316e-02 1.21667348e-01 -2.48603627e-01
3.93886685e-01 2.78245032e-01 5.81484795e-01 5.17631829e-01
4.40181047e-02 3.94292712e-01 4.57884103e-01 -6.45286322e-01
-9.20717955e-01 -6.19425595e-01 -5.71165323e-01 7.03065634e-01
-1.37873277e-01 -5.03920794e-01 -1.90328434e-01 -3.94743323e-01
1.05725639e-01 9.63534415e-01 -3.69944662e-01 -5.55113815e-02
-8.03396553e-02 -1.35779405e+00 -1.25403613e-01 1.88588962e-01
1.41938329e-01 -1.45045424e+00 -8.21360409e-01 5.91079108e-02
-2.89364398e-01 -9.25833285e-01 3.29553783e-01 8.47069919e-01
-9.28425252e-01 -1.36836958e+00 2.98134059e-01 -3.63395452e-01
1.45127222e-01 2.73332261e-02 1.15246964e+00 -1.15648635e-01
-8.08084011e-01 1.74975142e-01 -6.10107124e-01 -6.53572738e-01
-3.07233155e-01 -4.03225929e-01 -1.11061655e-01 2.19685674e-01
4.93714571e-01 -4.01640773e-01 -4.35126573e-01 1.83154702e-01
-7.16090083e-01 -2.79675305e-01 -2.23920345e-02 6.30354881e-01
8.34422886e-01 5.68094134e-01 6.19578362e-01 -8.27292204e-01
-5.72715811e-02 -5.27263999e-01 -1.05149484e+00 8.32710043e-02
-4.73147720e-01 -1.01109840e-01 5.54170489e-01 1.76865846e-01
-1.19849467e+00 1.17803238e-01 1.61415413e-01 -2.06886351e-01
-6.29239798e-01 7.01867998e-01 3.77613038e-01 -1.41502529e-01
1.28469026e+00 -1.53800964e-01 -2.99676180e-01 -3.33634555e-01
-7.62599111e-02 8.06350529e-01 5.68359137e-01 -1.92462042e-01
7.76158273e-01 4.99845266e-01 1.76945284e-01 -1.24599755e+00
-1.54251432e+00 -1.17834473e+00 -5.08215666e-01 -4.47404832e-01
5.96961379e-01 -9.56565201e-01 -5.48735261e-01 2.32957274e-01
-3.79840374e-01 -5.03764212e-01 -2.20385805e-01 3.88940811e-01
-6.85560226e-01 2.40040064e-01 -1.30248532e-01 -1.21667206e+00
-4.04431552e-01 -3.88455242e-01 9.32323039e-01 6.40730083e-01
7.79530406e-02 -1.05416310e+00 3.97154629e-01 7.52561927e-01
-5.79182096e-02 6.68862581e-01 9.71430242e-01 -3.60548526e-01
-4.51910079e-01 -2.07906350e-01 3.55494134e-02 1.17647447e-01
2.09527165e-02 1.57536045e-01 -1.23936450e+00 -5.38259923e-01
2.11098745e-01 -4.44836855e-01 1.34604514e+00 5.37365913e-01
1.03685212e+00 1.15103953e-01 -4.70601916e-01 6.55822754e-01
1.66458833e+00 3.64473462e-01 6.06605947e-01 4.07308251e-01
1.72197267e-01 6.49047375e-01 9.61193323e-01 5.52370787e-01
-3.66879106e-01 7.06502736e-01 6.01719677e-01 -2.70746887e-01
1.70661479e-01 4.87493649e-02 4.40875262e-01 1.48069575e-01
3.40829901e-02 8.78402069e-02 -9.26296771e-01 6.34413838e-01
-1.93701780e+00 -1.57050216e+00 -8.67070496e-01 2.76209664e+00
3.33408743e-01 7.70234466e-02 3.42136264e-01 1.94465593e-01
5.33027649e-01 3.19827408e-01 -4.96543467e-01 -1.91988438e-01
-4.07805771e-01 5.21398246e-01 6.01938963e-01 6.14457846e-01
-1.17726040e+00 5.95993042e-01 6.07346344e+00 2.99727142e-01
-1.22700489e+00 -2.56257296e-01 1.88238144e-01 -2.43013635e-01
-2.89521784e-01 2.52840549e-01 -1.02764118e+00 4.16535318e-01
1.26640058e+00 9.29972716e-03 5.87654531e-01 3.86382312e-01
3.07154685e-01 -6.21352553e-01 -5.89465439e-01 1.02298057e+00
2.47520674e-02 -1.45516229e+00 -7.38141000e-01 -1.22215189e-01
9.29136574e-01 5.87119281e-01 -4.66071188e-01 1.94881797e-01
-2.92609543e-01 -9.03400064e-01 2.93796867e-01 1.00429499e+00
3.06825548e-01 -1.08010948e+00 4.47889924e-01 6.40573919e-01
-9.15667355e-01 -3.31791788e-01 -5.92032254e-01 -7.62299001e-02
2.35096127e-01 1.22784150e+00 -1.11762989e+00 7.74309456e-01
8.57205331e-01 7.58462489e-01 -7.59946823e-01 1.38569617e+00
-1.29378304e-01 1.18228865e+00 -6.08294427e-01 4.29616839e-01
2.15921596e-01 -7.96066642e-01 4.61907208e-01 8.02268386e-01
4.42845732e-01 -2.87925452e-03 2.64963716e-01 5.32232344e-01
5.58745503e-01 4.23901640e-02 -7.17012227e-01 -4.42634493e-01
2.91645005e-02 1.61845767e+00 -4.85335559e-01 -3.23602669e-02
-2.16033161e-01 5.34119248e-01 7.69249052e-02 1.02210134e-01
-5.43066084e-01 -2.90700465e-01 4.59814429e-01 4.80655134e-01
6.26332462e-01 6.14517741e-02 1.37500271e-01 -9.99052823e-01
-1.61780134e-01 -5.59698284e-01 6.21619046e-01 -1.03338265e+00
-1.22243488e+00 4.33227777e-01 -4.00576055e-01 -1.24291062e+00
-5.27917504e-01 -5.49847782e-01 -9.96176541e-01 8.82210672e-01
-1.74968576e+00 -1.01037765e+00 -4.53424096e-01 4.98624653e-01
-3.40104802e-03 -3.50980759e-01 8.38595033e-01 -1.28155336e-01
-3.50288630e-01 -2.76944339e-01 4.87902671e-01 -4.63174760e-01
8.01463783e-01 -1.55409241e+00 -1.07574306e-01 6.16271973e-01
6.10707104e-01 -1.54455051e-01 1.24213040e+00 -8.61612260e-01
-8.93453956e-01 -1.26810002e+00 9.06052172e-01 -2.54611731e-01
9.22007620e-01 1.99880987e-01 -1.16105795e+00 5.47468066e-01
1.41081050e-01 2.40638644e-01 7.76222944e-01 4.27868217e-01
-1.09208286e-01 -3.24589998e-01 -9.22178984e-01 -1.44089848e-01
5.51352322e-01 -7.07377136e-01 -5.30357361e-01 1.17235947e+00
-8.20000470e-03 -1.18922941e-01 -8.65626991e-01 8.96238506e-01
-2.25456014e-01 -1.82659769e+00 6.42901242e-01 -6.36754513e-01
-5.14758788e-02 -6.01004601e-01 -1.19847350e-03 -1.44018877e+00
-2.21093684e-01 -6.98195100e-01 7.91163668e-02 9.96193588e-01
5.63055694e-01 -3.39360058e-01 8.07824552e-01 -2.64029145e-01
-2.77961403e-01 -9.87506285e-02 -6.01874590e-01 -6.42994106e-01
-1.69672251e-01 -4.41824228e-01 1.17055684e-01 1.04204178e+00
1.97393909e-01 5.66046953e-01 -3.20457011e-01 6.92734301e-01
7.35859275e-01 1.10026038e+00 4.98672158e-01 -1.71198857e+00
-5.54718494e-01 -6.67328984e-02 -1.08132370e-01 -1.71322912e-01
2.79083699e-01 -1.16317642e+00 -4.83305044e-02 -1.07917392e+00
-3.92554887e-02 -4.72889185e-01 -3.81941833e-02 3.98493022e-01
9.48939025e-02 7.64240474e-02 -4.24293503e-02 2.00984150e-01
-2.89608806e-01 2.20099688e-01 4.31582898e-01 -4.53847982e-02
-2.68813968e-01 4.37660366e-01 5.25327958e-03 7.40359306e-01
1.04972160e+00 -1.33845091e-01 -2.43606851e-01 2.58919090e-01
5.98126531e-01 6.29930913e-01 4.26706642e-01 -1.38541150e+00
-5.34014665e-02 -2.78997540e-01 3.11467797e-01 -9.96933520e-01
2.01791048e-01 -6.33178532e-01 3.40692222e-01 4.40624021e-02
6.73237070e-02 -7.92348325e-01 2.92015612e-01 3.36450249e-01
-5.51420391e-01 -7.88376153e-01 9.57927048e-01 -7.18258545e-02
-7.56227255e-01 2.09689200e-01 -3.77104402e-01 -3.13339114e-01
1.19084489e+00 1.95166185e-01 -3.31008524e-01 -2.71969944e-01
-9.72837985e-01 1.67739674e-01 3.71106416e-01 3.05356830e-01
-7.67419860e-02 -8.82528841e-01 -4.65235263e-01 2.58485913e-01
5.93164563e-01 -4.31030124e-01 6.62668407e-01 7.99547732e-01
-2.63276964e-01 6.59319997e-01 5.08551337e-02 -6.87909544e-01
-1.50476539e+00 5.39695978e-01 8.65734577e-01 -5.66254668e-02
-5.80227196e-01 5.07054389e-01 -1.79565057e-01 -3.60227793e-01
-6.10408634e-02 8.96173194e-02 -5.52545726e-01 7.73439586e-01
7.90227413e-01 5.46319596e-02 6.71723068e-01 -5.01551032e-01
4.91336063e-02 4.79203701e-01 2.29765803e-01 5.55129170e-01
1.38223696e+00 1.48611903e-01 -2.88602501e-01 7.82181323e-01
6.91819847e-01 1.48082852e-01 -1.26245761e+00 -2.51006335e-01
1.26569167e-01 -2.03767851e-01 4.10309225e-01 -1.15729368e+00
-9.10817444e-01 8.66991341e-01 9.32277441e-01 6.27286911e-01
1.19946766e+00 2.56214738e-01 3.02504033e-01 3.49388927e-01
4.32290584e-01 -1.10662532e+00 -3.06780964e-01 3.58569175e-01
7.91409791e-01 -1.32413614e+00 -2.27840975e-01 -2.66334236e-01
-6.85674846e-01 1.49407542e+00 4.02753443e-01 1.13343313e-01
4.11817253e-01 1.08243145e-01 5.46010099e-02 -5.82562029e-01
-8.94863427e-01 -6.74367785e-01 3.16829234e-01 3.96370828e-01
6.74132332e-02 3.55239302e-01 -1.42814636e-01 3.58773381e-01
-2.85490960e-01 -2.43546218e-01 6.28916323e-01 5.57859719e-01
-1.06803811e+00 -1.05910647e+00 -7.91739881e-01 9.14373994e-01
1.38881385e-01 1.60108373e-01 -4.01853412e-01 1.50909588e-01
2.71025479e-01 9.86780763e-01 2.97242969e-01 -2.04556257e-01
2.36426339e-01 6.38651252e-01 5.29668987e-01 -3.91129225e-01
-6.37052894e-01 3.26389641e-01 4.79407340e-01 -2.60126412e-01
-6.82972252e-01 -1.09445548e+00 -1.23205769e+00 1.26774386e-01
-3.37705940e-01 5.02565324e-01 4.35069948e-01 1.06996024e+00
9.03791413e-02 3.07621837e-01 9.85228717e-01 -7.17575550e-01
-1.23801053e-01 -9.69198704e-01 -1.15428710e+00 3.79541218e-01
5.67538559e-01 -6.16623044e-01 -8.35121930e-01 7.52371550e-02] | [6.62171745300293, 2.78182053565979] |
bc8136bc-4ad0-4f4f-bfba-331decb644b1 | feature-calibration-network-for-occluded | 2212.05717 | null | https://arxiv.org/abs/2212.05717v1 | https://arxiv.org/pdf/2212.05717v1.pdf | Feature Calibration Network for Occluded Pedestrian Detection | Pedestrian detection in the wild remains a challenging problem especially for scenes containing serious occlusion. In this paper, we propose a novel feature learning method in the deep learning framework, referred to as Feature Calibration Network (FC-Net), to adaptively detect pedestrians under various occlusions. FC-Net is based on the observation that the visible parts of pedestrians are selective and decisive for detection, and is implemented as a self-paced feature learning framework with a self-activation (SA) module and a feature calibration (FC) module. In a new self-activated manner, FC-Net learns features which highlight the visible parts and suppress the occluded parts of pedestrians. The SA module estimates pedestrian activation maps by reusing classifier weights, without any additional parameter involved, therefore resulting in an extremely parsimony model to reinforce the semantics of features, while the FC module calibrates the convolutional features for adaptive pedestrian representation in both pixel-wise and region-based ways. Experiments on CityPersons and Caltech datasets demonstrate that FC-Net improves detection performance on occluded pedestrians up to 10% while maintaining excellent performance on non-occluded instances. | ['Qi Tian', 'Xiaopeng Zhang', 'Jianzhuang Liu', 'Baochang Zhang', 'Qixiang Ye', 'Tianliang Zhang'] | 2022-12-12 | null | null | null | null | ['pedestrian-detection'] | ['computer-vision'] | [-3.14154173e-03 -5.52049205e-02 2.12529644e-01 -4.66749877e-01
-1.20977415e-02 -2.12908089e-01 6.38185620e-01 1.37802258e-01
-6.56989694e-01 5.90766072e-01 5.57383746e-02 9.13329199e-02
3.89026821e-01 -1.04496062e+00 -6.08724415e-01 -9.88352001e-01
-1.09386735e-01 -3.32117602e-02 8.11232030e-01 -2.30752364e-01
-1.02178566e-01 6.50622249e-01 -1.88081324e+00 3.69530290e-01
8.17545474e-01 7.98194528e-01 1.33709475e-01 6.26612663e-01
-3.61470431e-02 4.79099423e-01 -4.66623992e-01 -3.69713068e-01
4.61054564e-01 -9.57012922e-02 -3.20150375e-01 4.08681154e-01
5.72019577e-01 -1.73259348e-01 -4.48176742e-01 9.18253779e-01
5.14478683e-01 1.36285722e-01 5.26214778e-01 -1.24925745e+00
-2.36668825e-01 1.64790556e-01 -8.27859282e-01 4.60218459e-01
1.56129867e-01 6.02784812e-01 5.99319279e-01 -8.97576630e-01
3.00999701e-01 1.49574244e+00 6.90802872e-01 5.08597314e-01
-1.20402956e+00 -4.20220613e-01 5.01121402e-01 3.21391881e-01
-1.35818815e+00 -4.28436875e-01 8.36151659e-01 -4.69331354e-01
4.95335877e-01 3.37049633e-01 1.14187694e+00 1.18601811e+00
8.62709507e-02 9.76078868e-01 9.13161993e-01 -4.40665901e-01
2.61725336e-01 4.52908784e-01 2.33198613e-01 6.68440044e-01
5.42721868e-01 4.20126826e-01 -3.56439710e-01 9.90796164e-02
8.36235821e-01 9.57319960e-02 -1.22678079e-01 -6.59976363e-01
-7.49766111e-01 7.56381035e-01 9.08402383e-01 1.42990649e-01
-3.85335386e-01 -6.27718791e-02 4.10203099e-01 1.28151104e-01
3.81516248e-01 -1.53972104e-01 -3.69179934e-01 4.94645894e-01
-7.45122313e-01 3.02461684e-01 3.30523193e-01 7.86223054e-01
8.89547050e-01 2.20991820e-01 -6.42735779e-01 6.47344649e-01
3.26049745e-01 3.94725442e-01 4.12768394e-01 -5.24951160e-01
1.74884856e-01 9.68619645e-01 2.35537723e-01 -9.69154656e-01
-5.78782678e-01 -1.03714216e+00 -8.13092887e-01 6.35502815e-01
5.06724834e-01 -2.90439844e-01 -8.00515652e-01 1.72438419e+00
7.97720611e-01 9.47523117e-03 -1.13793753e-01 9.80779648e-01
9.54141736e-01 3.88334304e-01 5.66650748e-01 1.15451023e-01
1.59626198e+00 -1.08119130e+00 -2.05854475e-01 -3.55229169e-01
2.27312103e-01 -4.36545223e-01 8.91401529e-01 8.28173459e-02
-7.93092966e-01 -1.12388909e+00 -9.94160473e-01 5.15650176e-02
-5.10475218e-01 4.46022719e-01 6.43886745e-01 8.85187566e-01
-9.41072285e-01 2.69713491e-01 -5.03730893e-01 -6.50794089e-01
7.21161366e-01 2.46192992e-01 -5.14401317e-01 1.32683560e-01
-9.31668460e-01 7.00027287e-01 5.90865076e-01 3.02567065e-01
-8.69517446e-01 -5.90516388e-01 -9.34440792e-01 2.61368841e-01
1.83205530e-01 -9.66559529e-01 5.38603067e-01 -1.38208270e+00
-1.36462271e+00 8.63587379e-01 -1.35975391e-01 -6.69338703e-01
9.89734292e-01 -1.96957320e-01 -5.08728147e-01 1.53574616e-01
2.11169347e-01 1.02382779e+00 1.17545319e+00 -1.39533722e+00
-1.15645421e+00 -3.53572905e-01 7.93662891e-02 2.93225143e-02
-3.82545084e-01 -5.50110228e-02 -3.68357629e-01 -5.92506349e-01
1.27671128e-02 -6.12145782e-01 -4.18825120e-01 4.03996259e-01
-3.63129348e-01 -2.38258988e-01 1.04640865e+00 -3.49294841e-01
7.77541459e-01 -2.16914606e+00 -1.63399011e-01 2.16336474e-01
3.16373080e-01 6.40767038e-01 -2.34945133e-01 -6.70407563e-02
-1.45841137e-01 -5.53646266e-01 -1.21709369e-01 -2.20495492e-01
-3.39446425e-01 -1.13343131e-02 -9.00373533e-02 6.42030954e-01
8.03572893e-01 9.05306935e-01 -8.77113700e-01 -5.96451700e-01
7.39742815e-01 7.95883298e-01 -4.27405059e-01 1.99901208e-01
6.93614110e-02 5.31038821e-01 -3.91241312e-01 7.73020506e-01
1.03292286e+00 1.34961918e-01 -1.43430218e-01 -1.86047077e-01
-5.66096783e-01 -4.52710629e-01 -1.42404318e+00 1.17488539e+00
-1.00125723e-01 6.02558196e-01 9.28378180e-02 -8.65603626e-01
1.04938161e+00 -1.20579630e-01 1.86828077e-01 -7.42144525e-01
2.89811105e-01 -1.96074471e-01 -9.13827941e-02 -5.52464306e-01
4.38100100e-01 4.27187085e-01 1.59583613e-01 -2.03059539e-01
1.31158307e-01 6.31857991e-01 3.39488447e-01 8.69217440e-02
8.68380725e-01 1.73662275e-01 3.16849023e-01 -4.92339760e-01
1.06429005e+00 -1.64016217e-01 6.01930320e-01 8.73802304e-01
-6.55414045e-01 4.28305924e-01 2.14779422e-01 -1.00315666e+00
-7.74300635e-01 -1.24099207e+00 -2.82803088e-01 1.30677712e+00
3.26776952e-01 -2.10236296e-01 -9.30398285e-01 -7.09824741e-01
1.91929236e-01 4.67552930e-01 -8.47162664e-01 -2.35264540e-01
-6.87887132e-01 -7.99120367e-01 1.45248070e-01 6.50428891e-01
9.56032038e-01 -1.07734871e+00 -1.04039133e+00 2.64565825e-01
3.91752236e-02 -9.88735199e-01 -2.31330603e-01 3.49592060e-01
-4.37842876e-01 -1.15990794e+00 -7.51166940e-01 -7.60967612e-01
8.20337713e-01 7.48167098e-01 7.85382867e-01 2.85494886e-02
-7.13099003e-01 2.56986916e-01 -1.49158046e-01 -4.17451560e-01
-6.21256344e-02 -1.27925351e-01 -1.26538172e-01 5.79827309e-01
3.77353370e-01 -4.44842488e-01 -1.00193906e+00 3.85934234e-01
-4.46170688e-01 -4.20225300e-02 7.70030022e-01 8.49741518e-01
3.79730701e-01 4.50676233e-02 4.62252408e-01 -6.50676191e-01
7.22113177e-02 -2.17819974e-01 -7.63082027e-01 1.94820493e-01
-3.65955830e-02 -1.71305016e-01 5.07428527e-01 -3.98876131e-01
-1.24530220e+00 5.97993851e-01 -1.11431502e-01 -1.16016753e-01
-5.11213124e-01 -5.62111020e-01 -6.04040265e-01 -3.91764730e-01
8.24845254e-01 3.58027875e-01 -1.89353362e-01 -2.57834762e-01
5.10966420e-01 3.64318103e-01 7.78092325e-01 -4.68533784e-01
9.86112118e-01 7.60403872e-01 6.77789450e-02 -8.97409678e-01
-6.80203140e-01 -6.43912971e-01 -1.03993905e+00 -6.36973262e-01
7.92599499e-01 -1.15286243e+00 -6.89406991e-01 5.24280190e-01
-9.81392562e-01 -4.03477438e-02 -6.86575413e-01 2.14330837e-01
-2.16931343e-01 3.44932228e-01 -2.96926379e-01 -9.25908267e-01
-3.54044348e-01 -9.88744199e-01 1.07448566e+00 7.63194501e-01
1.70709863e-01 -7.05817342e-01 -3.00366759e-01 -1.42784845e-02
4.54353660e-01 4.36647832e-01 4.55785096e-01 -3.04878265e-01
-5.97891212e-01 -3.64021271e-01 -6.00318015e-01 1.64445937e-01
-6.95153922e-02 9.88640562e-02 -1.37922740e+00 -4.20611978e-01
-2.66029626e-01 8.51963311e-02 1.27226102e+00 6.26872301e-01
9.50554609e-01 5.34545630e-02 -5.21831751e-01 6.15029216e-01
1.25724840e+00 -2.66243041e-01 6.35116935e-01 5.35801589e-01
4.20988619e-01 6.70353591e-01 4.11747009e-01 4.99389142e-01
3.77225220e-01 6.97169662e-01 5.25108993e-01 -5.58901370e-01
-5.51197827e-01 -1.47934794e-01 2.46358007e-01 -2.78965861e-01
-1.59631541e-03 4.03595120e-02 -4.03160542e-01 4.31148350e-01
-2.00100756e+00 -1.04550862e+00 -4.21137989e-01 2.26498699e+00
4.36307460e-01 2.65592456e-01 5.91746032e-01 2.19178781e-01
1.03857505e+00 -1.23454414e-01 -4.86257136e-01 -9.37058590e-03
-4.38015193e-01 3.06130573e-02 4.16458577e-01 2.36682355e-01
-1.70154309e+00 1.03505981e+00 5.82022285e+00 6.28260970e-01
-9.67964292e-01 1.11917503e-01 7.20478296e-01 1.46516457e-01
3.28978449e-01 -1.96935460e-01 -9.96379673e-01 6.49677515e-01
4.11819339e-01 2.89943576e-01 -2.54421532e-01 1.16816664e+00
2.47546896e-01 -2.41131648e-01 -6.47615671e-01 9.12158132e-01
-1.61744967e-01 -9.21365380e-01 3.68529111e-02 -2.00905576e-01
4.24301833e-01 -2.50913590e-01 6.00853041e-02 3.71565640e-01
2.63622940e-01 -5.56145191e-01 9.80810821e-01 3.68622661e-01
3.40400994e-01 -8.01769018e-01 6.65925920e-01 1.41646072e-01
-1.62257457e+00 -5.02373636e-01 -6.42708719e-01 3.68626346e-03
1.00919880e-01 6.42159164e-01 -4.38579708e-01 4.22130734e-01
8.87324810e-01 5.65693736e-01 -1.04758632e+00 1.48219669e+00
-3.47901046e-01 2.57692993e-01 -1.78907499e-01 2.71624267e-01
2.66289264e-01 3.03239953e-02 6.45030737e-01 1.64784980e+00
-1.21446848e-01 -1.55036524e-01 3.28532010e-01 8.62517655e-01
4.38800007e-01 2.81351600e-02 -3.06460530e-01 8.61757398e-01
2.65223444e-01 1.65940559e+00 -8.63274574e-01 -3.05096626e-01
-2.76176959e-01 1.13267446e+00 5.13172805e-01 3.70921612e-01
-8.82815301e-01 -2.76190251e-01 6.01831555e-01 3.89349520e-01
6.61639631e-01 -7.25481659e-02 -8.23575482e-02 -1.07023442e+00
5.36345951e-02 -2.72120327e-01 5.38858116e-01 -3.72710705e-01
-1.21631420e+00 6.37218773e-01 -2.05575168e-01 -1.26924658e+00
2.10200220e-01 -6.41812205e-01 -8.90074372e-01 6.83608234e-01
-1.85120761e+00 -1.46427226e+00 -8.80561769e-01 8.87591839e-01
5.71201503e-01 -2.45578870e-01 4.90451008e-01 3.17342758e-01
-9.15911674e-01 7.01053858e-01 -3.24028373e-01 1.98486418e-01
4.96977955e-01 -1.21646810e+00 3.90667617e-01 1.06106758e+00
-1.41007617e-01 3.37542415e-01 6.52153969e-01 -4.45578367e-01
-9.48448241e-01 -1.51033890e+00 6.46401763e-01 -1.84966981e-01
1.23513408e-01 -4.00066018e-01 -7.12152660e-01 2.37738192e-01
1.67225040e-02 5.39914846e-01 4.32124704e-01 -8.44524428e-02
-4.39334720e-01 -4.28405970e-01 -1.32511163e+00 4.70210105e-01
1.07862711e+00 3.72301713e-02 -3.51124197e-01 4.31184471e-01
4.17198002e-01 -1.32551476e-01 -2.99485594e-01 2.12436736e-01
5.51591575e-01 -1.17675936e+00 1.34907925e+00 -5.48011839e-01
-1.84881404e-01 -7.06553519e-01 -8.16489831e-02 -1.01078296e+00
-8.31538320e-01 -1.74606696e-01 -1.35059997e-01 1.29239488e+00
-7.02768043e-02 -5.79132974e-01 7.41244674e-01 3.30679923e-01
-9.50739160e-02 -3.08270365e-01 -1.20573163e+00 -7.29077995e-01
-3.51173788e-01 -1.14741139e-02 4.56702620e-01 5.11550307e-01
-5.84776163e-01 1.18992373e-01 -2.31159166e-01 3.45704257e-01
8.98682177e-01 -1.27520740e-01 1.01375031e+00 -1.35270274e+00
-1.10960834e-01 -4.94834423e-01 -9.08430219e-01 -8.41496229e-01
2.47632898e-02 -5.74409664e-01 -4.82821316e-02 -1.15625405e+00
2.89066136e-01 -3.23160082e-01 -3.59332174e-01 4.16801333e-01
-5.09446442e-01 2.99730659e-01 1.58120230e-01 3.34451795e-02
-6.99268579e-01 6.72018647e-01 8.45975339e-01 -3.41340482e-01
-2.79170066e-01 3.06586534e-01 -6.40377223e-01 8.03303063e-01
6.02172673e-01 -1.52644798e-01 -9.79811847e-02 -1.70611367e-01
-7.02424288e-01 -7.38537788e-01 9.70711946e-01 -1.51968873e+00
2.40857691e-01 8.24219808e-02 1.29219246e+00 -6.19524896e-01
3.10766071e-01 -8.65826249e-01 -1.17355317e-01 8.74707997e-01
-5.09572774e-02 -1.59443408e-01 3.01714242e-01 7.63645232e-01
6.75117597e-02 4.07158099e-02 1.22870755e+00 -2.39898384e-01
-1.14974380e+00 1.96228191e-01 -3.29807162e-01 -2.46809751e-01
1.42374706e+00 -4.48653698e-01 -1.98060781e-01 9.16690826e-02
-7.67296672e-01 2.58878261e-01 2.48165131e-01 3.96098107e-01
6.17525220e-01 -1.21284211e+00 -8.63332510e-01 8.00677061e-01
1.77951515e-01 -1.57405108e-01 5.04480064e-01 4.88837004e-01
-2.46928498e-01 3.09589237e-01 -4.29261446e-01 -9.71159399e-01
-1.15419531e+00 6.10685170e-01 5.16857445e-01 -2.02754047e-02
-9.46466625e-01 9.15869594e-01 5.02448380e-01 -7.03872591e-02
2.97373801e-01 -2.65105758e-02 -4.79481220e-01 6.93157166e-02
8.82844329e-01 4.46533471e-01 -1.27936155e-01 -8.60878170e-01
-3.29701066e-01 4.39660728e-01 -2.19675884e-01 3.50977659e-01
1.16346896e+00 -1.95184931e-01 2.06506878e-01 -1.54757798e-01
7.37099349e-01 -2.04120159e-01 -1.76767290e+00 -3.94286245e-01
-2.21491918e-01 -7.20872283e-01 -3.23156011e-03 -6.28759682e-01
-1.22037399e+00 6.61551178e-01 1.18429756e+00 -1.53069913e-01
1.04966950e+00 -1.98111489e-01 4.10974860e-01 1.22738168e-01
2.86324561e-01 -1.06418347e+00 1.38937056e-01 1.96574599e-01
6.95851624e-01 -1.33256030e+00 -8.57351124e-02 -5.40399015e-01
-5.06973743e-01 1.27308166e+00 1.01695108e+00 -2.17015073e-01
5.46002388e-01 9.50962752e-02 -1.44326359e-01 8.54025502e-03
-3.84324193e-01 -6.56836092e-01 1.74686983e-01 9.92085278e-01
1.99255105e-02 1.53826877e-01 -2.19344590e-02 5.53796053e-01
1.10443808e-01 -3.59685838e-01 2.66752057e-02 7.06578255e-01
-8.98741901e-01 -8.89768004e-01 -5.63097000e-01 2.20216975e-01
2.67315745e-01 1.57748222e-01 -2.64443278e-01 8.60003769e-01
6.65234804e-01 9.42560077e-01 1.81193426e-01 -2.13559762e-01
4.66015458e-01 -1.56237662e-01 3.89855057e-01 -2.86341995e-01
-8.60483229e-01 1.13268169e-02 -2.85829514e-01 -4.74476159e-01
-3.54038745e-01 -7.17400014e-01 -9.24278915e-01 -1.76575303e-01
-4.14834589e-01 -1.36377439e-01 4.93991941e-01 7.13891923e-01
3.00295353e-01 6.12984359e-01 7.73484230e-01 -1.09135640e+00
-2.29353383e-01 -8.04063261e-01 -3.95644695e-01 4.71890658e-01
2.69693762e-01 -9.79019344e-01 -5.82059622e-02 -7.15739653e-02] | [8.07052230834961, -0.5729885101318359] |
dc6917c2-93c7-4ed3-9f7b-4b7793ea4d6d | from-a-glance-to-gotcha-interactive-facial | 2007.15683 | null | https://arxiv.org/abs/2007.15683v1 | https://arxiv.org/pdf/2007.15683v1.pdf | From A Glance to "Gotcha": Interactive Facial Image Retrieval with Progressive Relevance Feedback | Facial image retrieval plays a significant role in forensic investigations where an untrained witness tries to identify a suspect from a massive pool of images. However, due to the difficulties in describing human facial appearances verbally and directly, people naturally tend to depict by referring to well-known existing images and comparing specific areas of faces with them and it is also challenging to provide complete comparison at each time. Therefore, we propose an end-to-end framework to retrieve facial images with relevance feedback progressively provided by the witness, enabling an exploitation of history information during multiple rounds and an interactive and iterative approach to retrieving the mental image. With no need of any extra annotations, our model can be applied at the cost of a little response effort. We experiment on \texttt{CelebA} and evaluate the performance by ranking percentile and achieve 99\% under the best setting. Since this topic remains little explored to the best of our knowledge, we hope our work can serve as a stepping stone for further research. | ['Alexander Hauptmann', 'Xinru Yang', 'Haozhi Qi', 'Mingyang Li'] | 2020-07-30 | null | null | null | null | ['face-image-retrieval'] | ['computer-vision'] | [ 2.52859056e-01 4.19479236e-02 1.88795757e-02 -5.85001230e-01
-9.84680653e-01 -6.12631381e-01 6.21201456e-01 1.69839457e-01
-5.70512652e-01 4.28022444e-01 -1.11620605e-01 -1.16256930e-01
-1.42860770e-01 -2.84863055e-01 -2.73018420e-01 -4.93264228e-01
-9.04085487e-02 7.00806916e-01 3.10962051e-01 -4.26099561e-02
4.04678434e-01 9.03510153e-01 -1.73828638e+00 3.46368074e-01
1.85675591e-01 9.68464911e-01 6.55254945e-02 3.74233514e-01
1.94018662e-01 8.89281869e-01 -5.05165040e-01 -1.25165641e+00
3.48424315e-01 -3.17060053e-01 -1.06578541e+00 4.13245559e-01
7.64520526e-01 -8.29112411e-01 -3.42207134e-01 1.04789710e+00
6.79805160e-01 1.07775606e-01 3.96118134e-01 -1.09079051e+00
-3.05125445e-01 2.05739081e-01 -7.92909503e-01 5.93680918e-01
6.91452086e-01 1.60584450e-01 7.55095005e-01 -9.77769613e-01
1.02529144e+00 1.36146271e+00 2.09835187e-01 5.90560079e-01
-9.62273657e-01 -6.95037544e-01 2.10480958e-01 7.11794913e-01
-1.61675024e+00 -9.40040410e-01 9.07861114e-01 -6.34118617e-02
3.56062800e-01 3.21542680e-01 3.68353486e-01 1.01959574e+00
-4.65738982e-01 8.89218509e-01 1.03567374e+00 -2.79245913e-01
-3.60546913e-03 2.48666778e-01 1.02383986e-01 8.23238254e-01
2.38822512e-02 -1.72384232e-01 -9.47169781e-01 -3.79469007e-01
4.05759722e-01 1.46564603e-01 -1.96353033e-01 -1.19749263e-01
-6.00440264e-01 4.96452361e-01 2.49568924e-01 1.34697661e-01
-5.73596835e-01 -2.29674354e-02 3.56282890e-01 5.54255605e-01
4.81153756e-01 1.08372413e-01 3.08224261e-01 -3.08927745e-01
-1.22874153e+00 2.79875100e-01 5.73221505e-01 5.50683916e-01
6.92122161e-01 -4.30291176e-01 -2.41418537e-02 8.27823877e-01
1.24079101e-01 4.52494234e-01 3.52465697e-02 -1.02623022e+00
3.51210862e-01 5.08520961e-01 1.67491987e-01 -1.18625331e+00
8.67696200e-03 3.51236910e-02 -4.01249021e-01 3.43775511e-01
5.60736954e-01 1.43960208e-01 -6.47795081e-01 1.44380581e+00
6.82396114e-01 1.74754173e-01 -4.41788971e-01 1.13650286e+00
5.61142743e-01 1.38662398e-01 1.64467707e-01 -4.32110727e-01
1.59899616e+00 -3.47274184e-01 -5.76646984e-01 -2.67935216e-01
7.75895119e-02 -8.94206285e-01 6.35977507e-01 6.26789808e-01
-1.30633080e+00 -1.10131636e-01 -5.98611295e-01 -1.85014814e-01
1.37842838e-02 1.07577413e-01 5.27141452e-01 6.59157991e-01
-1.03869188e+00 5.60238838e-01 -7.07232535e-01 -4.88800287e-01
8.34983766e-01 2.41204813e-01 -7.22783327e-01 -4.34084743e-01
-8.93348455e-01 8.12864006e-01 1.20988175e-01 3.54900628e-01
-8.90236080e-01 -2.88984448e-01 -4.20652688e-01 -1.56465426e-01
7.42077053e-01 -3.13051492e-01 1.32238805e+00 -8.82931411e-01
-1.20721960e+00 1.24420202e+00 -4.18393403e-01 -2.43165597e-01
8.91698539e-01 -2.86710232e-01 -2.52415895e-01 8.24616969e-01
4.27055061e-02 6.65639520e-01 1.11336493e+00 -1.19279182e+00
-4.83111739e-01 -6.81274235e-01 3.56255531e-01 1.82941288e-01
-5.47675192e-01 7.58641422e-01 -8.32615316e-01 -4.61098552e-01
1.30192980e-01 -9.04695153e-01 5.23230284e-02 4.69182253e-01
-5.45865437e-03 -2.71430552e-01 7.49524176e-01 -8.05178940e-01
1.08888090e+00 -2.16975045e+00 -1.43509924e-01 2.87082762e-01
3.75399888e-01 4.21038747e-01 -1.04140989e-01 4.68466252e-01
-6.50327355e-02 1.46899894e-01 -9.82407853e-02 -5.77294588e-01
-2.76442170e-01 -1.82812035e-01 -2.16456428e-01 6.73951089e-01
2.65446454e-01 8.44040275e-01 -1.11874318e+00 -8.26466978e-01
-1.15811005e-01 4.72116321e-01 -1.65424570e-01 1.81965426e-01
1.86416104e-01 2.43965819e-01 -5.80559850e-01 9.72974777e-01
6.00458860e-01 -1.83271930e-01 2.94179797e-01 -4.19519730e-02
3.52821499e-01 -2.47053914e-02 -1.14042902e+00 1.58456540e+00
6.39099404e-02 5.84180593e-01 3.11269671e-01 -8.92514527e-01
7.57573545e-01 4.92280334e-01 2.52446920e-01 -8.41798007e-01
4.35783938e-02 3.61103900e-02 -1.92945614e-01 -6.94996476e-01
6.02826357e-01 -2.51916200e-01 1.07508726e-01 1.07436812e+00
-2.95891941e-01 2.78257042e-01 3.24483722e-01 4.89267409e-01
1.07206357e+00 -4.48540747e-02 1.50910929e-01 3.76803845e-01
3.56659234e-01 -1.51227102e-01 2.21760273e-01 6.82726860e-01
-2.75266677e-01 5.27596831e-01 5.14725447e-01 -6.18715584e-01
-7.97384620e-01 -8.78465176e-01 4.60454077e-02 1.21868885e+00
1.24962568e-01 -3.60884428e-01 -6.15708888e-01 -7.63886452e-01
-2.26649508e-01 3.32848758e-01 -6.68566465e-01 7.12691545e-02
-6.67821944e-01 -4.13652480e-01 6.33840621e-01 2.92067349e-01
3.09689909e-01 -1.22077632e+00 -9.35027480e-01 -7.31244087e-02
-2.80429035e-01 -1.02513683e+00 -4.27553266e-01 -5.06940305e-01
-8.06717575e-01 -1.20731151e+00 -7.60622382e-01 -3.06442529e-01
8.61685455e-01 6.46763623e-01 1.02200496e+00 5.90438545e-01
-5.79746544e-01 6.04682982e-01 -4.89192635e-01 -2.29674697e-01
-1.85036704e-01 -2.72153527e-01 -1.17401838e-01 4.03346777e-01
3.45606863e-01 -6.03426516e-01 -8.44726324e-01 3.09085399e-01
-1.20149601e+00 -2.29616821e-01 5.70005834e-01 6.06679440e-01
2.43702069e-01 -2.58358210e-01 3.03784132e-01 -8.83865356e-01
6.77227855e-01 -5.39071143e-01 -3.81271273e-01 4.74465013e-01
-3.55769187e-01 -1.80511922e-01 8.60705823e-02 -3.58373344e-01
-1.04813874e+00 3.51335928e-02 3.02408963e-01 -8.43902647e-01
-1.69119641e-01 2.68287241e-01 8.82981494e-02 4.74767014e-03
5.51889300e-01 1.19228192e-01 1.06342636e-01 -4.89952832e-01
4.56063092e-01 6.01803184e-01 7.73662388e-01 -6.62875533e-01
8.23586524e-01 7.36981690e-01 -3.20812389e-02 -6.59793973e-01
-6.23174071e-01 -5.69973707e-01 -7.48467386e-01 -6.82143569e-01
3.27676773e-01 -5.41697919e-01 -1.04286647e+00 1.94729775e-01
-1.20149279e+00 1.09254941e-01 2.03765910e-02 2.54720915e-02
-2.06190795e-01 9.58745182e-01 -4.64493662e-01 -1.23641598e+00
-4.62378174e-01 -9.95748281e-01 1.24263990e+00 3.41068730e-02
-2.87105739e-01 -4.83150750e-01 -3.07010263e-01 6.73972189e-01
1.73292130e-01 1.70280948e-01 3.97448033e-01 -5.11497021e-01
-7.09156871e-01 -5.59814155e-01 -3.67513806e-01 5.37690753e-03
-7.34618455e-02 -2.63171226e-01 -1.29011893e+00 -3.99776071e-01
-1.31532937e-01 -6.60898685e-01 8.30294132e-01 -3.46875936e-01
1.12268019e+00 -2.69044191e-01 -2.33459666e-01 1.57736894e-02
1.00287175e+00 3.09558734e-02 6.32862091e-01 1.98294774e-01
3.48119289e-01 1.02760494e+00 7.83509433e-01 6.08692288e-01
2.35702947e-01 8.28747809e-01 4.83475834e-01 1.95782796e-01
-9.54516008e-02 4.81447554e-04 2.02588081e-01 -7.59250624e-03
-3.96957874e-01 -2.38287956e-01 -1.01760685e+00 6.58914208e-01
-1.65037441e+00 -1.37548697e+00 3.19637477e-01 2.29669881e+00
6.77693963e-01 -2.22462997e-01 2.51281977e-01 2.26038367e-01
8.41617048e-01 1.37478873e-01 -5.31316578e-01 -5.91461211e-02
1.65013716e-01 2.96123981e-01 3.71501334e-02 2.09840402e-01
-9.01906133e-01 9.35670733e-01 6.08752441e+00 1.07138669e+00
-1.26968837e+00 8.79335552e-02 9.19556260e-01 -5.70946932e-01
-1.19324774e-02 6.17140420e-02 -4.57306653e-01 3.97122681e-01
7.72471786e-01 -7.17094988e-02 5.11995614e-01 6.33660316e-01
1.58583503e-02 -3.78274769e-01 -1.16057479e+00 1.36792183e+00
3.32013130e-01 -9.15909350e-01 -3.66435088e-02 1.14545360e-01
1.20092250e-01 -3.51436257e-01 1.90893635e-01 -1.09636523e-01
-3.34010907e-02 -9.92628872e-01 8.13823700e-01 7.47496128e-01
8.95330071e-01 -7.51229882e-01 4.92415547e-01 2.11302802e-01
-9.94236410e-01 -8.38489234e-02 -2.05943853e-01 2.43878998e-02
4.68497753e-01 2.83881336e-01 -1.15118814e+00 5.09935498e-01
6.60109282e-01 3.08183581e-01 -6.68577671e-01 1.00723207e+00
-3.54238093e-01 5.07712305e-01 -3.30833912e-01 8.96655098e-02
1.02401152e-01 2.05591589e-01 4.52010959e-01 9.64788377e-01
2.53795743e-01 4.68547136e-01 1.88098907e-01 5.34918487e-01
-2.75664657e-01 3.12278777e-01 -5.23577690e-01 1.18255153e-01
6.53058112e-01 1.44953418e+00 -9.31805789e-01 -3.12336743e-01
-7.73572698e-02 1.11646700e+00 5.17892540e-01 1.39540568e-01
-5.27898610e-01 5.20680323e-02 2.85106808e-01 4.58125949e-01
2.19443336e-01 2.71589104e-02 1.94524080e-01 -8.72040093e-01
3.81818861e-01 -8.97744000e-01 7.60412931e-01 -9.02628958e-01
-1.30093288e+00 7.96741962e-01 3.19335938e-01 -1.11980677e+00
-5.12190104e-01 -2.63825357e-01 -4.67670202e-01 5.88167965e-01
-1.48540926e+00 -1.04663825e+00 -3.23413879e-01 6.84643805e-01
4.29279208e-01 1.10495798e-01 5.87223470e-01 3.77682626e-01
-5.05401313e-01 6.78087950e-01 -4.64108020e-01 1.43840209e-01
9.28262949e-01 -7.82776237e-01 2.18699738e-01 8.08618009e-01
3.86665434e-01 8.24554920e-01 6.76207900e-01 -6.95142746e-01
-1.32750702e+00 -6.63461626e-01 8.75830889e-01 -4.86964047e-01
5.29493988e-01 -1.43937647e-01 -1.01844680e+00 2.37627298e-01
1.65913329e-01 1.17898896e-01 7.15327501e-01 3.76468934e-02
-5.36614656e-01 -1.73373178e-01 -1.17788601e+00 5.63267231e-01
1.17665350e+00 -7.48383403e-01 -4.53938514e-01 2.98499882e-01
-1.87982112e-01 -2.15612754e-01 -6.55745506e-01 -1.26304431e-02
7.21193075e-01 -9.48633075e-01 8.98038268e-01 -4.83001381e-01
1.44423053e-01 -1.23696029e-01 1.60642505e-01 -6.42930567e-01
1.40068337e-01 -7.59678721e-01 1.30798250e-01 1.30128729e+00
1.74991220e-01 -3.54418665e-01 8.05341899e-01 1.22421718e+00
4.47635531e-01 -4.52338994e-01 -1.13766301e+00 -5.68361044e-01
-4.84308034e-01 -4.65103596e-01 5.81596136e-01 7.64751315e-01
1.44916326e-01 1.73614115e-01 -7.23686874e-01 4.05448750e-02
6.58187091e-01 1.79248676e-01 8.57651234e-01 -1.28582251e+00
-2.42183775e-01 -3.50612849e-01 -5.59578240e-01 -7.14587867e-01
1.51974410e-01 -7.55182803e-01 -2.28364050e-01 -9.12304580e-01
6.37596250e-01 -3.20967346e-01 -3.35752368e-01 6.90831304e-01
-3.03107172e-01 8.02857578e-01 5.06141126e-01 4.53570127e-01
-1.05373168e+00 1.31601095e-01 1.02274311e+00 -1.02843948e-01
2.11171076e-01 -2.45699808e-01 -8.06485951e-01 6.33517861e-01
7.68243432e-01 -6.11194432e-01 -4.12811577e-01 -3.97252738e-01
1.69948205e-01 3.46849948e-01 5.97240269e-01 -5.84668040e-01
4.65196311e-01 -5.82999997e-02 2.96831846e-01 -4.31497842e-01
7.60421276e-01 -6.26768768e-01 2.72515923e-01 3.92884649e-02
-9.83626842e-02 2.46840373e-01 -4.39798757e-02 6.69580460e-01
-1.95197463e-01 -4.32103127e-01 6.30011320e-01 -2.25334793e-01
-7.50545561e-01 3.92328411e-01 -1.35819942e-01 -3.30773652e-01
1.01345730e+00 -4.53024268e-01 -1.63978010e-01 -7.97187388e-01
-8.33160579e-01 1.42710775e-01 5.75192153e-01 2.04447329e-01
8.80289674e-01 -1.16755629e+00 -8.80669534e-01 -7.54437372e-02
1.22594371e-01 -3.83816004e-01 5.42776525e-01 8.09696019e-01
-3.74761671e-01 -3.95087451e-02 -2.09269404e-01 -4.61298972e-01
-1.86395621e+00 5.63644111e-01 -5.33352196e-02 -1.56247139e-01
-5.93615472e-01 7.13830590e-01 5.32222632e-03 3.44330519e-01
1.93403050e-01 6.04980111e-01 -3.59628409e-01 5.02532899e-01
1.01623344e+00 4.29928333e-01 1.46144152e-01 -9.56360996e-01
-4.14052278e-01 4.27443832e-01 -5.65624356e-01 -3.82385015e-01
1.31713450e+00 -1.57254830e-01 -1.41267225e-01 -8.75875130e-02
9.48785663e-01 -5.49083948e-02 -1.11067104e+00 -3.11198801e-01
1.80734158e-01 -9.45255816e-01 -1.11989819e-01 -5.60871661e-01
-1.34640169e+00 9.26337659e-01 6.41310751e-01 -8.26442689e-02
1.31081855e+00 1.65273800e-01 5.62456965e-01 5.68283737e-01
6.20572269e-01 -9.35937583e-01 3.92480910e-01 -1.57609776e-01
9.61052656e-01 -1.18312097e+00 3.04915518e-01 -2.18109623e-01
-9.08479810e-01 1.14468420e+00 2.35400811e-01 4.83465679e-02
3.61422032e-01 -6.65063709e-02 2.86305398e-01 -5.10522902e-01
-9.28458929e-01 -2.39775822e-01 1.92546263e-01 4.18277770e-01
2.35644907e-01 -2.72258818e-01 -3.77646148e-01 1.86501946e-02
5.03955334e-02 -1.04940355e-01 2.59913743e-01 1.05240285e+00
-3.27228189e-01 -1.52025044e+00 -7.05965817e-01 3.29856247e-01
-8.97244453e-01 3.43714990e-02 -6.08161986e-01 6.96930230e-01
-1.24159567e-01 1.15159130e+00 -1.35989398e-01 -4.95766196e-03
1.33666754e-01 2.32295796e-01 5.96616447e-01 -3.48069072e-01
-5.54278731e-01 3.94031517e-02 9.16284099e-02 -6.44405723e-01
-5.61119199e-01 -1.19187689e+00 -7.46075690e-01 -3.02159578e-01
-1.57519490e-01 1.96883097e-01 4.36673164e-01 7.51250565e-01
2.84206510e-01 -2.75264680e-01 6.22047365e-01 -9.29135382e-01
-4.15072054e-01 -8.82693529e-01 -4.03655618e-01 8.78385961e-01
5.67739690e-03 -7.12361932e-01 3.01941894e-02 2.89944798e-01] | [12.863560676574707, 1.0189911127090454] |
fb1cf2a4-0421-4445-8e26-fc6d3942ee21 | where-did-you-learn-that-from-surprising | 2109.03975 | null | https://arxiv.org/abs/2109.03975v3 | https://arxiv.org/pdf/2109.03975v3.pdf | Membership Inference Attacks Against Temporally Correlated Data in Deep Reinforcement Learning | While significant research advances have been made in the field of deep reinforcement learning, there have been no concrete adversarial attack strategies in literature tailored for studying the vulnerability of deep reinforcement learning algorithms to membership inference attacks. In such attacking systems, the adversary targets the set of collected input data on which the deep reinforcement learning algorithm has been trained. To address this gap, we propose an adversarial attack framework designed for testing the vulnerability of a state-of-the-art deep reinforcement learning algorithm to a membership inference attack. In particular, we design a series of experiments to investigate the impact of temporal correlation, which naturally exists in reinforcement learning training data, on the probability of information leakage. Moreover, we compare the performance of \emph{collective} and \emph{individual} membership attacks against the deep reinforcement learning algorithm. Experimental results show that the proposed adversarial attack framework is surprisingly effective at inferring data with an accuracy exceeding $84\%$ in individual and $97\%$ in collective modes in three different continuous control Mujoco tasks, which raises serious privacy concerns in this regard. Finally, we show that the learning state of the reinforcement learning algorithm influences the level of privacy breaches significantly. | ['Doina Precup', 'Alexander Wong', 'Hossein Aboutalebi', 'Susan Amin', 'Maziar Gomrokchi'] | 2021-09-08 | null | null | null | null | ['membership-inference-attack'] | ['computer-vision'] | [-1.08040139e-01 1.62877724e-01 1.34176850e-01 -1.18052468e-01
-5.64774036e-01 -9.19716537e-01 4.92094159e-01 2.11256102e-01
-5.44307947e-01 8.45410168e-01 -5.57573080e-01 -6.69921637e-01
-1.21135838e-01 -1.18669534e+00 -1.15007329e+00 -8.74038279e-01
-5.50480485e-01 2.41996907e-02 -1.51358426e-01 -1.10942543e-01
2.78364718e-02 3.63105088e-01 -1.06573761e+00 -3.83352786e-02
5.81957877e-01 1.14026332e+00 -7.61485875e-01 5.29506445e-01
5.13867915e-01 9.49784636e-01 -1.16199136e+00 -7.17599392e-01
7.23373175e-01 -3.51041526e-01 -7.39290774e-01 -3.41507018e-01
3.33034307e-01 -8.39354455e-01 -6.50485098e-01 1.49328458e+00
4.07801121e-01 7.24206045e-02 2.02647716e-01 -1.54704726e+00
-3.58564317e-01 8.97963583e-01 -3.13995987e-01 7.31864423e-02
1.90044940e-02 5.39094746e-01 8.42809200e-01 2.93288212e-02
1.40770495e-01 9.10075009e-01 3.96061659e-01 6.39166415e-01
-9.84049857e-01 -1.28705871e+00 7.31005147e-02 -1.10348076e-01
-1.17579031e+00 -2.20100120e-01 6.49023235e-01 -2.89440572e-01
5.58780134e-01 7.30323493e-02 3.19432467e-01 1.42846835e+00
5.12102664e-01 5.44771731e-01 1.38698041e+00 -4.42844667e-02
7.27365792e-01 1.18528754e-01 8.95132273e-02 8.28381777e-01
1.53558969e-01 9.41074491e-01 -2.80611277e-01 -5.96174121e-01
6.18386507e-01 -1.38416529e-01 8.38764310e-02 -2.67693311e-01
-5.23673117e-01 9.52392578e-01 2.76623130e-01 -4.20962945e-02
-2.25290850e-01 5.58579504e-01 7.57919788e-01 8.19682837e-01
-8.41285847e-03 5.00974536e-01 -3.75779450e-01 -3.79161686e-02
-2.89569020e-01 4.15244818e-01 8.59665930e-01 8.03416073e-01
5.29719710e-01 3.87303293e-01 -9.47769731e-02 -3.25887948e-02
7.70323724e-02 4.05332953e-01 2.23357618e-01 -9.75024760e-01
5.33031523e-01 2.05422878e-01 9.05941203e-02 -1.06550837e+00
-2.04272896e-01 -4.66358513e-01 -6.37106717e-01 5.42526603e-01
6.23968720e-01 -9.31330502e-01 -2.79089272e-01 2.00853539e+00
4.04336751e-01 1.54708952e-01 5.41833341e-01 7.36232042e-01
3.10405612e-01 2.44503140e-01 1.38001904e-01 -1.58184931e-01
1.04974592e+00 -4.07441378e-01 -5.83349049e-01 1.12620391e-01
4.50700730e-01 -2.98244327e-01 8.82602990e-01 2.31619522e-01
-9.79247808e-01 -4.86903429e-01 -1.34099960e+00 6.41855061e-01
-4.62713540e-01 -4.53172475e-01 7.23924935e-01 1.19610262e+00
-4.36708510e-01 6.99524760e-01 -7.73408830e-01 2.55973309e-01
7.67430961e-01 6.45639062e-01 -1.17757842e-01 3.20414960e-01
-1.73513877e+00 5.45233130e-01 3.36869717e-01 -1.64605096e-01
-1.62010562e+00 -6.53966486e-01 -5.37867248e-01 5.60622327e-02
6.73150778e-01 -3.71823967e-01 1.15225613e+00 -1.01111758e+00
-1.58400702e+00 4.76637602e-01 7.77575552e-01 -1.19243753e+00
8.14087391e-01 -1.97371081e-01 -5.91316104e-01 8.47190544e-02
-3.75911504e-01 2.86364369e-02 1.18240941e+00 -1.03580713e+00
-7.18658030e-01 -6.84659004e-01 6.72675014e-01 -4.88583446e-02
-4.38620597e-01 -2.48239741e-01 4.29732591e-01 -6.16617262e-01
-8.10931265e-01 -1.01727569e+00 -2.65860677e-01 -3.55144799e-01
-3.71361911e-01 -1.75957039e-01 1.05222547e+00 -1.19714864e-01
1.03194487e+00 -2.41559458e+00 -3.45097333e-01 5.38573861e-01
1.39769927e-01 4.46073622e-01 -1.73739400e-02 5.05157769e-01
1.46454036e-01 1.21976800e-01 -9.59252417e-02 5.26820570e-02
3.86982560e-01 1.98044062e-01 -8.44199479e-01 8.20514381e-01
-1.09257042e-01 7.27335334e-01 -6.24259651e-01 7.92484581e-02
-4.52752132e-03 1.14614852e-01 -5.86237431e-01 6.69151485e-01
-3.49330246e-01 3.75442386e-01 -7.43033648e-01 3.60909909e-01
6.37549520e-01 1.37600034e-01 2.64270484e-01 3.20815295e-01
3.17942470e-01 -4.53058966e-02 -9.48384166e-01 1.20779419e+00
-2.16673642e-01 2.31153637e-01 1.43115908e-01 -1.14491487e+00
8.41592848e-01 4.41593945e-01 4.76398170e-01 -7.22469091e-01
4.29224640e-01 -2.00800493e-01 2.70886004e-01 -1.26807615e-01
3.47695619e-01 -8.55393261e-02 -4.67620462e-01 6.76284432e-01
-7.85133094e-02 1.02280088e-01 -2.76959121e-01 -8.35206285e-02
1.44452786e+00 -1.96117967e-01 -3.11971884e-02 -3.59218478e-01
4.99600738e-01 -2.53617644e-01 4.63458151e-01 1.13178325e+00
-7.03561306e-01 -2.86369145e-01 6.96696639e-01 -4.28207278e-01
-7.05365181e-01 -1.21936381e+00 -1.63753945e-02 9.75590885e-01
2.00476930e-01 -2.20854267e-01 -1.23023844e+00 -1.24178243e+00
2.73737758e-01 6.45234168e-01 -8.30088615e-01 -5.69741726e-01
-3.37422341e-01 -6.37302876e-01 1.36599529e+00 3.90876770e-01
9.03607845e-01 -1.18515849e+00 -9.21803534e-01 9.31068733e-02
3.27676117e-01 -1.14022732e+00 -2.51044571e-01 3.05261344e-01
-6.04746401e-01 -1.47312713e+00 6.66348338e-02 -4.81615365e-01
5.24614155e-01 -4.18714285e-01 7.48908579e-01 -7.26485103e-02
-7.41949230e-02 6.66937113e-01 -7.57453367e-02 -6.60892844e-01
-8.03726554e-01 -3.64730991e-02 3.87589633e-01 2.17719320e-02
4.52148974e-01 -5.15328586e-01 -5.26286483e-01 1.63806766e-01
-1.04129851e+00 -8.60194564e-01 1.82416990e-01 8.07785332e-01
1.53688192e-01 5.60297132e-01 1.01386535e+00 -1.14876664e+00
1.04210925e+00 -4.29400891e-01 -1.17722690e+00 -7.35438755e-03
-6.19800508e-01 3.56373517e-03 1.31950188e+00 -3.72980684e-01
-5.62292278e-01 -3.38633992e-02 -2.39899665e-01 -5.49718201e-01
-2.80637056e-01 2.02498823e-01 -1.07981406e-01 -1.84349239e-01
6.96134329e-01 2.80656546e-01 3.63847464e-01 1.45540908e-02
1.77387685e-01 3.63529563e-01 4.14834470e-01 -7.60754526e-01
9.66863334e-01 3.26443166e-01 2.22969145e-01 -6.16707683e-01
-4.84060347e-01 3.56162578e-01 -1.37636894e-02 -1.51438057e-01
7.08434284e-01 -7.65503824e-01 -1.52460504e+00 7.75956333e-01
-6.19340658e-01 -4.38356698e-01 -3.49780113e-01 1.53939292e-01
-8.78508031e-01 3.48005503e-01 -6.20597064e-01 -7.17937708e-01
-4.47843254e-01 -1.37043524e+00 2.59559482e-01 1.40700415e-01
1.11737758e-01 -9.07603800e-01 -3.63196060e-02 3.69095534e-01
2.64850020e-01 5.57480216e-01 8.58209014e-01 -1.00287640e+00
-5.67540526e-01 -2.57742733e-01 2.89843649e-01 6.00708306e-01
-3.97157818e-02 -1.82583764e-01 -1.16165638e+00 -7.32367218e-01
4.09786642e-01 -7.93655336e-01 2.57144392e-01 -4.11842763e-02
1.46973312e+00 -8.27571630e-01 3.05423051e-01 4.69870627e-01
1.27160263e+00 4.49809730e-01 5.42838097e-01 1.94967479e-01
2.96922803e-01 2.81417161e-01 6.43928111e-01 7.57952631e-01
-1.99477360e-01 3.10317218e-01 1.00164080e+00 2.26245761e-01
7.81642199e-01 -3.29075277e-01 7.19167054e-01 -8.74861926e-02
3.12237799e-01 2.08088607e-02 -4.19485718e-01 1.01912141e-01
-1.57458341e+00 -9.55078006e-01 4.90223914e-01 2.22605515e+00
8.98419917e-01 2.88972259e-01 3.12894702e-01 1.48659170e-01
3.28737706e-01 1.96117371e-01 -7.65636861e-01 -8.04892719e-01
2.00831786e-01 4.96889800e-01 7.49053061e-01 2.77733624e-01
-1.36052001e+00 8.19802880e-01 5.62300253e+00 7.64624834e-01
-1.08740532e+00 -2.09117264e-01 6.96780443e-01 8.34235623e-02
3.97292785e-02 -2.38643020e-01 -5.29248476e-01 4.94605452e-01
1.14885867e+00 -2.28797555e-01 6.65017188e-01 9.55671191e-01
-1.73564181e-01 1.56151041e-01 -1.29298711e+00 5.23278236e-01
-3.77587944e-01 -1.27342498e+00 -2.30359733e-01 3.84893268e-01
5.14177978e-01 -2.24531978e-01 7.31216908e-01 5.63649654e-01
9.06024158e-01 -1.20541477e+00 3.87894392e-01 1.69259131e-01
4.43938822e-01 -1.56706429e+00 6.29338562e-01 4.92365658e-01
-6.14908993e-01 -4.02043313e-01 -2.62602806e-01 -1.09528616e-01
-7.01066017e-01 8.52351263e-02 -7.28872240e-01 4.71387684e-01
6.08837724e-01 1.43151330e-02 -3.95862401e-01 2.08739340e-01
-1.19765364e-01 7.90978730e-01 -1.23614021e-01 -1.35466874e-01
5.94433010e-01 -7.84556568e-02 4.05707479e-01 6.36308789e-01
-1.52465165e-01 1.18704341e-01 2.65725672e-01 9.21301365e-01
-4.40561712e-01 -1.86056182e-01 -9.63025451e-01 -1.90230727e-01
5.37167013e-01 8.33324075e-01 -2.36117430e-02 8.77606273e-02
-1.89869687e-01 7.46942461e-01 3.76957595e-01 2.64514953e-01
-1.18161869e+00 -1.41883612e-01 1.04308963e+00 -2.07650930e-01
2.84965307e-01 -1.87480167e-01 -5.01456447e-02 -6.58477962e-01
-2.47036405e-02 -1.35952365e+00 6.88805819e-01 1.64345846e-01
-1.46279812e+00 3.71611714e-01 -3.37156922e-01 -9.83218253e-01
-3.70723367e-01 -3.41794103e-01 -5.35166323e-01 6.14894152e-01
-1.07768464e+00 -6.20141268e-01 3.55097175e-01 1.13526273e+00
-5.33400998e-02 -8.08694899e-01 1.09264028e+00 1.46560036e-02
-7.70564437e-01 1.46149468e+00 3.34120750e-01 7.43352234e-01
3.97661686e-01 -9.96842086e-01 2.37826377e-01 9.91564751e-01
7.16598928e-02 6.42271578e-01 5.94148219e-01 -3.42952281e-01
-1.75127065e+00 -1.32181931e+00 -1.42110482e-01 -3.90667737e-01
8.28599393e-01 -3.71694773e-01 -6.57446802e-01 6.59091532e-01
3.37889165e-01 2.97845662e-01 7.82914340e-01 -9.32029188e-02
-4.49444413e-01 -2.94206709e-01 -1.65901494e+00 7.19803810e-01
4.75020885e-01 -7.45863497e-01 -2.53168732e-01 4.14248072e-02
8.29826355e-01 -5.34549117e-01 -1.26854658e+00 2.94333220e-01
3.71182770e-01 -1.01284707e+00 8.43056798e-01 -1.06286764e+00
3.95744532e-01 -3.12786549e-02 -2.33361736e-01 -1.15171373e+00
2.62786865e-01 -9.06404436e-01 -4.01268035e-01 9.31030035e-01
1.99025229e-01 -7.50532687e-01 1.12166286e+00 6.54111207e-01
2.69031495e-01 -5.79020917e-01 -1.16132724e+00 -8.00842404e-01
7.20188558e-01 -2.63497263e-01 7.17895210e-01 1.07199395e+00
-2.03526970e-02 -3.79101485e-02 -4.65353996e-01 5.70648015e-01
8.40397596e-01 1.24204636e-01 9.98050034e-01 -5.28191447e-01
-5.19896865e-01 -2.16909319e-01 -2.89037555e-01 -3.97538543e-01
3.86812449e-01 -5.48809528e-01 -2.68428385e-01 -2.53326923e-01
-3.93415362e-01 -4.80655581e-01 -6.33625388e-01 5.01678169e-01
2.36546602e-02 -3.06149870e-02 3.35749865e-01 -2.15109512e-01
-5.02060831e-01 5.80145717e-01 1.04628623e+00 -2.64388651e-01
1.19237639e-02 4.40558702e-01 -6.06420338e-01 5.50099075e-01
1.02982104e+00 -4.43456411e-01 -6.10431910e-01 7.24122673e-02
-1.30953668e-02 2.99134791e-01 5.20077169e-01 -1.15351701e+00
1.36481509e-01 -2.25354686e-01 1.24774948e-01 -1.29036397e-01
-6.27175346e-02 -1.29658628e+00 -6.23014979e-02 7.50090420e-01
-7.28343427e-01 1.38433382e-01 3.38104755e-01 7.74654925e-01
4.10817750e-02 -1.27147377e-01 9.59052563e-01 -2.88431067e-02
-2.40092069e-01 6.04088068e-01 -5.06549656e-01 3.71327102e-01
1.47492671e+00 2.86462456e-01 -3.51862580e-01 -2.54660219e-01
-5.41876197e-01 3.39278489e-01 2.59423465e-01 3.82887214e-01
5.70665359e-01 -1.06654942e+00 -4.05184060e-01 4.70936894e-01
-5.59870116e-02 -2.00269714e-01 1.14631832e-01 2.21029237e-01
-1.61802083e-01 3.69825512e-02 -5.30159712e-01 -9.37163085e-02
-1.10241854e+00 1.00200796e+00 7.30379581e-01 -3.59600961e-01
-4.68403518e-01 5.26700079e-01 5.07177897e-02 -3.47740471e-01
7.95407295e-01 -1.03779957e-01 1.24328770e-01 -3.25256109e-01
3.98272693e-01 3.60220909e-01 9.39850137e-02 -7.23329186e-02
-1.88903511e-01 -2.33938769e-01 -2.84671634e-01 2.38800440e-02
8.58271956e-01 2.44565502e-01 2.18742922e-01 5.69951758e-02
1.18933201e+00 -3.28959040e-02 -1.46565950e+00 -2.03594044e-01
-4.42216903e-01 -2.89193392e-01 -1.94193259e-01 -7.67065644e-01
-1.35583436e+00 8.70627403e-01 8.42970133e-01 5.47383964e-01
9.93269503e-01 -7.10828424e-01 8.51175785e-01 6.66631043e-01
5.46184301e-01 -1.22352517e+00 8.57390538e-02 6.01150692e-01
4.25853699e-01 -1.11336470e+00 -2.90629864e-01 2.69567430e-01
-5.88174701e-01 7.40701199e-01 8.07323813e-01 -5.19691706e-01
9.25128162e-01 5.02404749e-01 1.65418372e-01 -1.42871425e-01
-6.00123405e-01 3.89942765e-01 -2.78898835e-01 5.88396549e-01
-1.80139512e-01 2.43509799e-01 -7.27173686e-02 8.27161908e-01
-2.81837702e-01 -1.82851404e-01 6.85973108e-01 8.81159067e-01
-3.95468734e-02 -1.04138064e+00 -1.97912872e-01 1.86885685e-01
-1.05104530e+00 1.38921857e-01 -4.93466467e-01 8.44572425e-01
-2.32442468e-02 9.69084680e-01 -1.61723560e-03 -6.21183753e-01
2.49657527e-01 -1.03695892e-01 3.08339506e-01 -5.78769483e-02
-1.24862111e+00 -5.62245250e-01 -2.85892561e-02 -7.27446735e-01
-1.11586250e-01 -5.57258606e-01 -1.35796225e+00 -7.55225122e-01
1.37032375e-01 3.15020055e-01 2.26663783e-01 9.28636491e-01
2.43358836e-01 5.30067027e-01 1.19202340e+00 1.52327418e-01
-1.51383662e+00 -4.58635479e-01 -7.55684853e-01 4.83613819e-01
4.94792849e-01 -4.24304754e-01 -3.54666829e-01 -5.75669825e-01] | [5.669051647186279, 7.541394233703613] |
bd3d0735-02c9-4710-8c06-fa403e68cf37 | using-adaptive-experiments-to-rapidly-help | 2208.05092 | null | https://arxiv.org/abs/2208.05092v1 | https://arxiv.org/pdf/2208.05092v1.pdf | Using Adaptive Experiments to Rapidly Help Students | Adaptive experiments can increase the chance that current students obtain better outcomes from a field experiment of an instructional intervention. In such experiments, the probability of assigning students to conditions changes while more data is being collected, so students can be assigned to interventions that are likely to perform better. Digital educational environments lower the barrier to conducting such adaptive experiments, but they are rarely applied in education. One reason might be that researchers have access to few real-world case studies that illustrate the advantages and disadvantages of these experiments in a specific context. We evaluate the effect of homework email reminders in students by conducting an adaptive experiment using the Thompson Sampling algorithm and compare it to a traditional uniform random experiment. We present this as a case study on how to conduct such experiments, and we raise a range of open questions about the conditions under which adaptive randomized experiments may be more or less useful. | ['Joseph Jay Williams', 'Andrew Petersen', 'Anna Rafferty', 'Jacob Nogas', 'Hammad Shaikh', 'Qi Yin Zheng', 'Angela Zavaleta-Bernuy'] | 2022-08-10 | null | null | null | null | ['thompson-sampling'] | ['methodology'] | [ 4.04325187e-01 1.04591183e-01 -4.59530175e-01 -3.90284657e-01
-3.24983388e-01 -6.44664526e-01 4.91355121e-01 4.77740973e-01
-8.00576568e-01 9.37502444e-01 2.79612869e-01 -1.15621531e+00
-4.00361478e-01 -9.01019931e-01 -9.22688127e-01 -3.20269525e-01
2.87582487e-01 1.45409524e-01 4.51171696e-01 2.02870056e-01
8.46233666e-01 4.47686374e-01 -2.24408460e+00 -9.30688009e-02
1.22528005e+00 -3.23168576e-01 4.98227179e-01 5.48063576e-01
-2.21698895e-01 6.69019222e-01 -9.81194675e-01 -3.76224630e-02
-7.37510026e-02 -8.24437797e-01 -7.87577808e-01 1.24210052e-01
7.20321655e-01 -5.71835220e-01 8.95316675e-02 8.41196954e-01
8.35847259e-01 7.59729207e-01 2.47988030e-01 -1.38154674e+00
-4.94511396e-01 7.41606116e-01 -4.04316515e-01 3.84654731e-01
8.40510428e-01 2.36055270e-01 4.87237036e-01 1.02291688e-01
7.67677248e-01 1.37194419e+00 3.85258496e-01 1.32490262e-01
-1.45234978e+00 -7.02610433e-01 4.08203423e-01 1.89337283e-01
-8.12776744e-01 -3.06151479e-01 1.91322371e-01 -2.27286682e-01
4.49494988e-01 3.91688943e-01 1.02396786e+00 1.03380704e+00
3.10950279e-01 5.13009965e-01 1.60679376e+00 -6.85268819e-01
5.82619786e-01 6.47175908e-01 1.88608453e-01 2.97285855e-01
9.32290971e-01 1.58032626e-01 -5.04789889e-01 -3.38798106e-01
7.13747680e-01 2.09489673e-01 -2.92070538e-01 -5.29505193e-01
-9.24839258e-01 8.38094592e-01 7.86398873e-02 5.28127134e-01
-3.51042718e-01 -1.23395331e-01 6.84398189e-02 5.32141209e-01
1.51626887e-02 8.39122891e-01 -3.97377551e-01 -5.75604677e-01
-7.33724952e-01 6.74018323e-01 8.26666534e-01 5.68907082e-01
4.96389270e-01 -4.31971133e-01 -1.98126674e-01 4.69837934e-01
3.80221456e-01 1.57858625e-01 6.51392877e-01 -1.12260616e+00
1.36109725e-01 3.91236067e-01 5.20762861e-01 -5.25479794e-01
2.13252101e-02 1.35937437e-01 2.80360907e-01 4.77943778e-01
8.58313024e-01 -5.29470444e-01 -4.46107477e-01 1.62961125e+00
6.04416847e-01 2.12996274e-01 -3.19674313e-01 4.94293332e-01
3.80350083e-01 3.57083231e-01 2.82412022e-01 -4.55128014e-01
1.15276849e+00 -4.18019801e-01 -9.97614920e-01 -7.32553005e-02
1.07634795e+00 -1.18724549e+00 1.58210802e+00 2.29685843e-01
-1.14106262e+00 -3.14361870e-01 -7.17316628e-01 4.35113221e-01
-2.87858635e-01 -7.96006560e-01 6.54953659e-01 1.40685523e+00
-8.64704013e-01 8.89241159e-01 -7.52408266e-01 -7.60697901e-01
5.73717654e-02 8.85068846e-04 5.17611764e-02 -2.30014533e-01
-9.83204663e-01 8.09118330e-01 -2.27324381e-01 -4.36432928e-01
-3.77317131e-01 -1.06549931e+00 -5.93945146e-01 3.44064742e-01
4.46702003e-01 -4.24126983e-01 1.57743645e+00 -7.92992771e-01
-1.61007357e+00 4.11139578e-01 -8.82705003e-02 8.67938921e-02
4.78495538e-01 -8.67897496e-02 2.52335966e-01 -2.17527375e-01
3.15395057e-01 3.66117030e-01 9.16863680e-02 -8.74336600e-01
-6.92630172e-01 -4.04931217e-01 1.64453670e-01 3.80978256e-01
-3.61896515e-01 3.69819194e-01 4.36677545e-01 -3.51338655e-01
-1.17529921e-01 -9.26240563e-01 -5.18879712e-01 -4.71598059e-01
3.15966368e-01 -3.97145331e-01 7.14897513e-01 1.81317553e-01
1.08174515e+00 -1.79879761e+00 -7.96400726e-01 7.03500882e-02
-1.42101482e-01 4.70836721e-02 1.64662506e-02 6.58595800e-01
-1.29896536e-01 5.62813044e-01 5.42556465e-01 5.53437412e-01
1.91164613e-01 -1.59417361e-01 1.05946384e-01 3.28924745e-01
-3.72771770e-01 2.14954615e-01 -1.08856690e+00 -5.30472994e-01
2.31200337e-01 7.47524574e-02 -7.97890484e-01 2.83890545e-01
1.84073970e-01 1.74956679e-01 -5.45503139e-01 2.18567229e-03
4.71929967e-01 -3.42376865e-02 3.85900736e-01 8.84304821e-01
-6.14883065e-01 8.47396135e-01 -1.47447991e+00 8.46620560e-01
-3.55362564e-01 8.13731074e-01 -2.10042968e-01 -8.58936608e-01
4.97275531e-01 4.10637766e-01 8.70522857e-02 -7.19698489e-01
3.46652791e-02 -1.39627099e-01 4.12951559e-01 -8.61039102e-01
5.77888548e-01 -1.49070963e-01 3.51592749e-01 1.18340063e+00
-2.42520735e-01 -3.96866024e-01 2.49622434e-01 2.29091182e-01
1.31884611e+00 5.53696565e-02 1.80758446e-01 -4.65221584e-01
-3.33441168e-01 -1.19401470e-01 4.31291610e-01 1.54170454e+00
-4.41850692e-01 -4.62998040e-02 4.84241098e-01 -9.48532671e-02
-8.52755666e-01 -6.68854833e-01 -3.23687047e-01 1.42130148e+00
-1.69601902e-01 -2.00600743e-01 -8.40169966e-01 -7.78719246e-01
1.97856966e-02 1.29442775e+00 -4.00703520e-01 -2.04488993e-01
-1.00938775e-01 -5.39722145e-01 1.29893292e-02 2.56824881e-01
2.14222968e-01 -1.10811937e+00 -1.10160184e+00 1.98964655e-01
-1.43867941e-03 -4.85238582e-01 -4.16805089e-01 6.30067065e-02
-1.13782442e+00 -9.84721541e-01 -4.38407511e-01 -6.35002613e-01
8.54928792e-01 8.15553427e-01 1.03731370e+00 4.20114458e-01
-1.41531631e-01 8.41892660e-01 -4.14524555e-01 -8.84484231e-01
-4.02871490e-01 -1.84744388e-01 2.00709268e-01 -7.42375672e-01
7.03629613e-01 -5.29410899e-01 -6.40764892e-01 3.42545331e-01
-9.20394540e-01 -4.22374725e-01 4.44511861e-01 7.09546626e-01
-1.94092855e-01 3.53141367e-01 8.20675552e-01 -1.26269805e+00
9.88178134e-01 -3.77248228e-01 -7.31055856e-01 1.10468306e-01
-8.92192960e-01 -1.85971931e-01 3.17149758e-01 -9.29892182e-01
-1.21482933e+00 -4.16919529e-01 2.56615251e-01 2.52488017e-01
-6.09679878e-01 4.94470984e-01 -4.19881307e-02 -2.02998966e-01
8.79111171e-01 -4.34767902e-01 7.90195391e-02 -1.66278154e-01
-1.40443206e-01 7.20438421e-01 -6.25218511e-01 -9.98082459e-01
4.82157648e-01 -3.77684444e-01 -2.12973192e-01 -8.31358612e-01
-5.60763240e-01 4.42592427e-03 -2.40645632e-01 -4.77150142e-01
3.91503692e-01 -5.17971933e-01 -1.04062784e+00 -9.94785130e-02
-3.07749242e-01 -9.90162015e-01 -4.48606610e-01 1.16826284e+00
-4.41044033e-01 1.15286238e-01 -2.80133039e-01 -7.68961251e-01
7.44147837e-01 -1.46137750e+00 2.17108831e-01 8.62176120e-01
-7.00388312e-01 -1.01105404e+00 6.35729879e-02 5.90151191e-01
3.27099025e-01 -1.56399280e-01 7.93831766e-01 -8.22444856e-01
-4.75809634e-01 -1.37257338e-01 4.94703174e-01 -2.30238050e-01
2.05958396e-01 4.35960621e-01 -7.27933168e-01 -4.96845365e-01
2.17963140e-02 -3.32952082e-01 1.08895488e-01 7.32744753e-01
1.01565266e+00 -4.05237913e-01 -4.04655635e-01 -2.60774225e-01
1.09161019e+00 5.61429024e-01 4.71953809e-01 6.21823609e-01
1.82522051e-02 9.08761740e-01 1.04199815e+00 3.43237638e-01
2.07505852e-01 4.28069532e-01 -2.98957795e-01 2.76059240e-01
3.35605532e-01 -3.47648412e-01 5.13013303e-01 4.47047979e-01
2.58979112e-01 -2.49992937e-01 -7.67177880e-01 7.59335220e-01
-1.45276642e+00 -1.13805568e+00 -2.52213240e-01 2.76981497e+00
1.06807423e+00 4.04514045e-01 2.98319072e-01 -2.63657290e-02
9.06914473e-01 -1.54422134e-01 -1.54591396e-01 -8.45713973e-01
7.00195312e-01 3.40746135e-01 4.72594082e-01 4.31936651e-01
-3.69579405e-01 4.77939725e-01 7.59798861e+00 2.78033823e-01
-7.71588624e-01 -1.69490427e-01 7.35655606e-01 -1.65076569e-01
-5.17852485e-01 5.08518815e-01 -7.80838013e-01 4.45804715e-01
1.52095413e+00 -6.57713115e-01 1.31560475e-01 5.95503330e-01
6.45862997e-01 -7.62219846e-01 -1.22887945e+00 -8.37698057e-02
-4.48065400e-01 -9.86521304e-01 -3.87566358e-01 3.47286195e-01
9.46380258e-01 -6.08399034e-01 4.99859080e-02 4.18198407e-01
1.08682430e+00 -7.43867695e-01 3.30293119e-01 1.87456146e-01
2.41334319e-01 -5.80947816e-01 4.75065023e-01 4.99618143e-01
-2.62569189e-01 4.86894809e-02 -2.66074866e-01 -7.81066358e-01
-5.47779441e-01 2.33147651e-01 -1.24385417e+00 -2.19698980e-01
7.85720408e-01 -2.57888436e-01 -5.33189893e-01 1.56501520e+00
-2.00580373e-01 1.33551514e+00 -1.20378472e-01 -7.93448448e-01
1.74570709e-01 -2.31219232e-01 2.61791199e-01 6.21145487e-01
4.94567662e-01 2.58536607e-01 -4.80831042e-02 6.06363237e-01
2.56212354e-01 2.39033625e-01 -1.10430813e+00 -1.58845142e-01
1.02411044e+00 9.05895889e-01 -1.18233037e+00 -2.34561548e-01
-4.94246900e-01 2.74373561e-01 -1.59668162e-01 3.99616510e-01
-3.48693579e-01 -6.83838725e-01 5.54233372e-01 5.12979209e-01
1.04685739e-01 1.11642860e-01 -2.73064673e-01 -6.06027901e-01
-4.43319529e-01 -1.20121217e+00 1.36889398e-01 -7.53704548e-01
-8.28167796e-01 -5.65482736e-01 3.57307583e-01 -7.58882344e-01
-7.46873207e-03 -1.60844117e-01 -8.12095046e-01 8.67330968e-01
-7.02052176e-01 1.88075840e-01 -1.08160548e-01 2.27857176e-02
3.95916432e-01 3.55916053e-01 6.02885783e-01 -4.24842983e-02
-6.17361248e-01 6.92674577e-01 3.99131894e-01 -5.23059011e-01
1.32990229e+00 -1.36719728e+00 1.66906323e-02 7.95877218e-01
-2.76023388e-01 1.09207475e+00 1.00318801e+00 -8.52182508e-01
-1.21085370e+00 -5.07947862e-01 7.25593030e-01 -4.35574293e-01
4.73457605e-01 -2.06434757e-01 -1.01071727e+00 9.87819016e-01
4.21290964e-01 -5.19395649e-01 9.82897878e-01 5.94863594e-01
3.81114304e-01 2.32047305e-01 -1.40393627e+00 1.11020648e+00
9.29397404e-01 -2.92613685e-01 -5.60616732e-01 3.93502504e-01
8.00077915e-01 -3.65261406e-01 -1.12697256e+00 -2.24377111e-01
5.25434375e-01 -9.98872757e-01 5.73638856e-01 -6.92681789e-01
4.59024101e-01 1.31023139e-01 3.91546875e-01 -1.62074363e+00
-3.42079371e-01 -8.38027418e-01 7.78742135e-01 1.45587909e+00
2.52439380e-01 -8.89325440e-01 9.37247694e-01 1.09925640e+00
2.42722407e-01 -5.11468887e-01 -2.91418046e-01 -6.00235820e-01
3.81461740e-01 7.22790584e-02 8.87619555e-01 1.48735869e+00
3.23463798e-01 9.87777263e-02 4.00000304e-01 -3.32323313e-02
5.42429805e-01 -1.72391385e-02 9.21562254e-01 -1.17392802e+00
4.26645316e-02 -4.41858500e-01 -2.85380781e-01 -6.49215639e-01
-5.23226075e-02 -2.14253545e-01 6.53087050e-02 -1.37604439e+00
3.38165313e-01 -5.70735872e-01 -2.61417385e-02 1.96185797e-01
-6.63973689e-01 -5.66112936e-01 1.18575521e-01 -4.52263236e-01
-4.10003304e-01 1.63815558e-01 1.44530511e+00 5.51534474e-01
-6.65624440e-01 3.52013558e-01 -1.06270719e+00 5.48774362e-01
6.59567356e-01 -5.48245728e-01 -6.56405747e-01 1.65784225e-01
1.98355522e-02 2.27874562e-01 -1.59186676e-01 -7.95526147e-01
3.25086564e-01 -9.15723443e-01 4.07046258e-01 5.95115265e-03
-6.27954006e-01 -8.24233413e-01 9.05123502e-02 5.33969522e-01
-7.71495402e-01 2.99381554e-01 4.99187768e-01 2.41638362e-01
2.70451218e-01 -9.13524926e-01 5.97541749e-01 -1.74031198e-01
-1.27564505e-01 -3.68653536e-01 -1.36485958e+00 1.44108295e-01
1.33969998e+00 -4.67444837e-01 -3.69179338e-01 -7.39107132e-01
-3.75234842e-01 2.18086898e-01 8.38048756e-01 2.23051310e-01
1.02383524e-01 -1.04439557e+00 -2.35467225e-01 1.84000060e-02
-1.85399622e-01 -3.32564831e-01 1.68509498e-01 7.27073729e-01
-3.82267743e-01 3.84088635e-01 -3.22617233e-01 -2.10982487e-01
-1.58914816e+00 4.75160271e-01 1.17110528e-01 3.01071268e-04
-4.22915846e-01 6.48742735e-01 5.16490117e-02 -6.75815940e-01
4.47374493e-01 -2.78335065e-01 -2.25676656e-01 1.48293853e-01
5.92109263e-01 5.43590248e-01 6.17361218e-02 2.37847358e-01
4.04264182e-02 -2.47857019e-01 -4.45507169e-01 -3.34330231e-01
1.31328070e+00 -1.88743949e-01 2.22935691e-01 6.69827580e-01
5.98318338e-01 3.50592911e-01 -1.20412242e+00 -1.61639735e-01
-1.60294041e-01 -1.08813632e+00 2.43796125e-01 -7.57868171e-01
-4.18233156e-01 3.95839781e-01 7.37716675e-01 6.11535847e-01
8.90915275e-01 -4.50892776e-01 9.14665463e-04 4.72147107e-01
2.22215101e-01 -1.23804629e+00 9.23968554e-02 5.65470494e-02
2.30257839e-01 -1.03270447e+00 2.85872757e-01 1.38085848e-02
-3.18470716e-01 8.14312994e-01 7.81579554e-01 2.51462698e-01
3.87288272e-01 9.72160921e-02 -8.60681757e-02 -5.86205348e-02
-1.01362348e+00 1.64421722e-01 -4.75657851e-01 5.52645802e-01
1.02636456e+00 7.79296309e-02 -9.59179759e-01 3.06661613e-02
-4.52316552e-01 3.35223943e-01 1.45067704e+00 1.55951047e+00
-5.83874822e-01 -1.39843369e+00 -9.85160828e-01 8.11972082e-01
-6.33857131e-01 2.32854247e-01 -4.34818983e-01 9.84737694e-01
-3.06895822e-01 1.21489465e+00 3.32281947e-01 3.27754356e-02
3.28574270e-01 3.79678220e-01 6.34851933e-01 -7.89548516e-01
-6.70480669e-01 -3.04805905e-01 6.63866401e-02 -3.60034853e-01
-3.04227442e-01 -1.29250455e+00 -7.94940054e-01 -8.87427151e-01
-7.25023568e-01 5.31553268e-01 4.67696220e-01 7.76435077e-01
3.26503456e-01 7.48647571e-01 7.11855590e-01 -4.63361025e-01
-6.35237873e-01 -8.21417212e-01 -6.03522837e-01 1.56052634e-01
-6.65966645e-02 -7.40008414e-01 -5.22905529e-01 -3.43385726e-01] | [10.181479454040527, 7.174191951751709] |
9a393467-3af6-42b8-a541-3105784446ca | game-up-game-aware-mode-enumeration-and | 2305.17600 | null | https://arxiv.org/abs/2305.17600v1 | https://arxiv.org/pdf/2305.17600v1.pdf | GAME-UP: Game-Aware Mode Enumeration and Understanding for Trajectory Prediction | Interactions between road agents present a significant challenge in trajectory prediction, especially in cases involving multiple agents. Because existing diversity-aware predictors do not account for the interactive nature of multi-agent predictions, they may miss these important interaction outcomes. In this paper, we propose GAME-UP, a framework for trajectory prediction that leverages game-theoretic inverse reinforcement learning to improve coverage of multi-modal predictions. We use a training-time game-theoretic numerical analysis as an auxiliary loss resulting in improved coverage and accuracy without presuming a taxonomy of actions for the agents. We demonstrate our approach on the interactive subset of Waymo Open Motion Dataset, including three subsets involving scenarios with high interaction complexity. Experiment results show that our predictor produces accurate predictions while covering twice as many possible interactions versus a baseline model. | ['Guy Rosman', 'Naomi Leonard', 'Avinash Balachandran', 'John Leonard', 'Yen-Ling Kuo', 'Xin Huang', 'Xiongyi Cui', 'Jonathan DeCastro', 'Yanxia Zhang', 'Oswin So', 'Justin Lidard'] | 2023-05-28 | null | null | null | null | ['trajectory-prediction'] | ['computer-vision'] | [-1.15028721e-04 3.84091973e-01 -5.46482861e-01 -2.49303365e-03
-1.05231535e+00 -7.22437322e-01 6.57855809e-01 4.65176962e-02
-1.66800857e-01 1.11524105e+00 5.34250319e-01 -6.32008314e-01
-6.01039648e-01 -1.02646339e+00 -8.45121682e-01 -2.46502995e-01
-6.78470850e-01 9.55493689e-01 6.82514191e-01 -7.18388379e-01
1.95453614e-01 1.66590035e-01 -1.65396631e+00 2.26953328e-01
1.21472704e+00 3.95344287e-01 -1.83842471e-03 8.83010745e-01
3.52345318e-01 1.25044417e+00 -1.26253814e-01 -5.44387877e-01
6.89684510e-01 -2.97245830e-01 -8.85677338e-01 -2.63007939e-01
1.58723108e-02 -6.82026327e-01 -6.03000164e-01 4.58264917e-01
2.85040587e-01 6.90388620e-01 9.60253835e-01 -1.72401655e+00
1.38619810e-01 9.09654140e-01 -3.79308194e-01 2.22153425e-01
4.94479477e-01 4.64288205e-01 1.35154355e+00 -2.32110992e-01
6.75017715e-01 1.12368226e+00 9.41468835e-01 4.45486009e-01
-1.21128762e+00 -4.61996078e-01 3.22743595e-01 5.66694260e-01
-1.22238636e+00 -2.45808348e-01 3.76271755e-01 -4.43199962e-01
1.18406236e+00 4.23089862e-01 7.54214108e-01 8.21049750e-01
1.30522683e-01 9.05598283e-01 5.32233119e-01 4.53752950e-02
2.89413154e-01 -2.51798749e-01 -6.49590865e-02 4.67202395e-01
8.92903879e-02 6.53424740e-01 -2.29110092e-01 -3.30717772e-01
4.27732080e-01 -1.39820486e-01 8.05711672e-02 -5.65775812e-01
-9.12720501e-01 9.21695530e-01 3.35084796e-01 -5.47123969e-01
-5.51249504e-01 2.66244888e-01 3.13839078e-01 1.83785990e-01
3.55168492e-01 4.51487511e-01 -4.17285860e-01 -7.76701748e-01
-5.57855606e-01 1.01364648e+00 1.03052390e+00 1.13583302e+00
7.84908652e-01 -2.19447151e-01 -1.28617436e-01 5.31901419e-01
-4.03878614e-02 1.86658800e-01 -1.13284729e-01 -1.35573244e+00
7.81835496e-01 6.06566310e-01 5.80433071e-01 -7.50358462e-01
-7.31485248e-01 -6.82853581e-03 -2.69251943e-01 4.46523607e-01
5.46384871e-01 -5.81423998e-01 -5.70365489e-01 1.79262674e+00
4.67195958e-01 5.34246027e-01 1.89112052e-01 7.48928905e-01
3.09627324e-01 5.50211370e-01 1.29084215e-01 2.65816227e-02
6.05023861e-01 -1.19653451e+00 -1.25715598e-01 -1.44774377e-01
1.09708095e+00 -6.49175718e-02 8.74489367e-01 1.75611585e-01
-1.14176512e+00 -7.30863139e-02 -8.06156754e-01 3.21795344e-01
-2.02263519e-01 -5.55624545e-01 8.05645049e-01 6.75904155e-01
-9.53076839e-01 7.19869673e-01 -7.14091480e-01 -3.32703441e-01
4.31592643e-01 4.86000746e-01 3.05686686e-02 6.57697618e-02
-1.10352075e+00 1.18793666e+00 4.12690222e-01 -5.42280138e-01
-8.45298409e-01 -9.62883413e-01 -7.79773235e-01 5.94666786e-02
8.80426168e-01 -5.32932997e-01 1.31432331e+00 -4.90309328e-01
-1.50148690e+00 -7.05874264e-02 1.64579749e-02 -8.65499079e-01
9.88383174e-01 -1.15025289e-01 -2.65683323e-01 -7.56689757e-02
2.03291550e-01 7.84119427e-01 3.89911011e-02 -1.22952783e+00
-1.32031190e+00 1.95301026e-01 6.44498289e-01 8.01601410e-01
2.88563520e-01 -6.18943334e-01 -1.29852012e-01 -2.20634252e-01
-4.68710572e-01 -1.15132904e+00 -8.19756150e-01 -3.65873426e-01
-3.09988916e-01 -1.77036807e-01 3.55709136e-01 -3.74431163e-01
1.18897676e+00 -1.54233265e+00 1.98413506e-01 4.52619106e-01
1.48213893e-01 -1.30627811e-01 -3.37797523e-01 9.52056050e-01
3.73401940e-01 1.82596236e-01 -7.70976469e-02 -2.07634255e-01
1.77622139e-01 2.77864456e-01 -4.96284336e-01 1.89776912e-01
-8.87449607e-02 1.06999385e+00 -1.00281179e+00 -3.58385324e-01
4.09554064e-01 -1.28334329e-01 -1.12400687e+00 8.90228003e-02
-5.99495530e-01 4.63680625e-01 -5.00408888e-01 3.45095754e-01
4.38929766e-01 2.91121919e-02 2.08868399e-01 4.57726389e-01
-2.07189351e-01 4.20946568e-01 -1.06753087e+00 1.28277659e+00
-3.07458818e-01 4.76484388e-01 -4.42927867e-01 -6.80013776e-01
3.44922662e-01 -6.51987419e-02 8.06846380e-01 -5.06253421e-01
-1.52646720e-01 -4.43678610e-02 2.83001870e-01 -3.96742672e-01
7.91346490e-01 2.42634546e-02 -3.53430122e-01 5.45913339e-01
-4.09774691e-01 -4.72676270e-02 3.11348855e-01 2.79581696e-01
1.46281278e+00 2.71098733e-01 3.88672262e-01 8.80566146e-03
4.91884351e-02 7.45266914e-01 5.27557254e-01 1.14690697e+00
-2.86569744e-01 2.67555475e-01 4.09438312e-01 -4.65376168e-01
-1.17796898e+00 -1.01682365e+00 3.46037388e-01 1.08201647e+00
6.75297499e-01 -4.96943265e-01 -5.48037767e-01 -6.10920608e-01
8.82117376e-02 1.13536000e+00 -5.97466290e-01 -6.93959370e-02
-6.47903681e-01 -5.72927892e-01 5.83219111e-01 3.94579232e-01
3.08137536e-02 -8.99925172e-01 -6.75627053e-01 3.64176184e-01
-3.94556880e-01 -9.68999684e-01 -3.20417106e-01 -1.21508040e-01
-4.59684879e-01 -1.36288083e+00 -8.37311745e-02 -2.70505399e-01
-1.93559155e-02 3.50788355e-01 9.43046153e-01 6.18439689e-02
1.71072900e-01 5.38066804e-01 -4.95256543e-01 -3.01774442e-01
-5.73394477e-01 3.72504890e-01 3.77004482e-02 -5.16484678e-01
2.65241235e-01 -7.81538308e-01 -5.59321105e-01 3.97952229e-01
-1.40391529e-01 3.73603195e-01 3.79759610e-01 7.22326040e-01
2.51123399e-01 1.50145471e-01 7.60228455e-01 -6.57607853e-01
6.85086489e-01 -9.89339411e-01 -4.77728933e-01 1.30114242e-01
-4.50016052e-01 1.41548719e-02 7.31439829e-01 -4.38675553e-01
-9.11292315e-01 4.85635884e-02 -1.32706478e-01 -1.29840970e-01
-2.51182407e-01 4.99229580e-01 -1.11984216e-01 -1.15419582e-01
8.00368071e-01 1.92533210e-01 1.04836132e-02 1.23873107e-01
5.88680863e-01 2.22785607e-01 2.34059989e-01 -6.59914911e-01
8.92979085e-01 3.58111680e-01 8.32859576e-02 -5.56691110e-01
-2.82282352e-01 -4.13115889e-01 -3.44983697e-01 -5.30980885e-01
4.38816965e-01 -9.01422441e-01 -1.32268214e+00 5.87063916e-02
-7.40471005e-01 -9.31948483e-01 -4.15371388e-01 3.91911566e-01
-1.24734795e+00 2.14013755e-01 -3.99732351e-01 -1.09119987e+00
1.19396992e-01 -1.11298168e+00 6.39498174e-01 1.36386558e-01
-4.72135544e-01 -8.62649620e-01 4.16332841e-01 3.25867444e-01
1.26466572e-01 2.80414075e-01 7.92029142e-01 -8.61391842e-01
-1.03860128e+00 -2.19567847e-02 1.41617924e-01 -6.99664772e-01
-1.19508132e-01 -2.05416918e-01 -4.53086525e-01 -8.61584991e-02
-8.91252458e-01 -3.06378454e-01 6.65602982e-01 5.95224619e-01
8.85360897e-01 -5.81467271e-01 -7.97614396e-01 3.12800646e-01
1.28071678e+00 4.37688291e-01 7.83739448e-01 4.43895012e-01
5.83586574e-01 8.16988289e-01 1.07973015e+00 6.57623768e-01
1.02637124e+00 8.89495492e-01 7.13581622e-01 2.87508845e-01
2.99553007e-01 -7.13558078e-01 2.58216560e-01 -2.19250489e-02
-2.28019521e-01 -6.77309215e-01 -1.13205099e+00 9.10285056e-01
-2.37206578e+00 -1.39304125e+00 -3.22890431e-01 2.14825392e+00
3.72856051e-01 3.29071462e-01 9.71491039e-01 -1.77200660e-01
4.27558571e-01 -4.12337035e-02 -8.51704121e-01 -2.09160909e-01
1.69169366e-01 -2.01392695e-01 9.23392832e-01 9.62657452e-01
-1.04831445e+00 1.15875280e+00 7.12207317e+00 1.06853330e+00
-2.93381274e-01 -7.07533071e-03 4.14590478e-01 -4.66516793e-01
-4.68241483e-01 1.56611249e-01 -6.19361997e-01 3.67165744e-01
1.07168603e+00 -4.70007658e-01 8.06420565e-01 7.66134560e-01
3.84473830e-01 -2.42771536e-01 -1.12355065e+00 4.05348063e-01
-5.36772072e-01 -1.71934402e+00 3.51583064e-02 4.54748571e-01
8.10371518e-01 3.00365359e-01 -4.58854390e-03 6.40229642e-01
1.20829213e+00 -1.17994511e+00 8.02074492e-01 3.81729603e-01
3.97348136e-01 -1.29098666e+00 3.99040312e-01 7.84854174e-01
-1.30584085e+00 -4.64579850e-01 -1.40609458e-01 -6.73907995e-01
5.42998314e-01 -2.97296971e-01 -1.13764346e+00 6.09095752e-01
4.38176095e-01 7.60078251e-01 2.26517655e-02 1.18176389e+00
1.96694866e-01 6.77592695e-01 -5.16303957e-01 -2.93179214e-01
4.36377943e-01 -2.66042471e-01 9.41062331e-01 7.72863030e-01
2.70746768e-01 5.55771470e-01 4.94471043e-01 5.75970054e-01
3.26201826e-01 2.44472530e-02 -1.06572258e+00 3.42145622e-01
7.99704909e-01 7.56776810e-01 -3.81287783e-01 -8.64064172e-02
-2.94338018e-01 6.03808582e-01 4.71146911e-01 3.92646044e-01
-1.11628985e+00 1.61505401e-01 1.24940264e+00 1.94810748e-01
3.64800304e-01 -1.34753987e-01 -5.24184585e-01 -6.95828915e-01
-1.40347660e-01 -7.13790774e-01 3.58710676e-01 -3.34752709e-01
-1.15392303e+00 2.08457947e-01 2.73203909e-01 -1.63866627e+00
-8.25233400e-01 -2.86862403e-01 -9.27764237e-01 5.29925942e-01
-1.16448402e+00 -1.32839715e+00 6.34205416e-02 2.29208440e-01
6.51525855e-01 -2.43792161e-01 5.21243274e-01 6.57632807e-03
-3.16607296e-01 5.32437027e-01 1.18021384e-01 -3.53342980e-01
1.70496956e-01 -1.30176246e+00 6.37504637e-01 6.47012889e-01
-2.12040931e-01 7.05868937e-03 9.79614615e-01 -8.08293581e-01
-1.08254194e+00 -1.16418076e+00 3.40780526e-01 -6.69490874e-01
7.18982220e-01 -3.46896760e-02 -5.66004515e-01 9.05715466e-01
-8.23987573e-02 -4.96036351e-01 7.92539120e-01 3.25814217e-01
1.91330910e-01 3.59432280e-01 -1.05549729e+00 1.29467297e+00
1.54668033e+00 -8.01769719e-02 -3.20806384e-01 1.48079127e-01
7.72904038e-01 -6.16244376e-01 -7.04109609e-01 5.01415789e-01
6.91542208e-01 -9.85489964e-01 1.23185849e+00 -8.81323457e-01
6.61903143e-01 -2.05076784e-01 -1.98105246e-01 -1.57172132e+00
-3.88899773e-01 -6.25636637e-01 -2.94335186e-01 7.41182983e-01
7.29840815e-01 -4.97072518e-01 1.17048931e+00 9.68662858e-01
-1.99716315e-01 -9.57035542e-01 -9.82895017e-01 -7.95120955e-01
4.37987119e-01 -7.56411791e-01 8.42179418e-01 5.30285537e-01
4.60623294e-01 4.31003198e-02 -8.18159640e-01 3.97733301e-01
6.72866046e-01 -8.72926936e-02 1.29709828e+00 -9.70815241e-01
-4.63443309e-01 -6.83735549e-01 -4.19256061e-01 -1.27437091e+00
3.43969077e-01 -6.40256882e-01 1.73433974e-01 -1.45440257e+00
1.13598228e-01 -7.72588491e-01 2.70324647e-01 2.64715850e-01
-1.39743045e-01 -1.58570156e-01 1.12374313e-01 6.44700900e-02
-9.03906465e-01 7.21188903e-01 9.60034728e-01 -1.14716895e-01
-5.02847910e-01 4.01374847e-01 -5.97589254e-01 6.68165743e-01
9.43964899e-01 -2.60158360e-01 -8.60286117e-01 2.08775308e-02
2.25781381e-01 5.31686962e-01 3.25729221e-01 -1.19661272e+00
3.37187409e-01 -8.50873768e-01 -2.00888515e-01 -9.50412571e-01
6.48380935e-01 -7.42411077e-01 4.57542837e-01 5.45444250e-01
-6.14005148e-01 -2.01667994e-01 4.00351614e-01 1.02171397e+00
2.68291473e-01 6.02790006e-02 2.05433175e-01 1.60362870e-01
-9.83899593e-01 4.77887422e-01 -8.61611307e-01 1.43154591e-01
1.49678361e+00 -5.49739361e-01 -3.76707792e-01 -9.42141831e-01
-5.99839091e-01 9.71856296e-01 6.04568660e-01 3.55569094e-01
5.47662437e-01 -1.22483301e+00 -8.03520620e-01 -3.44702929e-01
1.38715774e-01 -1.87569946e-01 4.80407298e-01 6.24507487e-01
-3.80175143e-01 1.68548509e-01 -3.34116369e-01 -2.60127455e-01
-1.09877777e+00 5.50560713e-01 5.78283191e-01 -5.14741600e-01
-6.47907257e-01 5.00376046e-01 1.29049510e-01 -7.93746114e-01
-3.57019641e-02 -1.22954123e-01 -3.63359869e-01 -2.72840798e-01
3.41334790e-01 8.45326841e-01 -5.95747173e-01 -6.88639700e-01
-2.03577876e-01 1.45700753e-01 2.27704141e-02 -4.25913304e-01
1.31832087e+00 -3.73694092e-01 6.49140835e-01 2.88287669e-01
5.66875875e-01 -1.31332606e-01 -1.79830456e+00 8.90365094e-02
4.03403770e-03 -4.39129472e-01 -3.73675644e-01 -7.94515908e-01
-5.45042813e-01 4.51317251e-01 1.64803207e-01 1.86084136e-01
6.95515931e-01 -6.67582750e-02 8.73768151e-01 4.92037803e-01
9.71223295e-01 -9.35162604e-01 -2.62602985e-01 6.44763470e-01
5.83472371e-01 -1.32852983e+00 -2.16456532e-01 -5.55335104e-01
-9.68318701e-01 6.18573248e-01 1.04261506e+00 -1.01459071e-01
5.52467883e-01 1.36358500e-01 -4.75419253e-01 1.23577882e-02
-1.16482353e+00 -5.73799312e-01 6.79914132e-02 9.74255860e-01
-3.61261904e-01 3.97053570e-01 -1.83428571e-01 7.05432475e-01
-4.55844223e-01 -6.01329282e-02 7.19518483e-01 6.66722178e-01
-4.78340775e-01 -1.08223581e+00 -3.61634302e-04 7.99938917e-01
-2.71736234e-02 5.00147976e-02 -2.28472650e-01 8.46391380e-01
-8.79955143e-02 1.21095979e+00 1.24480121e-01 -1.00748682e+00
2.67331451e-01 -3.70989591e-01 3.26175332e-01 -4.05424595e-01
-4.00677085e-01 -4.66989666e-01 6.85052812e-01 -7.41091967e-01
-9.06690583e-02 -9.04463470e-01 -1.40968275e+00 -9.79466259e-01
-1.72570869e-01 9.73320752e-02 -1.02171615e-01 1.20293128e+00
4.93213683e-01 3.29903036e-01 4.81139451e-01 -1.00623071e+00
-3.89346808e-01 -6.16462111e-01 -3.58102471e-01 2.81889826e-01
3.38660479e-01 -1.01444149e+00 -8.28885809e-02 -4.55478489e-01] | [5.421816349029541, 1.1200640201568604] |
2d7ccdaa-8df2-4a3e-96b4-44139a34e1b4 | black-box-vs-gray-box-a-case-study-on | 2305.15189 | null | https://arxiv.org/abs/2305.15189v2 | https://arxiv.org/pdf/2305.15189v2.pdf | Black-Box vs. Gray-Box: A Case Study on Learning Table Tennis Ball Trajectory Prediction with Spin and Impacts | In this paper, we present a method for table tennis ball trajectory filtering and prediction. Our gray-box approach builds on a physical model. At the same time, we use data to learn parameters of the dynamics model, of an extended Kalman filter, and of a neural model that infers the ball's initial condition. We demonstrate superior prediction performance of our approach over two black-box approaches, which are not supplied with physical prior knowledge. We demonstrate that initializing the spin from parameters of the ball launcher using a neural network drastically improves long-time prediction performance over estimating the spin purely from measured ball positions. An accurate prediction of the ball trajectory is crucial for successful returns. We therefore evaluate the return performance with a pneumatic artificial muscular robot and achieve a return rate of 29/30 (97.7%). | ['Joerg Stueckler', 'Michael Muehlebach', 'Dieter Buechler', 'Hao Ma', 'Philip Tobuschat', 'Jan Achterhold'] | 2023-05-24 | null | null | null | null | ['trajectory-prediction'] | ['computer-vision'] | [-1.12629183e-01 4.31646585e-01 -1.32281855e-01 1.83164194e-01
-1.18156746e-01 -4.30518508e-01 3.46820593e-01 -1.01375774e-01
-6.93944097e-01 7.52322137e-01 -6.93433434e-02 -1.78155452e-01
-2.64329374e-01 -7.03382075e-01 -1.21130204e+00 -3.67899358e-01
-1.32731766e-01 8.18403780e-01 6.34493232e-01 -6.30150855e-01
3.11725676e-01 7.66438305e-01 -1.31655073e+00 -2.68479809e-02
6.26419544e-01 9.16825891e-01 3.43859076e-01 1.08089721e+00
6.38669193e-01 1.07213926e+00 -5.74723959e-01 -2.27925658e-01
4.42891717e-01 -2.09401548e-01 -6.93765938e-01 -4.65922803e-01
-1.94497835e-02 -4.02811170e-01 -9.00749326e-01 3.78562212e-01
3.09319854e-01 5.68406165e-01 5.93350470e-01 -8.60304058e-01
1.91482976e-01 6.95272088e-01 1.45322382e-01 -5.26155382e-02
4.36904281e-01 4.35901970e-01 6.33800328e-01 -3.90952021e-01
8.31806064e-01 7.83195913e-01 1.34695578e+00 4.98390347e-01
-1.27581000e+00 -4.57220674e-01 -2.77564049e-01 1.76376566e-01
-1.21906900e+00 -2.82342494e-01 4.35149074e-01 -7.68659353e-01
8.27223003e-01 8.39160010e-02 1.12455988e+00 9.33250487e-01
8.02003562e-01 6.39068127e-01 7.12586462e-01 -3.40736032e-01
2.09424078e-01 -1.60864204e-01 -4.35733572e-02 5.85676908e-01
3.01220179e-01 8.90242457e-01 -6.04776978e-01 1.46875292e-01
1.10939574e+00 -2.03843430e-01 -2.14807317e-01 -6.78727090e-01
-1.09866691e+00 2.88428724e-01 3.88729066e-01 -2.29851022e-01
-5.07545292e-01 6.28738821e-01 1.21547945e-01 7.34617785e-02
-2.93177098e-01 7.68662333e-01 -4.37073708e-01 -8.02446961e-01
-8.26087892e-01 8.51957083e-01 1.31621718e+00 9.74625289e-01
2.63090193e-01 5.41193150e-02 -1.29902571e-01 3.70132059e-01
8.74655992e-02 5.08353055e-01 2.94032693e-01 -1.15488136e+00
2.85503089e-01 2.81057745e-01 7.06991076e-01 -8.86402369e-01
-8.61668944e-01 -3.59156728e-01 -1.19017109e-01 5.91198325e-01
7.67190397e-01 -3.95445973e-01 -6.98581159e-01 1.21897233e+00
3.09980571e-01 2.78416295e-02 1.90623850e-01 1.09255457e+00
3.05969387e-01 5.07999241e-01 -4.20359820e-01 2.45860443e-01
8.79022360e-01 -8.41906190e-01 -6.45397544e-01 -2.64472157e-01
4.79255140e-01 -3.49409908e-01 7.58045793e-01 1.03943634e+00
-1.21917784e+00 -7.23731518e-01 -1.31870306e+00 2.61058420e-01
-4.08575609e-02 5.04613221e-01 5.35199225e-01 4.67979163e-01
-3.52262855e-01 1.68447244e+00 -1.65307224e+00 -3.30657996e-02
-2.96088010e-01 8.18064511e-01 -1.29319072e-01 6.73222601e-01
-1.04443467e+00 1.64431739e+00 5.23351669e-01 1.83285415e-01
-1.01359642e+00 -5.43588579e-01 -4.50759113e-01 -2.63807505e-01
3.09172809e-01 -3.93239260e-01 1.64801824e+00 -2.70939797e-01
-2.31560302e+00 1.71255589e-01 3.60169142e-01 -8.24878514e-01
7.19734669e-01 -9.14587259e-01 -7.89806545e-02 1.62972867e-01
-3.92741501e-01 2.19858930e-01 5.56575775e-01 -1.03539908e+00
-6.13074183e-01 1.53034166e-01 -1.23283565e-01 1.15532398e-01
-6.77292235e-03 -5.54768920e-01 -3.90817761e-01 -5.23443878e-01
1.92657918e-01 -1.35379088e+00 -3.79890382e-01 -5.08340134e-04
-1.08350560e-01 2.80150741e-01 4.26930994e-01 -9.90895927e-01
1.04683304e+00 -1.65939891e+00 2.51581073e-01 2.48476654e-01
-1.94077462e-01 9.65965912e-02 5.17535806e-01 7.27772951e-01
2.45628178e-01 -6.62677646e-01 3.23034912e-01 1.97661947e-02
-8.61399695e-02 2.73783624e-01 -5.59619725e-01 5.13942301e-01
-3.55057657e-01 7.78142631e-01 -7.98737109e-01 -6.45356625e-02
2.91041195e-01 3.11867476e-01 -6.78409398e-01 3.93818378e-01
-1.30244300e-01 5.56398690e-01 -3.82281423e-01 1.83000416e-01
1.58550486e-01 1.88897818e-01 1.34876251e-01 -1.89972639e-01
-1.44323379e-01 4.18088734e-01 -1.43776572e+00 1.75108218e+00
-4.46984470e-01 3.68670732e-01 1.59250498e-01 -9.10060823e-01
1.19157016e+00 2.49961033e-01 7.79674292e-01 -2.96579301e-01
4.20621425e-01 2.84319282e-01 -6.13037671e-04 -5.76543868e-01
8.86219561e-01 -3.44394833e-01 -5.51598109e-02 1.71624050e-01
2.96454132e-01 -6.81681812e-01 9.34274867e-02 -1.35225803e-01
1.29585695e+00 1.15399110e+00 -1.00056656e-01 -2.89310157e-01
2.14608327e-01 5.80858290e-01 5.04683495e-01 1.02914989e+00
1.48896262e-01 5.70022285e-01 2.23526880e-01 -5.24031222e-01
-1.13796341e+00 -1.11795640e+00 1.23599477e-01 6.48798227e-01
5.45749485e-01 -5.87842286e-01 -6.34582043e-01 -6.38865829e-02
5.72801471e-01 7.02114820e-01 -4.55207884e-01 -6.80279732e-01
-9.54218030e-01 -4.05197412e-01 6.00233018e-01 9.71495688e-01
-1.39699295e-01 -6.36919260e-01 -1.02444887e+00 7.07485199e-01
-2.08380949e-02 -1.00596941e+00 3.32724601e-02 4.15180445e-01
-1.08008158e+00 -1.15718591e+00 -7.30633363e-02 -3.29578727e-01
1.99039891e-01 -6.03424609e-01 8.31161618e-01 -1.96823597e-01
-1.68955758e-01 3.66172075e-01 -3.98115128e-01 -6.32954538e-01
-7.07534730e-01 -2.28249118e-01 5.12237430e-01 -6.34708941e-01
-1.51507974e-01 -4.68259990e-01 -4.62867886e-01 6.32310271e-01
-2.23312557e-01 3.95468265e-01 5.33670008e-01 7.78356791e-01
5.09886682e-01 6.85314601e-03 -7.10837916e-02 -1.99197978e-01
4.37041342e-01 1.04830384e-01 -8.25983524e-01 -2.27933764e-01
-5.11730552e-01 2.42954180e-01 7.80715823e-01 -8.59240830e-01
-1.12578654e+00 7.12335825e-01 -2.53270209e-01 -3.48464072e-01
8.50403383e-02 1.83221042e-01 4.25947368e-01 -3.74249399e-01
9.29305017e-01 1.17781147e-01 4.71415788e-01 -6.95148587e-01
1.97837204e-01 5.67383170e-01 1.13351023e+00 -9.04979885e-01
6.66430593e-01 4.88040954e-01 3.24756294e-01 -4.35597271e-01
-4.34265941e-01 -3.09661955e-01 -9.66027975e-01 -5.25349379e-01
4.70560253e-01 -7.14347243e-01 -1.49510252e+00 4.97247905e-01
-9.27274108e-01 -8.86363089e-01 -5.28359294e-01 1.06327057e+00
-1.29073358e+00 6.24289922e-02 -1.07826769e+00 -9.91160393e-01
-2.26857334e-01 -8.18215251e-01 6.94940269e-01 8.72901157e-02
-3.83731097e-01 -5.78707159e-01 3.44262719e-01 1.82629228e-01
1.72071621e-01 3.02823335e-01 1.46099012e-02 -4.72975910e-01
-3.29543501e-01 -8.17753255e-01 5.75227320e-01 2.63410091e-01
-3.31364930e-01 -1.70256749e-01 -6.40059173e-01 -4.51129019e-01
2.71248501e-02 -8.96539167e-02 4.82185304e-01 3.32357377e-01
8.45584869e-01 -6.78949729e-02 -6.78811729e-01 4.13634628e-01
1.21973288e+00 1.67401314e-01 4.45501387e-01 5.87303579e-01
4.51255023e-01 2.95753658e-01 1.01377404e+00 5.15194058e-01
6.81964979e-02 9.56066072e-01 4.78622198e-01 6.45290911e-01
7.60192722e-02 -7.28060126e-01 4.82726544e-01 4.57426637e-01
-6.74305201e-01 9.67959687e-02 -1.05780649e+00 2.15864718e-01
-1.96919656e+00 -7.95775473e-01 -1.34826213e-01 2.27365208e+00
7.36949325e-01 5.35592318e-01 1.85510397e-01 2.51979262e-01
3.76596928e-01 -7.43592262e-01 -5.20292103e-01 -2.50347108e-01
4.61309046e-01 1.71423450e-01 1.07048237e+00 5.50332844e-01
-9.32888031e-01 8.67697656e-01 7.35098839e+00 6.55305266e-01
-9.90661979e-01 -2.84045517e-01 -4.08091336e-01 -3.24105352e-01
5.28546810e-01 2.91073084e-01 -1.06892002e+00 4.07312691e-01
1.12497938e+00 -9.81592666e-03 4.98005718e-01 9.28562343e-01
1.88877583e-01 -3.85261178e-01 -1.23615968e+00 5.11691749e-01
-4.98289317e-02 -1.26166618e+00 -5.70853889e-01 -4.27959040e-02
3.78519714e-01 -1.33620009e-01 -5.29952109e-01 4.63059157e-01
5.01043916e-01 -7.70592511e-01 1.40207219e+00 1.30990422e+00
1.39341295e-01 -5.03861129e-01 5.72409213e-01 9.27748799e-01
-9.12499487e-01 -4.77474421e-01 -2.89060503e-01 -7.22111344e-01
4.37775612e-01 2.28933275e-01 -9.02656615e-01 5.52788377e-01
5.90753257e-01 4.96228546e-01 -1.78225040e-01 1.34955275e+00
-3.01555842e-01 8.75359535e-01 -8.42939913e-01 -3.63168746e-01
-2.23939165e-01 -1.74324244e-01 8.58721495e-01 8.49366486e-01
7.73044452e-02 1.74624562e-01 2.20309347e-01 7.70102322e-01
6.75548851e-01 -1.41420022e-01 -2.90321678e-01 2.37725660e-01
-1.47185950e-02 1.02113390e+00 -5.10639012e-01 -1.03599139e-01
1.78213924e-01 7.06784308e-01 7.94920605e-03 1.71164498e-02
-8.30915630e-01 -6.44717336e-01 3.47961187e-01 3.39094251e-01
3.93320650e-01 -6.16449237e-01 -3.62753004e-01 -9.82458889e-01
1.93949595e-01 -2.90711343e-01 -2.90478906e-03 -1.03819001e+00
-6.82117820e-01 5.49332537e-02 2.42720768e-01 -1.50607920e+00
-6.11399472e-01 -1.01882589e+00 -4.41204906e-01 7.08888412e-01
-6.23470485e-01 -6.55464113e-01 -1.17167287e-01 -9.15473774e-02
-1.24461576e-01 1.48235247e-01 5.98176062e-01 -1.60377100e-01
-8.10427815e-02 2.17450887e-01 4.23331439e-01 1.92111582e-01
3.83255422e-01 -1.19688618e+00 4.11611617e-01 6.26703382e-01
-1.06852032e-01 5.13620079e-01 1.34910071e+00 -9.44663882e-01
-1.93848276e+00 -4.28792596e-01 1.96498424e-01 -7.83547401e-01
9.46896791e-01 -2.90038913e-01 -6.56311631e-01 7.48877227e-01
-5.09999633e-01 -9.95159596e-02 -1.54338190e-02 -2.09877617e-03
6.74081147e-01 -3.23055118e-01 -7.27183163e-01 4.83535856e-01
8.07259619e-01 -1.86404333e-01 -1.07003820e+00 2.45120883e-01
3.04223448e-01 -1.26312399e+00 -1.17836916e+00 6.05951905e-01
1.23817718e+00 -6.02205157e-01 1.06777668e+00 -6.38936818e-01
2.43018702e-01 -2.27631614e-01 2.63373911e-01 -1.19549799e+00
-1.67659104e-01 -7.73971081e-01 -6.62574887e-01 4.25439239e-01
2.29118168e-01 -3.88020247e-01 1.40906310e+00 6.14947736e-01
-3.52680147e-01 -1.04889214e+00 -9.05428529e-01 -1.20886362e+00
1.59070462e-01 -5.85022688e-01 2.90073246e-01 -2.06550844e-02
6.42946720e-01 5.64752668e-02 -6.54920220e-01 2.59484053e-01
4.81084645e-01 2.43074179e-01 1.17260849e+00 -1.18552268e+00
-6.98291600e-01 -1.72361895e-01 -7.99463034e-01 -1.45798111e+00
-8.40220079e-02 -4.37065929e-01 5.00029624e-01 -1.42146230e+00
-3.29127192e-01 -2.79494345e-01 -9.52717140e-02 3.48640025e-01
2.06891477e-01 8.94712210e-02 2.09824055e-01 1.69391900e-01
-3.69972736e-01 4.48555797e-01 1.21551204e+00 2.72488147e-01
-4.41105455e-01 3.85833234e-01 2.36175701e-01 8.44671309e-01
8.39488387e-01 -5.19240439e-01 8.36244076e-02 -6.45785555e-02
2.55479008e-01 6.48315251e-01 7.10647702e-01 -1.89694989e+00
5.30564845e-01 -9.87638757e-02 5.84981859e-01 -6.40198231e-01
6.37798250e-01 -7.19409943e-01 5.30769229e-01 1.10447919e+00
-1.56580970e-01 -3.98908436e-01 3.77428412e-01 6.89399004e-01
1.51511192e-01 -3.48019928e-01 5.25070846e-01 1.38308808e-01
-5.07816553e-01 -1.12698279e-01 -5.70236504e-01 -4.05880779e-01
8.95300508e-01 -6.93747818e-01 1.35307491e-01 -1.96799234e-01
-1.31687248e+00 1.61025882e-01 5.11804581e-01 4.43206698e-01
3.21208209e-01 -1.02953076e+00 -1.16015352e-01 1.95253581e-01
-3.01691592e-01 -1.32967532e-01 -8.71419460e-02 9.61846173e-01
-1.03674412e+00 4.02709514e-01 -4.78642672e-01 -6.25888467e-01
-8.18667352e-01 3.87176424e-01 5.89114785e-01 -8.30804184e-02
-1.02873874e+00 5.32986343e-01 -6.70092404e-01 -6.19587064e-01
1.53185084e-01 -4.86105472e-01 -6.64329156e-02 -6.43271923e-01
1.16765849e-01 5.76369345e-01 1.84803411e-01 -4.34941024e-01
-2.32599191e-02 4.98534113e-01 4.89286244e-01 -3.42525274e-01
1.41229379e+00 2.81171888e-01 4.40113634e-01 6.78358853e-01
2.57315338e-01 -1.79630928e-02 -1.82255089e+00 1.41970679e-01
-8.31305981e-02 -2.99154252e-01 -4.06782776e-02 -8.89420927e-01
-6.36147082e-01 5.31836152e-01 3.86096030e-01 -2.93259740e-01
5.65779746e-01 -2.59625047e-01 7.71103919e-01 8.59840453e-01
7.03122854e-01 -1.52040493e+00 -8.52793530e-02 5.95213175e-01
7.98110962e-01 -6.42663419e-01 3.09798837e-01 -3.06122422e-01
-4.55051273e-01 1.43342936e+00 7.54659176e-01 -6.72920704e-01
6.75119460e-01 7.55407751e-01 -1.44780159e-01 2.44228989e-02
-6.69700623e-01 1.20284744e-01 3.30234945e-01 3.31657827e-01
-7.81419128e-02 3.06034461e-02 -2.93556601e-01 1.20641148e+00
-7.26446927e-01 4.26567227e-01 5.97031355e-01 1.35112464e+00
-7.54651070e-01 -8.20837796e-01 -6.35078549e-01 3.04169118e-01
-3.41410398e-01 5.43211877e-01 7.24662691e-02 9.17046189e-01
-5.43637238e-02 5.95017254e-01 -5.23092411e-02 -8.02104175e-01
9.18490708e-01 -6.93937764e-02 7.46544898e-01 -2.69542187e-01
-6.32615864e-01 -3.26684207e-01 2.50200897e-01 -9.28425014e-01
1.08223222e-01 -7.35833108e-01 -1.54532528e+00 -2.16971397e-01
-7.74786532e-01 4.27095234e-01 7.91177452e-01 8.68138969e-01
2.55490430e-02 3.99627239e-01 9.67887137e-03 -1.35526836e+00
-1.03166842e+00 -9.56711292e-01 -8.06041479e-01 2.71168500e-01
1.31137699e-01 -1.28107941e+00 -4.40409407e-02 1.73485622e-01] | [4.741697311401367, 1.1084847450256348] |
b0708dc0-c5e1-4ba7-92c4-03592dd5a520 | adaptive-similarity-embedding-for | null | null | https://ieeexplore.ieee.org/document/8970566 | https://iitkgpmail.iitkgp.ac.in/service/home/~/?auth=co&loc=en_US&id=10916&part=2 | Adaptive Similarity Embedding for Unsupervised Multi-View Feature Selection | Multi-view learning has become a significant research topic in image processing, data mining, and machine learning due
to the proliferation of multi-view data. Considering the difficulty in obtaining labeled data in many real applications, we focus on the
multi-view unsupervised feature selection problem. Most existing multi-view feature selections introduce an identical similarity matrix
among different views, which cannot preserve the specific correlation between every single view. Also, some of these methods just
consider either global or local structures. In this paper, we propose an embedding method, Adaptive Similarity Embedding for
Unsupervised Multi-View Feature Selection (ASE-UMFS). This method reduces the high-dimensional data to the low dimensions and
unifies different views to a combined weight matrix. We also use parameters to constraint the similarity matrix for the local structure, where the regularization term is used to add a prior of uniform distribution; taking into account the independence in the projection matrix among different views, optimization of the similarity matrix is further improved. To confirm the effectiveness of ASE-UMFS,
comparisons are made with benchmark algorithms on real-world data sets. The experimental results demonstrate that the proposed
algorithm outperforms several state-of-the-art methods in multi-view learning. | ['Cheng Zeng', 'Shengzi Sun', 'Yuan Wan'] | 2020-01-27 | null | null | null | ieee-xplore-2020-1 | ['multi-view-learning'] | ['computer-vision'] | [ 2.26342306e-02 -6.28349960e-01 -2.87184119e-01 -2.51446128e-01
-2.82323956e-01 -2.55043834e-01 2.99299449e-01 -1.38637811e-01
-2.29747146e-01 2.94205219e-01 4.19803739e-01 3.87980044e-01
-4.78596091e-01 -7.15783179e-01 -1.86264757e-02 -9.89336550e-01
2.72979885e-01 1.27854884e-01 2.58401364e-01 -7.05845878e-02
3.73254985e-01 2.61098444e-01 -1.54339445e+00 3.47773284e-01
6.73606515e-01 6.91287518e-01 2.98312008e-01 2.08882883e-01
3.33282128e-02 3.05186749e-01 -1.76753625e-01 -1.48778856e-01
3.26263160e-01 -4.13498670e-01 -3.25045466e-01 6.19757056e-01
3.34992141e-01 -1.31386086e-01 -4.18319181e-02 1.28508663e+00
6.99461341e-01 2.14460790e-01 6.16172910e-01 -1.28175497e+00
-6.34594500e-01 2.61368185e-01 -1.13249087e+00 2.20479786e-01
1.52992055e-01 -3.93337339e-01 1.12295926e+00 -1.36836541e+00
6.48251474e-01 1.25505757e+00 2.90673018e-01 1.54157549e-01
-1.07410419e+00 -5.52683413e-01 4.27695930e-01 6.78408980e-01
-1.36531484e+00 -8.58940855e-02 1.06427979e+00 -4.94855821e-01
4.37763751e-01 1.96620718e-01 6.60589576e-01 6.66647136e-01
3.85428607e-01 7.77733386e-01 1.27272999e+00 -3.32204938e-01
-1.18654057e-01 4.20238763e-01 1.85824707e-01 7.39315450e-01
3.28462064e-01 -8.62476602e-02 -4.56494927e-01 -2.88191497e-01
4.65970755e-01 5.48255444e-01 -3.20611268e-01 -1.12294972e+00
-1.35909796e+00 1.02624500e+00 9.16175544e-02 3.41694593e-01
-2.14771375e-01 -6.95847988e-01 6.99827373e-01 3.59915584e-01
3.35859448e-01 -1.08411394e-01 -3.76055717e-01 3.24646980e-01
-5.03128886e-01 -2.63168573e-01 4.18986350e-01 8.36815894e-01
7.91223288e-01 -6.32200902e-03 2.58607924e-01 1.12709284e+00
4.32798982e-01 4.73668128e-01 8.05523157e-01 -3.71794790e-01
5.52795649e-01 1.01982665e+00 -2.97323704e-01 -1.38399446e+00
-5.36435127e-01 -3.62217158e-01 -1.12198389e+00 1.81075826e-01
-1.53848216e-01 -6.77269474e-02 -5.15473485e-01 1.27836394e+00
5.88442624e-01 3.97128835e-02 1.92208529e-01 9.24809158e-01
9.10030544e-01 5.59169829e-01 -4.43577915e-01 -6.21519983e-01
1.27764690e+00 -9.57197070e-01 -6.56048357e-01 1.72616646e-01
3.40929806e-01 -9.70172346e-01 8.97403061e-01 5.92051506e-01
-4.42520231e-01 -6.46516025e-01 -1.22106171e+00 4.29679841e-01
-2.35904187e-01 4.08805072e-01 5.65166056e-01 4.89518195e-01
-4.09292668e-01 1.81106642e-01 -6.09082043e-01 -3.69093925e-01
1.29816771e-01 4.37976092e-01 -8.95569861e-01 -2.37408474e-01
-1.04489148e+00 6.02415502e-01 4.90749270e-01 4.15051766e-02
-3.62925351e-01 -2.63797671e-01 -8.18152785e-01 -4.25930135e-02
5.10445297e-01 -4.93839860e-01 3.42843503e-01 -8.71307611e-01
-1.10052085e+00 7.05618620e-01 -1.23391852e-01 2.81541377e-01
1.71536997e-01 -6.60590753e-02 -8.42882812e-01 2.52621382e-01
2.86934167e-01 -5.45011722e-02 1.00818145e+00 -1.30832124e+00
-6.58167720e-01 -7.09664464e-01 -2.08609045e-01 5.55579245e-01
-7.29361236e-01 -3.10392100e-02 -4.75217789e-01 -5.82195699e-01
6.49923742e-01 -1.01780176e+00 -2.16880515e-01 -2.46572375e-01
-3.37805539e-01 -2.04624981e-02 1.14438081e+00 -2.68954039e-01
1.38053083e+00 -2.33187914e+00 7.38421619e-01 4.61067379e-01
1.82116434e-01 1.58769358e-02 1.23007223e-01 5.64653397e-01
-2.42900893e-01 -2.00572401e-01 -1.50779292e-01 1.29247263e-01
-4.81003731e-01 3.66109163e-02 1.70618311e-01 6.95621312e-01
-2.71847337e-01 6.05705343e-02 -7.41925538e-01 -8.00077081e-01
4.66636062e-01 3.11588764e-01 -3.73787373e-01 1.15425982e-01
6.56561017e-01 3.27060550e-01 -7.96123028e-01 4.73534733e-01
8.91047776e-01 -3.25540870e-01 2.62963593e-01 -7.02631772e-01
-1.22708298e-01 -5.96587777e-01 -1.92390132e+00 1.50530910e+00
-3.50437075e-01 1.59997959e-02 -5.40388077e-02 -9.95465517e-01
8.22765350e-01 3.61575425e-01 1.01132429e+00 -1.44470647e-01
1.09172918e-01 8.01486522e-02 1.75588399e-01 -6.87783182e-01
1.56027094e-01 -3.54621053e-01 1.00276791e-01 5.71260691e-01
2.53373206e-01 1.22427210e-01 3.38966638e-01 1.68778241e-01
4.42662239e-01 -1.80873886e-01 6.79958045e-01 -2.10219905e-01
1.13738990e+00 -4.54943597e-01 9.68047500e-01 9.63274203e-03
-8.68697688e-02 8.24282289e-01 2.35729352e-01 -5.15095413e-01
-7.17621684e-01 -8.70553255e-01 -2.65629113e-01 8.28656733e-01
3.88961226e-01 -5.64315379e-01 -3.48527938e-01 -1.16375482e+00
5.03014065e-02 1.38218537e-01 -6.24350548e-01 -2.30035394e-01
-2.75618821e-01 -1.03933489e+00 -1.93133637e-01 2.54064918e-01
5.26980162e-01 -7.11222827e-01 -2.64263332e-01 8.91096368e-02
1.09645560e-01 -8.81153643e-01 -6.40639305e-01 -7.79565200e-02
-9.10653353e-01 -1.35600019e+00 -5.41975498e-01 -8.90706062e-01
9.33346629e-01 8.72818291e-01 5.90936065e-01 5.14034033e-02
-1.92643836e-01 5.35384834e-01 -6.20034456e-01 -2.24670991e-01
2.56563518e-02 9.71117429e-03 3.89565527e-01 5.98659575e-01
4.89390045e-01 -6.48735881e-01 -4.17776048e-01 7.20636964e-01
-1.05902326e+00 2.13317256e-02 5.86104572e-01 1.24493647e+00
8.82186830e-01 3.71332973e-01 5.14634132e-01 -1.05805576e+00
3.60611826e-01 -3.24332863e-01 -4.21611309e-01 4.43945825e-01
-8.57595444e-01 -4.36642952e-02 7.20968902e-01 -3.46813917e-01
-9.67298508e-01 2.01793239e-01 2.57978946e-01 -4.81233984e-01
1.15954168e-01 6.43660426e-01 -6.28272653e-01 -2.62857527e-01
1.63074762e-01 5.76504409e-01 1.97097734e-01 -3.94113690e-01
2.69473016e-01 6.22950971e-01 -2.57070154e-01 -1.06356762e-01
7.64789462e-01 6.76371157e-01 1.94253236e-01 -8.95815909e-01
-8.71945143e-01 -7.44822085e-01 -1.02478647e+00 -1.91946596e-01
7.39566624e-01 -8.87324750e-01 -3.71400386e-01 3.43761504e-01
-5.68311691e-01 9.08932030e-01 1.34212552e-02 9.91947472e-01
-4.35939968e-01 7.68436134e-01 -2.18178794e-01 -3.66741657e-01
-2.17260957e-01 -1.25089037e+00 6.34741068e-01 1.79566264e-01
2.89021969e-01 -1.07344425e+00 1.58713013e-01 2.90214866e-01
-8.12868997e-02 1.14983581e-01 9.01625276e-01 -7.43616700e-01
-1.58436403e-01 -1.48557082e-01 -3.35586704e-02 4.59743887e-01
6.59712851e-01 6.62109405e-02 -6.57834947e-01 -5.66555858e-01
4.44035321e-01 -1.08895332e-01 8.74003410e-01 2.34015077e-01
1.01254749e+00 4.50806059e-02 -3.57322186e-01 6.69470310e-01
1.63800681e+00 2.56187201e-01 1.51498318e-01 4.72414225e-01
9.39590514e-01 5.83187222e-01 7.83596098e-01 7.16120481e-01
1.54223397e-01 4.76628006e-01 3.17372531e-01 2.10778993e-02
3.55143160e-01 4.53166887e-02 1.07513770e-01 1.51164258e+00
-8.09132084e-02 4.07402776e-03 -4.38286275e-01 3.94929588e-01
-1.91219592e+00 -1.27368760e+00 -1.59613043e-01 2.29028821e+00
3.14659357e-01 1.13570951e-01 6.24464825e-02 1.88241392e-01
9.06897604e-01 4.25099641e-01 -4.81404275e-01 -5.99454567e-02
-3.27295333e-01 -4.15452003e-01 2.33621955e-01 2.55186766e-01
-1.45076632e+00 4.43727016e-01 5.35401011e+00 6.77257180e-01
-1.22411215e+00 7.55392537e-02 3.26991409e-01 -8.09025019e-02
-3.34707826e-01 -9.06987712e-02 -9.10656393e-01 4.35139000e-01
1.00797959e-01 -1.81214437e-01 1.54901981e-01 8.22983980e-01
8.20434839e-02 -3.96075174e-02 -7.97558427e-01 1.25429940e+00
6.17360413e-01 -8.26696515e-01 4.25225765e-01 3.24695520e-02
8.48425865e-01 -2.58590519e-01 9.17053893e-02 -3.82549576e-02
-2.96515793e-01 -5.03827870e-01 8.45131576e-02 3.64316761e-01
5.00457942e-01 -1.12671924e+00 7.89073884e-01 2.98711866e-01
-1.50230849e+00 -1.33651882e-01 -6.46362543e-01 2.75273323e-01
1.66436732e-01 6.91913784e-01 -2.77524680e-01 1.13756657e+00
4.21908140e-01 1.24795318e+00 -8.23964894e-01 9.41921830e-01
1.01122729e-01 1.06507748e-01 -2.20653102e-01 2.64099002e-01
2.56866831e-02 -6.17918491e-01 6.82430565e-01 6.96351707e-01
2.10764036e-01 3.35635431e-02 7.27117360e-01 4.29340340e-02
3.28757703e-01 6.82461500e-01 -8.02595794e-01 2.57033139e-01
1.87266856e-01 1.46490979e+00 -6.97174549e-01 -1.98268175e-01
-1.00630152e+00 1.08141351e+00 8.69953409e-02 5.45859896e-02
-4.94834214e-01 -4.28406984e-01 3.34191978e-01 -1.84403270e-01
4.83073592e-01 -5.44004701e-02 -2.66532898e-02 -1.57486331e+00
1.92718461e-01 -1.00667524e+00 7.07726955e-01 -1.81625172e-01
-1.56382978e+00 5.63673556e-01 9.95765701e-02 -1.97403443e+00
8.27883035e-02 -4.80445325e-01 -4.91283596e-01 5.38578272e-01
-1.37833381e+00 -1.22418165e+00 -1.17609873e-01 7.84904242e-01
5.86911082e-01 -7.10398912e-01 8.02558661e-01 5.06101310e-01
-6.97666228e-01 5.11195898e-01 4.79556233e-01 -2.36160830e-02
1.00605440e+00 -1.01442683e+00 -3.11252147e-01 7.11029649e-01
2.69876778e-01 7.21782327e-01 2.87862748e-01 -5.37609994e-01
-1.56416690e+00 -7.76007712e-01 4.21101630e-01 -7.02276528e-02
4.69238728e-01 -9.04951692e-02 -7.92046726e-01 5.57000518e-01
1.75295874e-01 3.64275336e-01 1.33012867e+00 2.04822853e-01
-2.01198816e-01 -3.02830786e-01 -9.74433839e-01 2.79049128e-01
5.57968616e-01 -3.46546561e-01 -4.70437199e-01 2.32951552e-01
2.82567292e-01 -9.16268304e-02 -1.07546818e+00 4.75316733e-01
7.46258855e-01 -1.27978647e+00 9.11975086e-01 -6.55864120e-01
2.17622131e-01 -7.18600512e-01 -3.44742000e-01 -1.54985499e+00
-7.29790330e-01 7.54831284e-02 1.56555459e-01 1.22696018e+00
1.50878832e-01 -6.03776693e-01 7.07103074e-01 1.06073521e-01
2.02431187e-01 -9.70879138e-01 -9.03500974e-01 -5.96590400e-01
-4.66869116e-01 2.67180562e-01 3.90143514e-01 1.18357611e+00
-1.04406439e-01 6.12686038e-01 -6.55668676e-01 2.92176038e-01
7.96818197e-01 6.60429537e-01 6.09265685e-01 -1.40641809e+00
-3.62113416e-01 -4.77438085e-02 -7.55472481e-01 -3.94054115e-01
-2.81650033e-02 -7.37549782e-01 -4.80708331e-01 -1.53045034e+00
6.41022325e-01 -1.47462457e-01 -7.53475249e-01 -5.26083037e-02
-4.36251223e-01 -3.22906487e-02 2.47189760e-01 2.60853976e-01
-6.70189023e-01 8.54818583e-01 1.37945640e+00 -5.63179441e-02
-2.32362837e-01 1.62198156e-01 -6.50710762e-01 1.04138029e+00
4.36925650e-01 -3.47550422e-01 -6.43818378e-01 -2.46279225e-01
2.73815729e-02 2.34992942e-03 -2.87283778e-01 -1.00861275e+00
1.55979067e-01 -3.85440290e-01 5.78569174e-01 -6.49509192e-01
2.60190368e-01 -1.27365232e+00 1.12777352e-01 3.10967386e-01
6.14204481e-02 2.56833047e-01 -2.70582616e-01 8.41112137e-01
-5.94752848e-01 -3.17792922e-01 8.51031840e-01 -3.41476381e-01
-9.38908815e-01 4.55982864e-01 -3.90295051e-02 -2.82824244e-02
1.18240893e+00 -3.74222547e-01 1.34400800e-01 -1.17118008e-01
-8.25598657e-01 3.69704247e-01 4.25518811e-01 4.69579518e-01
9.74128246e-01 -1.78796363e+00 -6.49461508e-01 4.91082698e-01
5.08049905e-01 -2.35663131e-01 5.84154010e-01 8.06014359e-01
-1.36575967e-01 -2.53171120e-02 -4.71497118e-01 -5.80429316e-01
-1.81766737e+00 7.93699563e-01 -9.09951627e-02 -2.91604370e-01
-5.12187779e-01 5.81844389e-01 4.23484355e-01 -5.00775099e-01
-1.44090787e-01 3.18263203e-01 -8.77522469e-01 6.02668524e-01
5.48454463e-01 4.12476718e-01 -7.82855153e-02 -9.82501149e-01
-3.18067342e-01 1.14423263e+00 -3.91036004e-01 1.26067534e-01
1.51832902e+00 -3.32517415e-01 -3.40346724e-01 7.78129220e-01
1.46309090e+00 3.17527056e-01 -8.51171613e-01 -4.24935728e-01
-2.97148436e-01 -7.30450094e-01 6.43554106e-02 -1.23309612e-01
-1.29082823e+00 8.27174842e-01 8.36094797e-01 2.55116560e-02
1.19017935e+00 -3.98369551e-01 5.46790659e-01 3.87813658e-01
4.78128672e-01 -1.16821933e+00 1.55488878e-01 4.15077984e-01
7.54650295e-01 -1.47313499e+00 7.46744692e-01 -6.11007452e-01
-1.00048757e+00 1.23551440e+00 8.82038593e-01 -1.74843222e-01
1.10032237e+00 -2.73537636e-01 1.16779124e-02 -2.77121723e-01
-5.23838818e-01 -6.90807635e-03 3.40897292e-01 2.87852943e-01
3.52037609e-01 -5.27708083e-02 -5.31079590e-01 4.74367738e-01
2.23682240e-01 -3.48839939e-01 4.83509988e-01 9.57640171e-01
-4.96466756e-01 -1.43391049e+00 -4.23336238e-01 6.65529788e-01
-5.30045390e-01 1.38177112e-01 -1.58960223e-01 6.84108198e-01
2.77934670e-01 7.00133145e-01 -2.85707921e-01 -6.41374171e-01
4.10650611e-01 -9.55413878e-02 3.34094435e-01 -7.82368779e-01
-4.46702808e-01 5.00691354e-01 -2.50134736e-01 -2.70308256e-01
-7.31233537e-01 -8.71967852e-01 -1.00638747e+00 1.10206440e-01
-6.99869037e-01 2.63982296e-01 3.30394983e-01 6.58742309e-01
3.81822884e-01 2.66525805e-01 1.22352862e+00 -5.44242024e-01
-6.50199533e-01 -7.16772735e-01 -1.08638990e+00 6.41018033e-01
1.04874857e-01 -9.64056909e-01 -4.17425841e-01 -5.59239835e-02] | [8.34209156036377, 4.575998783111572] |
e96acd4c-b4b0-4639-8feb-df370a43dfd8 | template-instance-loss-for-offline | 1910.05545 | null | https://arxiv.org/abs/1910.05545v1 | https://arxiv.org/pdf/1910.05545v1.pdf | Template-Instance Loss for Offline Handwritten Chinese Character Recognition | The long-standing challenges for offline handwritten Chinese character recognition (HCCR) are twofold: Chinese characters can be very diverse and complicated while similarly looking, and cursive handwriting (due to increased writing speed and infrequent pen lifting) makes strokes and even characters connected together in a flowing manner. In this paper, we propose the template and instance loss functions for the relevant machine learning tasks in offline handwritten Chinese character recognition. First, the character template is designed to deal with the intrinsic similarities among Chinese characters. Second, the instance loss can reduce category variance according to classification difficulty, giving a large penalty to the outlier instance of handwritten Chinese character. Trained with the new loss functions using our deep network architecture HCCR14Layer model consisting of simple layers, our extensive experiments show that it yields state-of-the-art performance and beyond for offline HCCR. | ['Chi-Keung Tang', 'Dan Meng', 'Cewu Lu', 'Yao Xiao'] | 2019-10-12 | null | null | null | null | ['offline-handwritten-chinese-character', 'offline-handwritten-chinese-character'] | ['computer-vision', 'natural-language-processing'] | [ 2.36557680e-03 -5.58443248e-01 -1.46912217e-01 -4.83146787e-01
-4.68847930e-01 -6.87462866e-01 4.01423335e-01 -5.37346601e-01
-4.11767840e-01 4.85850275e-01 -1.92547351e-01 -2.87787318e-01
7.38813654e-02 -2.83530086e-01 -5.83821952e-01 -7.10096180e-01
1.08328424e-01 4.68825251e-01 7.08895130e-03 -7.81087503e-02
4.90293741e-01 9.91618276e-01 -8.55046749e-01 5.30019462e-01
1.04372752e+00 1.16657031e+00 2.31286883e-01 9.75345612e-01
-1.07568771e-01 1.25479722e+00 -8.19515228e-01 -7.82410741e-01
3.13967645e-01 -3.74478489e-01 -5.05344689e-01 3.05977106e-01
6.85135841e-01 -6.46262705e-01 -9.71914828e-01 9.10887897e-01
5.35132647e-01 9.25770998e-02 7.98108280e-01 -7.87153840e-01
-1.30743849e+00 7.59235144e-01 -3.60241950e-01 -2.41610765e-01
-4.50699404e-02 2.33808726e-01 7.11068094e-01 -1.19818830e+00
5.53158104e-01 8.91106665e-01 9.63023484e-01 9.04882014e-01
-6.83370590e-01 -3.67988020e-01 5.14474571e-01 2.41462752e-01
-1.24667871e+00 -1.88173115e-01 5.77714086e-01 -1.89181045e-01
8.11087191e-01 4.39109921e-01 2.03580141e-01 1.28436399e+00
-2.79763117e-02 1.51831686e+00 7.10556924e-01 -2.32094526e-01
-4.67627272e-02 1.05982855e-01 4.49873745e-01 4.97415781e-01
8.66954476e-02 -2.99675405e-01 -6.09899238e-02 4.58944917e-01
7.31195509e-01 3.53027433e-01 -2.22309336e-01 1.44011542e-01
-1.05591786e+00 3.60824794e-01 3.51953804e-01 1.76910862e-01
1.51197985e-01 3.15956473e-01 5.03866851e-01 4.07834768e-01
-1.79569051e-02 7.74705470e-01 -3.71193886e-01 -5.29657662e-01
-9.32173550e-01 1.23032704e-01 9.60007250e-01 1.55965889e+00
2.98064649e-01 2.19745293e-01 -5.11011004e-01 1.20985556e+00
-1.43420666e-01 5.02187073e-01 5.98831356e-01 -5.21856666e-01
7.82532692e-01 2.83613384e-01 -6.92495182e-02 -9.73901033e-01
-2.89007407e-02 -3.60049427e-01 -1.12980366e+00 5.63249849e-02
6.91042900e-01 -2.07436681e-01 -1.18650770e+00 1.00125206e+00
-6.69846177e-01 -2.13401213e-01 -2.04636857e-01 9.75056529e-01
6.01653337e-01 5.13681531e-01 -3.94155234e-01 3.12058032e-01
8.26703072e-01 -1.56979418e+00 -8.10867846e-01 -2.39664868e-01
2.68320888e-01 -8.63291740e-01 1.45632923e+00 5.71600854e-01
-9.44831014e-01 -5.61455905e-01 -1.16778195e+00 -5.54343998e-01
-4.45265591e-01 9.17580664e-01 4.88334298e-01 5.16212761e-01
-5.63322783e-01 9.82847214e-01 -7.84045219e-01 2.45673042e-02
7.81647146e-01 1.42050227e-02 -1.65851578e-01 -3.50382000e-01
-6.41554475e-01 8.23802650e-01 4.07206826e-02 6.55003130e-01
-7.57445097e-01 -7.28440285e-01 -5.29062927e-01 2.46848300e-01
3.12688679e-01 2.74549931e-01 1.13949895e+00 -9.45556641e-01
-1.92176640e+00 5.94342113e-01 -1.85251515e-02 -2.28052884e-01
1.53530550e+00 -5.21670640e-01 -5.86470544e-01 5.05380668e-02
-4.29608494e-01 2.59389967e-01 8.94641995e-01 -1.01047039e+00
-3.83674145e-01 -2.75474936e-01 -6.54575408e-01 -2.09210552e-02
-4.92315769e-01 -7.83092082e-02 -1.01370418e+00 -1.04060543e+00
-3.53416055e-02 -6.16764069e-01 -1.21786632e-01 1.03114471e-01
-6.65515304e-01 -6.13833545e-03 1.10671163e+00 -9.69941914e-01
1.36527026e+00 -2.30295992e+00 -1.46288231e-01 1.88326657e-01
1.02850288e-01 5.56987822e-01 -4.10770833e-01 2.48742476e-01
3.68433923e-01 3.31068844e-01 -1.51202247e-01 -3.00461590e-01
1.64923206e-01 -1.90784484e-02 -7.66152024e-01 3.41482401e-01
5.12661457e-01 1.04347265e+00 -8.56653333e-01 -1.08606689e-01
-1.04161322e-01 1.72132850e-01 -2.48883575e-01 2.85596699e-01
-6.79728687e-02 -1.43563822e-01 -3.28705966e-01 1.05213654e+00
9.34681416e-01 -2.53407389e-01 1.55929729e-01 -5.08184582e-02
-1.04111172e-01 -2.30660420e-02 -8.10076892e-01 1.13686550e+00
-2.21655816e-01 1.10215950e+00 -4.22530264e-01 -5.45056403e-01
1.28177285e+00 -2.78814048e-01 -2.80106604e-01 -6.77284718e-01
-1.34130329e-01 6.22886777e-01 6.25862414e-03 -3.10925215e-01
8.19777668e-01 5.77494919e-01 1.84648484e-01 2.03658536e-01
-1.31696373e-01 -2.74380803e-01 1.00598328e-01 5.02410010e-02
9.44558918e-01 3.59605849e-02 -2.86286563e-01 -7.08861575e-02
4.41761047e-01 -1.50910646e-01 4.01339471e-01 1.26897216e+00
-2.48362303e-01 1.19375658e+00 7.81205356e-01 -6.66445494e-01
-1.35218441e+00 -8.30961943e-01 -1.89416498e-01 6.19701564e-01
1.27864718e-01 4.36457880e-02 -4.50265765e-01 -7.53635108e-01
3.42767954e-01 4.16153044e-01 -5.93758583e-01 4.78537846e-03
-1.05749059e+00 -4.58328128e-01 1.07095051e+00 1.08597755e+00
8.31873417e-01 -1.04152095e+00 -1.98717222e-01 1.79494962e-01
3.28412563e-01 -1.14671397e+00 -1.02246141e+00 2.74024010e-01
-7.81481147e-01 -9.37055826e-01 -1.48491347e+00 -1.10677254e+00
8.28121245e-01 7.67657682e-02 9.13992822e-01 2.74115145e-01
-5.15204191e-01 -4.82756495e-02 -5.56373477e-01 -1.91257998e-01
-1.92371696e-01 2.87078381e-01 -1.99649617e-01 -3.04265437e-03
2.27057666e-01 1.31336212e-01 -5.20509720e-01 5.15416443e-01
-6.81460500e-01 -2.49301806e-01 6.26447558e-01 1.33024335e+00
4.64268029e-01 -3.26736093e-01 1.93710893e-01 -9.64538634e-01
7.36406684e-01 2.29241662e-02 -5.77498317e-01 8.72695982e-01
-3.95806104e-01 -2.24895626e-01 1.22161949e+00 -9.34524953e-01
-9.21378970e-01 -1.33036196e-01 2.06328984e-02 -6.48672283e-01
1.42218351e-01 4.07166570e-01 -1.73675209e-01 -2.81432569e-01
4.12533313e-01 6.56031430e-01 -6.49651140e-02 -6.29221678e-01
1.82787672e-01 8.61340940e-01 8.46412718e-01 -6.96570277e-01
5.99550009e-01 2.66883820e-01 -3.14317584e-01 -8.72045100e-01
-4.23841894e-01 -6.26150221e-02 -7.39479542e-01 -1.63820505e-01
6.18398786e-01 -6.51224971e-01 -8.01198483e-01 1.48016798e+00
-1.01572740e+00 -8.79935503e-01 -6.81700706e-02 1.74807414e-01
-2.40977213e-01 8.03487718e-01 -1.17076194e+00 -8.12286913e-01
-2.94140637e-01 -1.16908383e+00 7.01059401e-01 4.37402695e-01
3.05466801e-01 -7.76288807e-01 -4.31766272e-01 -1.84640378e-01
5.74859977e-01 2.75951717e-02 8.42725635e-01 -6.06933892e-01
-6.44894600e-01 -7.25026608e-01 -6.12764120e-01 9.43119347e-01
1.96856558e-01 5.23413360e-01 -8.15454185e-01 -2.77133405e-01
-3.48825783e-01 -6.03680253e-01 1.14738035e+00 -5.52409142e-02
1.98285973e+00 -3.28375846e-01 1.67419426e-02 1.09352779e+00
1.35682690e+00 4.74343508e-01 1.17897117e+00 2.03409046e-01
1.07628906e+00 1.49088740e-01 3.99451733e-01 5.20786226e-01
5.71677499e-02 4.38674837e-01 -1.15434013e-01 -7.60322958e-02
-1.37177512e-01 -4.10073936e-01 2.87189335e-01 8.47300053e-01
-2.48803824e-01 -3.37770820e-01 -9.30251360e-01 1.44375116e-01
-1.77063751e+00 -9.47781801e-01 -1.19230501e-01 2.09513783e+00
8.69788229e-01 -5.64391799e-02 -2.55238086e-01 -2.11971000e-01
6.65834188e-01 7.68798143e-02 -8.83186460e-01 -4.77619976e-01
-7.11420655e-01 5.16361669e-02 7.62064576e-01 1.40524492e-01
-1.09145606e+00 1.20589030e+00 6.65483952e+00 1.06486070e+00
-1.43135476e+00 -6.17247403e-01 1.19446540e+00 2.55589455e-01
-4.76133898e-02 -3.58068019e-01 -1.00469148e+00 6.94307506e-01
1.96652964e-01 1.29261687e-01 7.34825075e-01 9.55772698e-01
-1.36407271e-01 3.77746135e-01 -1.30739820e+00 1.03850031e+00
2.30652273e-01 -1.53334141e+00 3.37495387e-01 -1.79053009e-01
9.72741604e-01 -1.80922166e-01 3.69746864e-01 2.78260410e-01
1.95668340e-02 -1.33962178e+00 1.01916313e+00 7.25334883e-01
1.12605977e+00 -6.52414441e-01 7.07946241e-01 7.76847973e-02
-7.99484491e-01 -2.23750040e-01 -7.13163972e-01 1.45777196e-01
-1.27715766e-01 2.69943833e-01 -2.84359187e-01 1.67238638e-01
5.08022308e-01 1.01352143e+00 -8.33841562e-01 1.10777950e+00
-2.11361557e-01 4.98461783e-01 1.44434422e-01 -5.60403705e-01
5.20999908e-01 -3.63856018e-01 9.39114690e-02 1.63356137e+00
1.70133397e-01 8.33692476e-02 -1.32817537e-01 1.11551619e+00
-3.07893842e-01 -2.51456112e-01 -7.52465576e-02 -6.43928230e-01
4.78419274e-01 1.04235828e+00 -6.02914095e-01 -4.33728844e-01
-1.69680834e-01 1.56776154e+00 5.36712587e-01 5.69813192e-01
-8.27402711e-01 -1.11593485e+00 5.44141948e-01 -4.67454970e-01
5.30568600e-01 -4.32647705e-01 -7.73551047e-01 -1.61578858e+00
3.12103719e-01 -1.21537566e+00 -4.79236990e-02 -3.82039666e-01
-1.74466383e+00 6.93989694e-01 -9.45707023e-01 -1.26720357e+00
2.39221454e-01 -1.36867034e+00 -9.51245844e-01 8.62981856e-01
-1.37045908e+00 -9.95922506e-01 -5.10571003e-01 4.31692451e-01
7.87903965e-01 -5.04152596e-01 4.80735809e-01 4.34323460e-01
-8.93994689e-01 1.60216486e+00 6.11311376e-01 8.51891398e-01
7.26640284e-01 -1.40196884e+00 8.46278250e-01 9.68010783e-01
-2.32122585e-01 7.37492442e-01 6.06816411e-02 -6.33597612e-01
-1.81024122e+00 -1.02715659e+00 6.52091920e-01 -4.35026824e-01
6.23412669e-01 -6.48497760e-01 -1.08542538e+00 4.22212929e-01
-4.31451708e-01 8.79408494e-02 3.06009382e-01 -1.80028483e-01
-7.17948675e-01 -5.74707314e-02 -8.07622433e-01 8.69958043e-01
8.30033839e-01 -6.93902850e-01 -1.70897871e-01 3.95722210e-01
3.11610579e-01 -6.62391543e-01 -5.47513664e-01 1.06633991e-01
9.82840598e-01 -5.77603221e-01 7.08418846e-01 -1.01645446e+00
9.38035131e-01 -1.27052039e-01 -7.31289387e-02 -9.21299160e-01
-4.30250555e-01 -8.10089827e-01 -1.96283564e-01 1.11408305e+00
6.61343932e-01 -3.03799868e-01 8.33723068e-01 8.83472383e-01
-3.76741678e-01 -9.03391659e-01 -4.04848546e-01 -1.19929743e+00
4.81409550e-01 -7.61307329e-02 5.06151795e-01 1.01560211e+00
-5.76622784e-02 -3.25684518e-01 -7.91628063e-01 -1.23971447e-01
3.49421471e-01 -4.37012576e-02 6.36201024e-01 -5.63369334e-01
-4.03602630e-01 -8.95190895e-01 -2.84191489e-01 -1.59126222e+00
-7.82253966e-02 -5.91941237e-01 2.50289798e-01 -1.04280460e+00
2.51852155e-01 -6.28217876e-01 -3.15797850e-02 3.07662934e-01
-4.04175907e-01 1.19214088e-01 7.05441833e-01 2.97625989e-01
-5.23666799e-01 4.24160779e-01 1.42560184e+00 -4.36180115e-01
-1.41646340e-01 1.65817171e-01 -2.79831052e-01 3.21936220e-01
5.31589687e-01 2.61849403e-01 2.94239759e-01 -1.00710785e+00
-3.10545303e-02 -3.08442026e-01 6.86927885e-02 -7.58476019e-01
5.34692407e-01 -8.66398066e-02 8.85832667e-01 -6.46614492e-01
-2.24123411e-02 -6.01986349e-01 -4.71838295e-01 5.53772271e-01
-4.88352656e-01 2.01257929e-01 5.15115121e-03 4.06558216e-01
-3.61974329e-01 -2.96501130e-01 9.60376680e-01 -1.24938615e-01
-7.65714467e-01 3.15136284e-01 -3.15109730e-01 6.64844438e-02
5.73782444e-01 -5.22834420e-01 -5.23800135e-01 -3.18986475e-01
-3.02102000e-01 2.93836385e-01 3.15659106e-01 5.07106185e-01
8.42165291e-01 -1.25304878e+00 -6.72328711e-01 2.19383016e-01
-7.79973459e-04 -1.44359872e-01 2.52208322e-01 5.61531544e-01
-1.27824676e+00 2.91772693e-01 -2.86651075e-01 -2.37879947e-01
-8.74241054e-01 3.68394524e-01 5.49672246e-01 -1.39062628e-01
-7.56872535e-01 1.08273244e+00 -3.26041460e-01 -3.80742610e-01
9.40165639e-01 -6.17529094e-01 1.70827061e-01 -1.35452837e-01
8.68225992e-01 8.32862914e-01 1.03922874e-01 5.68181165e-02
-2.55488425e-01 4.62225527e-01 -6.77918375e-01 3.46824169e-01
1.23974121e+00 3.27168822e-01 -2.59263664e-02 1.57417864e-01
1.31853127e+00 -4.60833423e-02 -1.76701522e+00 7.81598687e-02
1.33878648e-01 -7.56854236e-01 -5.75722158e-01 -1.10709119e+00
-1.10504270e+00 1.00123775e+00 3.01239848e-01 -1.78292468e-01
8.32352579e-01 -5.51632643e-01 7.72136927e-01 1.09594929e+00
9.75053757e-02 -1.61840582e+00 3.48442107e-01 1.25199878e+00
9.46644306e-01 -1.24088085e+00 -1.72715411e-01 -8.43979791e-02
-1.06480587e+00 1.76034141e+00 8.56587112e-01 -4.19985473e-01
3.88866305e-01 4.24882025e-01 3.43975186e-01 3.03265631e-01
-4.06926483e-01 3.75649184e-01 3.20901841e-01 4.80810016e-01
4.23580199e-01 1.47837371e-01 -1.83613390e-01 8.17505419e-01
7.84010068e-02 -2.31880933e-01 6.84246361e-01 6.52990401e-01
-5.26724234e-02 -9.70778108e-01 1.18353814e-01 5.49299717e-01
-3.56402367e-01 -2.41561741e-01 -7.95573354e-01 6.14729285e-01
-3.82694125e-01 4.67957228e-01 2.07735524e-01 -4.60232586e-01
4.06207174e-01 -2.76502818e-01 4.55502838e-01 -1.06409773e-01
-6.68823600e-01 -2.36141056e-01 -2.71613508e-01 -3.96832675e-01
5.11571229e-01 -3.88509691e-01 -9.72332239e-01 -2.95704573e-01
-3.72858196e-01 -3.51167619e-01 5.89923799e-01 6.73543632e-01
2.26930156e-01 2.84951180e-01 9.46913719e-01 -7.88888097e-01
-1.40349972e+00 -7.64992654e-01 -7.92044759e-01 5.37797213e-01
3.39404434e-01 1.17265120e-01 -3.63876313e-01 -1.35715064e-02] | [11.894505500793457, 2.4509899616241455] |
6bd69402-4b65-495f-aeb2-1439b8c3b84f | decoupling-representation-and-classifier-for | 1910.09217 | null | https://arxiv.org/abs/1910.09217v2 | https://arxiv.org/pdf/1910.09217v2.pdf | Decoupling Representation and Classifier for Long-Tailed Recognition | The long-tail distribution of the visual world poses great challenges for deep learning based classification models on how to handle the class imbalance problem. Existing solutions usually involve class-balancing strategies, e.g., by loss re-weighting, data re-sampling, or transfer learning from head- to tail-classes, but most of them adhere to the scheme of jointly learning representations and classifiers. In this work, we decouple the learning procedure into representation learning and classification, and systematically explore how different balancing strategies affect them for long-tailed recognition. The findings are surprising: (1) data imbalance might not be an issue in learning high-quality representations; (2) with representations learned with the simplest instance-balanced (natural) sampling, it is also possible to achieve strong long-tailed recognition ability by adjusting only the classifier. We conduct extensive experiments and set new state-of-the-art performance on common long-tailed benchmarks like ImageNet-LT, Places-LT and iNaturalist, showing that it is possible to outperform carefully designed losses, sampling strategies, even complex modules with memory, by using a straightforward approach that decouples representation and classification. Our code is available at https://github.com/facebookresearch/classifier-balancing. | ['Marcus Rohrbach', 'Yannis Kalantidis', 'Zhicheng Yan', 'Saining Xie', 'Jiashi Feng', 'Bingyi Kang', 'Albert Gordo'] | 2019-10-21 | null | https://openreview.net/forum?id=r1gRTCVFvB | https://openreview.net/pdf?id=r1gRTCVFvB | iclr-2020-1 | ['long-tail-learning-with-class-descriptors'] | ['methodology'] | [ 8.25352967e-02 -2.15397641e-01 -4.18502182e-01 -5.92891335e-01
-8.56786728e-01 -5.22439718e-01 5.84156632e-01 1.56909347e-01
-5.59258103e-01 6.58983707e-01 1.41957536e-01 -4.15575683e-01
-9.91406366e-02 -7.29746103e-01 -9.48081374e-01 -5.84044933e-01
2.99393982e-02 5.77808738e-01 1.46876678e-01 -2.24821046e-01
1.85941234e-01 5.62384188e-01 -1.92137873e+00 6.26920998e-01
6.55112803e-01 1.26842725e+00 -2.53343999e-01 7.54222393e-01
-2.66001165e-01 1.01264167e+00 -5.90340436e-01 -6.60490632e-01
3.51621777e-01 -3.41462523e-01 -7.55241215e-01 -1.08810574e-01
8.70825768e-01 -2.00660393e-01 -1.59218445e-01 9.19461310e-01
7.80555010e-01 -1.02564536e-01 9.16182280e-01 -1.50775874e+00
-6.03787720e-01 4.54315245e-01 -1.05209315e+00 2.94503033e-01
2.34194286e-02 3.48544985e-01 1.17051077e+00 -6.65146768e-01
3.80619824e-01 1.38372660e+00 8.61894786e-01 5.86740017e-01
-1.52955604e+00 -9.13304508e-01 3.03498089e-01 4.47978348e-01
-1.11657298e+00 -5.41696429e-01 5.43839931e-01 -6.84146643e-01
9.46600437e-01 3.69047374e-01 3.34649861e-01 1.24326622e+00
1.20916694e-01 9.66316164e-01 1.16573334e+00 -3.25082451e-01
4.07069437e-02 5.98754883e-02 3.61069977e-01 4.23543036e-01
3.92951280e-01 8.13877806e-02 -5.09898007e-01 -1.09387778e-01
3.06572348e-01 3.30815725e-02 -2.08591655e-01 -7.27443159e-01
-1.06755233e+00 8.39608192e-01 6.43989861e-01 -2.08371077e-02
-5.79164363e-02 2.82869756e-01 8.49238396e-01 7.44992554e-01
6.04938865e-01 4.07416433e-01 -5.71574330e-01 -5.33185303e-02
-9.41133678e-01 3.87088180e-01 7.61208594e-01 7.08777905e-01
8.61079514e-01 -4.32029329e-02 -3.21591020e-01 9.74099815e-01
-4.95322347e-02 1.96960077e-01 6.56614661e-01 -6.33509278e-01
4.16598916e-01 3.72265249e-01 -2.25185454e-01 -8.75116229e-01
-3.93939793e-01 -7.69255996e-01 -1.05777884e+00 6.17713571e-01
7.17427433e-01 -2.55086143e-02 -1.10917056e+00 1.88749170e+00
2.39887573e-02 -4.64727208e-02 -2.39337116e-01 6.83953524e-01
7.49984562e-01 4.15907651e-01 2.53261328e-01 1.22106820e-01
1.24365902e+00 -9.64173794e-01 -3.06147039e-01 -3.62303674e-01
6.66358829e-01 -6.40601158e-01 1.42763901e+00 5.76074958e-01
-1.08141375e+00 -5.71849167e-01 -1.11515296e+00 -1.70886949e-01
-4.26274508e-01 -3.68008316e-02 5.31175077e-01 5.68795025e-01
-9.12981987e-01 7.10379899e-01 -6.80299938e-01 -1.81562379e-01
8.59040678e-01 2.34574765e-01 -4.59573239e-01 -3.84817213e-01
-8.15393746e-01 8.67931247e-01 1.13047473e-01 -2.46545374e-01
-9.07162488e-01 -8.66008878e-01 -8.16943467e-01 9.12925005e-02
8.82060304e-02 -7.01391459e-01 1.27123952e+00 -1.55291009e+00
-1.15012753e+00 1.25820780e+00 6.21857755e-02 -5.17961621e-01
8.40965986e-01 -2.12359756e-01 -1.98090989e-02 -3.43136579e-01
-6.65730909e-02 6.88548148e-01 9.12234604e-01 -1.19631243e+00
-3.75431895e-01 -5.17012179e-01 -3.68947275e-02 3.82239632e-02
-3.86539161e-01 2.26886421e-02 -7.64725655e-02 -6.39559507e-01
-1.44678935e-01 -6.26172185e-01 -5.77729307e-02 4.64132071e-01
-3.01352024e-01 -9.39690918e-02 3.50874960e-01 -4.84104186e-01
1.01672900e+00 -2.15616679e+00 4.94396351e-02 -5.35449982e-02
2.99628615e-01 2.95048922e-01 -4.64729279e-01 1.80022806e-01
-4.91179436e-01 1.38598576e-01 -1.40389591e-01 -5.29182851e-01
1.21613994e-01 9.61641222e-02 -3.62563372e-01 6.70266390e-01
2.90003866e-01 9.24985230e-01 -6.32369220e-01 -1.73995510e-01
-1.26473233e-01 3.44639003e-01 -8.45962167e-01 2.58286059e-01
-2.14925766e-01 9.76379067e-02 1.46011114e-01 6.63699925e-01
8.89140785e-01 -3.82289797e-01 5.40365465e-02 -2.68246949e-01
1.87079281e-01 4.40709859e-01 -1.13006020e+00 1.42104244e+00
-5.46118319e-01 7.00750589e-01 8.72374624e-02 -1.33087909e+00
6.94578469e-01 -2.81139672e-01 8.38254020e-02 -1.06107986e+00
-8.33455399e-02 2.47964323e-01 1.01517431e-01 -2.84981102e-01
1.73447177e-01 -2.80937642e-01 1.03083059e-01 3.49916756e-01
1.95977524e-01 5.50508648e-02 1.43715099e-01 -2.82619195e-03
1.05717731e+00 3.06184832e-02 1.60391495e-01 -1.80866346e-01
8.70597139e-02 -2.43315771e-01 6.01912081e-01 8.03372324e-01
-2.17735484e-01 9.18840826e-01 9.65110838e-01 -5.36643267e-01
-1.02471685e+00 -1.05566096e+00 -3.53809863e-01 1.62789500e+00
-1.61427245e-01 -2.55957812e-01 -5.29560566e-01 -8.03826451e-01
3.70851666e-01 5.28755367e-01 -8.29083562e-01 -4.59019303e-01
-3.60833704e-01 -1.19794750e+00 5.30676544e-01 6.29215896e-01
2.87421286e-01 -9.34396625e-01 -4.61568892e-01 -4.57105041e-02
5.07363416e-02 -5.93422055e-01 -1.99675664e-01 6.49283051e-01
-7.14159131e-01 -1.03657591e+00 -8.07549715e-01 -4.61498469e-01
5.36209524e-01 2.18111709e-01 1.72934735e+00 2.02803165e-01
-4.28809464e-01 1.25807852e-01 -1.44246504e-01 -3.96494240e-01
-1.09418474e-01 3.20608258e-01 -3.01578045e-01 5.09973057e-03
2.42502540e-01 -6.52273476e-01 -7.69068360e-01 4.70326453e-01
-8.02395105e-01 -1.61216468e-01 6.54370725e-01 1.00746691e+00
5.23819387e-01 -2.82787889e-01 7.27574706e-01 -9.93508637e-01
5.09701550e-01 -7.63309181e-01 -4.43929613e-01 1.76129863e-01
-6.44903839e-01 -3.00147524e-03 5.06274104e-01 -5.69612145e-01
-6.60491705e-01 -2.35159963e-01 -3.00328970e-01 -3.89848143e-01
-1.70612201e-01 1.81808472e-01 -2.92744011e-01 4.71257754e-02
1.01207459e+00 1.16481803e-01 1.92109779e-01 -5.86884320e-01
3.32147628e-01 6.04728699e-01 2.83766299e-01 -6.75992548e-01
4.95848686e-01 4.00536418e-01 -3.09864283e-01 -4.55395550e-01
-1.00226176e+00 -3.18158090e-01 -3.74343574e-01 3.64023186e-02
5.68584561e-01 -1.14493763e+00 -6.35634482e-01 7.67470658e-01
-8.38955641e-01 -7.02122331e-01 -5.03290534e-01 1.59057200e-01
-6.15860522e-01 4.61437218e-02 -5.79453886e-01 -4.98247296e-01
-2.07472205e-01 -1.11964118e+00 1.04983544e+00 -6.50907531e-02
-2.10887372e-01 -6.59715414e-01 1.50177881e-01 4.66686845e-01
7.62488663e-01 1.41087502e-01 1.07264495e+00 -6.58270597e-01
-4.13941473e-01 -7.66116455e-02 -5.82272351e-01 6.90501392e-01
-9.68928412e-02 -3.74817029e-02 -1.28654289e+00 -6.51548684e-01
-3.95279974e-01 -9.38895762e-01 1.48510671e+00 2.21401200e-01
1.75452030e+00 -2.65520424e-01 -3.47038353e-04 1.07922411e+00
1.25487971e+00 -3.76402557e-01 9.34531212e-01 4.58547711e-01
6.19926155e-01 5.78096628e-01 2.69927114e-01 4.18759257e-01
5.48518717e-01 6.49938166e-01 7.16600776e-01 -1.81806833e-01
-4.42694783e-01 -1.54312536e-01 2.28897482e-01 4.84373152e-01
3.38550448e-01 -3.33101541e-01 -1.02231145e+00 5.83524168e-01
-1.73716533e+00 -8.94963801e-01 1.49048105e-01 2.25822163e+00
1.11828852e+00 2.97128618e-01 3.77154559e-01 3.27113301e-01
4.69539613e-01 2.98258752e-01 -7.19559371e-01 -4.21700120e-01
-1.35011643e-01 9.49688479e-02 5.23320496e-01 3.18374991e-01
-1.16377997e+00 5.93240798e-01 6.19912338e+00 1.12288439e+00
-1.31824338e+00 1.27252862e-01 1.20277131e+00 -4.07903910e-01
-3.72095853e-01 -3.53381902e-01 -8.43774796e-01 5.59616208e-01
8.32170069e-01 7.39289820e-02 3.78457963e-01 9.17974591e-01
-3.79275203e-01 1.59163967e-01 -1.23554635e+00 1.09264791e+00
8.83257762e-02 -1.28069019e+00 2.49399185e-01 1.11002577e-04
5.89740753e-01 3.68060440e-01 1.86550319e-01 6.15434825e-01
2.93062717e-01 -1.37565017e+00 8.29146802e-01 5.07183015e-01
1.01867771e+00 -6.63138449e-01 5.97966135e-01 2.91419923e-01
-7.26114213e-01 -2.64292449e-01 -5.85209370e-01 -1.57759711e-01
-5.08335888e-01 9.53394771e-01 -3.13870251e-01 1.08875036e-01
9.03113961e-01 8.45687389e-01 -8.33846509e-01 1.35519838e+00
7.14541897e-02 6.12328589e-01 -1.30188689e-01 2.28450119e-01
-8.07072297e-02 2.45793685e-01 1.13547698e-01 1.41095793e+00
1.66753128e-01 -5.20832419e-01 1.10464968e-01 5.79609156e-01
-3.63146216e-01 2.49331817e-03 -5.74128389e-01 2.16163486e-01
9.78390276e-02 1.04949749e+00 -4.94865209e-01 -2.57274717e-01
-4.13545251e-01 7.11450994e-01 8.05865765e-01 1.91821277e-01
-6.66288197e-01 -3.61840338e-01 1.07973897e+00 4.33383524e-01
3.94936085e-01 1.23561114e-01 -4.89771247e-01 -1.32778919e+00
4.17119637e-02 -1.32545531e+00 6.60333216e-01 -5.35192847e-01
-1.69518793e+00 5.93831182e-01 -1.88699916e-01 -1.19385326e+00
-1.24019533e-01 -7.42686093e-01 -5.03896654e-01 6.18745387e-01
-2.00371337e+00 -1.00362110e+00 -3.94275814e-01 6.35491371e-01
4.29727584e-01 -7.14599118e-02 6.06951654e-01 6.65762007e-01
-5.77165425e-01 1.05010474e+00 1.57668442e-01 2.98328865e-02
9.52544808e-01 -1.44338131e+00 2.15243310e-01 4.19723570e-01
1.42301977e-01 2.53357202e-01 5.66711307e-01 -1.65811911e-01
-1.13111389e+00 -1.07489932e+00 5.58854043e-01 -4.07877922e-01
5.41864216e-01 -6.70295537e-01 -1.19768465e+00 6.45993650e-01
1.65306926e-01 5.24379730e-01 7.49573410e-01 3.03189397e-01
-1.04287946e+00 -5.63692987e-01 -1.13513982e+00 3.15338016e-01
1.07991958e+00 -4.38259423e-01 -3.51347506e-01 4.13104713e-01
4.13748533e-01 -2.88322389e-01 -3.98972839e-01 5.09398460e-01
8.08445513e-01 -1.20516825e+00 1.09401608e+00 -9.23206389e-01
6.04214370e-01 -5.09862415e-02 -3.15171331e-01 -1.56864059e+00
-3.56281370e-01 -2.04834685e-01 -4.01070341e-02 1.18970037e+00
4.33665633e-01 -7.32231677e-01 8.75882328e-01 2.50817060e-01
1.58993602e-01 -9.74805593e-01 -9.17049825e-01 -7.89879203e-01
5.33582270e-01 -4.19278204e-01 6.17387772e-01 9.04651165e-01
-5.25424182e-01 2.33046830e-01 -3.73940408e-01 -2.26718128e-01
6.47946537e-01 1.99108720e-01 9.60782707e-01 -1.31083941e+00
-5.19546151e-01 -7.82003224e-01 -5.98257363e-01 -1.02039301e+00
2.72541791e-01 -1.06942856e+00 -1.05629295e-01 -1.21530592e+00
4.25143242e-01 -6.10348642e-01 -6.23010397e-01 6.50467694e-01
-9.45172384e-02 4.57426220e-01 2.52312124e-01 1.17329009e-01
-7.67059863e-01 5.87094069e-01 1.09243190e+00 -3.74547511e-01
2.49616608e-01 6.92459419e-02 -9.99183178e-01 7.11682320e-01
7.73927331e-01 -5.03239870e-01 -4.77746308e-01 -6.71358287e-01
4.95698541e-01 -3.20841759e-01 5.11991560e-01 -1.06780136e+00
7.93734416e-02 1.77896246e-02 6.09475434e-01 -3.03326368e-01
1.96746111e-01 -6.89817846e-01 -2.20704839e-01 3.89879584e-01
-6.39995873e-01 1.18862942e-01 4.00905073e-01 5.70188999e-01
-2.61641413e-01 -5.88310547e-02 1.13717854e+00 -1.98884085e-01
-4.06022519e-01 2.77424604e-01 -6.07681796e-02 5.32916307e-01
8.30335498e-01 -5.55639639e-02 -6.95698559e-01 -4.22968030e-01
-5.28435767e-01 2.63759881e-01 4.86009210e-01 3.84704113e-01
4.30135041e-01 -1.25131845e+00 -8.85159075e-01 3.78004640e-01
3.73921007e-01 -3.63264941e-02 1.51305512e-01 7.21453547e-01
-4.06300902e-01 -1.91909447e-01 -4.74666774e-01 -7.53383815e-01
-1.13884425e+00 3.64735931e-01 6.60431802e-01 -3.78620714e-01
-3.85897815e-01 1.10036051e+00 4.50029343e-01 -7.35942900e-01
6.37336254e-01 -2.24146813e-01 1.47944121e-02 5.59490561e-01
6.89785063e-01 2.22788289e-01 4.06629354e-01 -3.13874990e-01
-4.59002167e-01 4.93110687e-01 -3.23123544e-01 3.89603645e-01
1.55568862e+00 1.53331444e-01 -4.50612716e-02 4.91707355e-01
1.40378380e+00 -2.99808025e-01 -1.34307158e+00 -1.63364172e-01
-1.05200902e-01 -6.69878006e-01 1.85594261e-02 -9.77488995e-01
-1.40772450e+00 1.24950659e+00 8.07887375e-01 1.43458024e-01
1.23056901e+00 -1.03012346e-01 5.74782908e-01 3.74704540e-01
2.45831400e-01 -7.57151961e-01 2.63173550e-01 4.83255416e-01
1.12178183e+00 -1.37948930e+00 -5.88174909e-02 2.04065200e-02
-4.45373297e-01 8.26653361e-01 8.49946380e-01 -2.43520126e-01
7.96820760e-01 4.03311253e-01 1.09195434e-01 -3.12153948e-03
-1.18783879e+00 -1.62443370e-01 2.39455506e-01 6.24712288e-01
6.20294571e-01 2.02348642e-02 1.58633545e-01 4.31824505e-01
-1.19011879e-01 -1.47320747e-01 3.95245016e-01 6.82533324e-01
-2.98285931e-01 -9.95206535e-01 -1.99107960e-01 7.88324654e-01
-5.12516916e-01 -1.40562251e-01 -2.03570649e-01 5.89268506e-01
1.07209280e-01 5.22901535e-01 3.21435034e-01 -2.80288339e-01
5.10943413e-01 1.95722319e-02 4.47548896e-01 -5.58567107e-01
-6.25379562e-01 -3.95458817e-01 8.10954534e-03 -8.84148002e-01
-5.54740280e-02 -5.68685472e-01 -5.50634861e-01 -4.12797362e-01
-1.61577821e-01 -2.87945211e-01 5.35946012e-01 4.52082843e-01
5.61790526e-01 5.46973586e-01 5.23954988e-01 -9.95334685e-01
-1.01690125e+00 -7.63395071e-01 -5.50200343e-01 6.59198046e-01
8.04733217e-01 -7.38180578e-01 -7.19372094e-01 -2.88155228e-01] | [9.509749412536621, 2.8889870643615723] |
ecd85b9d-6421-462f-84df-60ee4e70898e | synthesis-of-stabilizing-recurrent | 2204.00122 | null | https://arxiv.org/abs/2204.00122v3 | https://arxiv.org/pdf/2204.00122v3.pdf | Synthesis of Stabilizing Recurrent Equilibrium Network Controllers | We propose a parameterization of a nonlinear dynamic controller based on the recurrent equilibrium network, a generalization of the recurrent neural network. We derive constraints on the parameterization under which the controller guarantees exponential stability of a partially observed dynamical system with sector bounded nonlinearities. Finally, we present a method to synthesize this controller using projected policy gradient methods to maximize a reward function with arbitrary structure. The projection step involves the solution of convex optimization problems. We demonstrate the proposed method with simulated examples of controlling nonlinear plants, including plants modeled with neural networks. | ['Peter Seiler', 'Murat Arcak', 'Fangda Gu', 'He Yin', 'Neelay Junnarkar'] | 2022-03-31 | null | null | null | null | ['policy-gradient-methods'] | ['methodology'] | [ 3.80807042e-01 9.18792069e-01 -5.53282559e-01 2.83449560e-01
-2.14390680e-01 -7.92097867e-01 3.28143895e-01 -7.55870700e-01
-1.22889504e-01 9.82633650e-01 -2.62738198e-01 -5.93895793e-01
-3.12513113e-01 -1.62814021e-01 -8.77848506e-01 -9.29229259e-01
-4.15671319e-02 1.05452813e-01 -3.76370609e-01 -2.93281168e-01
3.34867425e-02 6.70589566e-01 -6.83684528e-01 -5.83089352e-01
5.33769011e-01 7.12107182e-01 3.34495783e-01 7.17427909e-01
1.10593593e+00 6.50014222e-01 -1.90374911e-01 6.14679277e-01
9.76905465e-01 -3.76458019e-01 -1.86778992e-01 5.97319186e-01
-6.22108318e-02 -4.01925147e-01 -5.01303256e-01 1.42947114e+00
4.71450448e-01 5.58606625e-01 5.97106874e-01 -1.16081679e+00
-6.92708552e-01 6.21081591e-01 -6.06112145e-02 -1.18519008e-01
-3.85767907e-01 2.99349338e-01 8.65951300e-01 -8.44989896e-01
6.38399422e-01 1.21906126e+00 4.45531279e-01 7.07331777e-01
-1.39985991e+00 -5.96047163e-01 3.18079144e-01 -3.51564229e-01
-1.25914025e+00 -5.90544641e-01 4.10521179e-01 -4.62897152e-01
9.81940389e-01 4.82094772e-02 5.21274269e-01 8.17578614e-01
3.63482058e-01 5.62030733e-01 9.30229962e-01 -1.34439424e-01
2.57323861e-01 3.24163854e-01 7.76924146e-03 9.26665545e-01
4.44676578e-01 7.71826088e-01 3.47397089e-01 -3.07602555e-01
1.10185611e+00 -7.40275979e-02 -6.04593933e-01 -5.91913640e-01
-9.98171091e-01 8.44214022e-01 3.63544255e-01 -3.17847937e-01
-7.92303085e-01 1.94623873e-01 -1.53931588e-01 6.10222280e-01
3.01309526e-01 9.44379449e-01 -4.70424116e-01 4.60805833e-01
-1.00859299e-01 2.10141063e-01 1.06795228e+00 1.19727254e+00
3.09544891e-01 1.15811038e+00 -3.47544663e-02 5.69764078e-01
4.16034460e-01 1.05153203e+00 3.51910561e-01 -1.39319050e+00
2.74290800e-01 3.72026294e-01 7.75063097e-01 -7.89820373e-01
-3.48204941e-01 -5.14569163e-01 -8.43572676e-01 5.25095105e-01
8.43699947e-02 -1.11773741e+00 -7.10684597e-01 1.93731177e+00
9.41023678e-02 3.25296819e-01 4.67629582e-01 9.55808103e-01
-3.88175845e-01 1.06606340e+00 -7.18144953e-01 -9.76848722e-01
4.00580764e-01 -8.98654282e-01 -1.14863181e+00 -1.19307607e-01
2.34401897e-01 -4.72418927e-02 8.70299816e-01 1.11305244e-01
-1.47419369e+00 8.56198743e-02 -1.20379353e+00 6.77113831e-01
-1.57064840e-01 7.84684896e-01 -3.11583966e-01 7.86442384e-02
-1.03877366e+00 8.73761475e-01 -1.07028770e+00 -1.74577534e-01
-5.57123303e-01 7.84687519e-01 5.92358448e-02 1.04925299e+00
-1.06105471e+00 1.13935840e+00 7.45801508e-01 7.92234957e-01
-1.31116021e+00 -4.40824360e-01 -5.24855137e-01 2.32659519e-01
1.03663039e+00 -5.02684832e-01 1.48304772e+00 -7.98619747e-01
-2.52247763e+00 2.23571658e-01 1.87610220e-02 -7.06237435e-01
1.60018906e-01 -1.44158587e-01 -1.43201321e-01 -1.01539455e-01
-3.46089154e-01 1.35526493e-01 1.24555540e+00 -1.03660858e+00
-5.30678272e-01 1.21341020e-01 -1.50215760e-01 4.52739775e-01
-5.04204690e-01 -2.53878802e-01 2.62197107e-01 -3.91257167e-01
-3.78924818e-03 -1.62701321e+00 -7.18291700e-01 -6.00688718e-02
-7.22595632e-01 2.22226933e-01 1.06012464e+00 -4.85787213e-01
1.27948737e+00 -1.76936007e+00 7.50338972e-01 5.27243674e-01
-1.62595838e-01 2.58767575e-01 -1.48423677e-02 4.27455634e-01
-2.35998765e-01 8.18435028e-02 -2.02928543e-01 1.33372888e-01
-4.87020053e-02 1.22829117e-01 -1.09539771e+00 6.19141877e-01
2.15722695e-01 6.40492916e-01 -5.52501559e-01 3.88883859e-01
-6.19689003e-03 3.46415564e-02 -2.77949303e-01 3.49499851e-01
-3.97348046e-01 2.02822804e-01 -7.87402093e-01 7.02176541e-02
-3.57918739e-02 -2.86729842e-01 4.63594764e-01 1.40255034e-01
-5.68901598e-01 -1.96694642e-01 -1.26553512e+00 5.36328793e-01
-3.58665884e-01 5.02213955e-01 8.55373740e-01 -1.33364558e+00
9.33822095e-01 7.16849983e-01 2.59311318e-01 3.40970784e-01
6.40067518e-01 2.44996756e-01 -1.63496640e-02 -2.53199428e-01
1.18235044e-01 -3.80345993e-02 1.14727125e-01 2.86871850e-01
-5.36337122e-02 -4.06281084e-01 -1.62579820e-01 -1.61702082e-01
7.64475524e-01 -2.00123727e-01 7.52368093e-01 -5.71577013e-01
8.26086402e-01 -4.48840149e-02 6.72756195e-01 5.23732305e-01
-2.13503763e-01 -1.64848596e-01 6.20030105e-01 2.05090776e-01
-1.32755506e+00 -4.96525586e-01 2.45273843e-01 6.02630317e-01
-2.25315377e-01 3.63242596e-01 -5.68325877e-01 -6.76793605e-02
9.50298682e-02 5.18703759e-01 -5.88373303e-01 -5.73551476e-01
-7.08950758e-01 -3.52416009e-01 1.34497359e-01 2.87061840e-01
2.10776925e-01 -8.07347357e-01 -5.60142457e-01 4.39892232e-01
3.77730131e-01 -1.07609951e+00 -7.29314923e-01 4.39144135e-01
-1.00524735e+00 -8.12787235e-01 -8.58968377e-01 -1.02617121e+00
1.00230443e+00 -8.70968774e-02 2.60472804e-01 -4.84626621e-01
7.98009709e-02 5.56718349e-01 6.06905341e-01 -4.61081713e-01
-6.94348156e-01 5.23410514e-02 7.94884205e-01 3.78901437e-02
-7.90565491e-01 -1.88808471e-01 -1.39166430e-01 5.59088826e-01
-4.09763545e-01 1.57033265e-01 3.46728146e-01 1.12425804e+00
8.06075275e-01 -6.00959770e-02 6.67853534e-01 -5.93398213e-01
1.23448205e+00 -4.02093947e-01 -1.88744497e+00 4.26207691e-01
-9.08307135e-01 1.87692106e-01 9.97365832e-01 -1.05831432e+00
-1.06436121e+00 8.78646493e-01 8.54946494e-01 -9.60566700e-01
5.37327528e-01 6.53698802e-01 1.77335918e-01 -2.07517624e-01
6.51501954e-01 2.01721951e-01 8.03892612e-01 -6.37078807e-02
5.48920751e-01 5.09629190e-01 5.72173536e-01 -3.83645982e-01
9.59604323e-01 1.10182077e-01 2.45214105e-01 -8.54638577e-01
-5.96100271e-01 -9.80395749e-02 -2.86226660e-01 -2.81144023e-01
3.86096627e-01 -8.94591033e-01 -1.30114388e+00 2.91990638e-01
-9.42237437e-01 -7.44453013e-01 -5.80797315e-01 7.44375169e-01
-1.33462298e+00 -4.10982132e-01 -7.83447623e-01 -1.43268192e+00
-2.02099502e-01 -8.63895953e-01 3.98681700e-01 2.24349692e-01
3.57504606e-01 -9.77092862e-01 3.36818933e-01 -5.79097331e-01
3.91799003e-01 2.43839368e-01 4.43647385e-01 -3.15380037e-01
-6.22652471e-01 -2.57706910e-01 3.00589353e-01 5.59553742e-01
1.21010728e-01 2.24821106e-01 -5.07448137e-01 -8.66015673e-01
3.93593341e-01 -2.16775060e-01 2.59967536e-01 8.87113690e-01
3.86848807e-01 -9.21468377e-01 -4.90194201e-01 3.64662021e-01
1.42205799e+00 7.73054481e-01 -3.42947692e-01 -6.30857656e-03
5.75959027e-01 4.68015075e-01 3.61762941e-01 3.63784850e-01
-3.10544699e-01 1.85519516e-01 5.59782684e-01 1.71675816e-01
7.09158778e-01 -2.47669190e-01 9.11487520e-01 9.73570228e-01
3.54856253e-02 -1.35923728e-01 -5.56813002e-01 6.06901169e-01
-2.27305174e+00 -7.25306392e-01 4.08014357e-01 2.10923743e+00
5.60779870e-01 -2.48227015e-01 1.13110989e-01 -1.64426029e-01
1.23061991e+00 -3.00652385e-01 -1.25941384e+00 -4.73479986e-01
-5.59525900e-02 -5.52791715e-01 1.14022124e+00 8.55374038e-01
-9.05721605e-01 9.84580457e-01 7.69903517e+00 2.70438612e-01
-1.32359624e+00 -4.79546577e-01 3.16184103e-01 7.22981691e-02
4.79617059e-01 -1.74326792e-01 -1.23143983e+00 2.42897309e-02
1.32663119e+00 -1.02943408e+00 1.11891258e+00 1.13355649e+00
1.02519131e+00 4.77821618e-01 -7.48333216e-01 2.98645020e-01
-3.72686833e-01 -1.18275225e+00 -3.47592384e-01 2.06676349e-01
1.29010487e+00 -1.67288840e-01 5.73587477e-01 2.56769747e-01
7.57450044e-01 -4.68484193e-01 5.69933474e-01 5.47260046e-01
4.00863677e-01 -5.72015345e-01 7.94291124e-02 6.42710924e-01
-9.72598016e-01 -8.85954678e-01 -4.67797846e-01 -1.19441234e-01
3.53377342e-01 4.24999222e-02 -1.00656700e+00 -1.66456223e-01
-2.17400163e-01 9.57649350e-01 2.42550209e-01 9.18601573e-01
-3.83530229e-01 6.48137689e-01 -4.69132304e-01 -4.50658619e-01
4.81130093e-01 -6.21179223e-01 1.20217836e+00 6.82042837e-01
4.66245323e-01 4.29659724e-01 5.47166765e-01 1.03456247e+00
3.12115923e-02 -1.35990679e-01 -1.21523452e+00 -4.69008654e-01
2.98578113e-01 1.11683822e+00 -3.73832971e-01 -3.67052346e-01
2.56624073e-01 4.03444231e-01 3.01187485e-01 8.37158442e-01
-7.57143259e-01 -3.85873914e-01 4.94383991e-01 -4.90362376e-01
2.95665890e-01 -4.47084010e-01 -1.50953839e-03 -9.89132047e-01
-2.17945561e-01 -8.57823968e-01 3.11798565e-02 -7.58892477e-01
-8.39193344e-01 4.74469781e-01 1.12168312e-01 -1.50694478e+00
-1.15072966e+00 -6.98182166e-01 -5.04159153e-01 8.04928839e-01
-9.29043353e-01 -2.24667624e-01 4.87883180e-01 6.39053345e-01
3.07872832e-01 -5.91209233e-01 5.57463765e-01 -2.48175845e-01
-1.19792938e+00 3.22670490e-02 6.83694959e-01 -4.00614053e-01
3.18337798e-01 -1.37950730e+00 -1.07785754e-01 1.00651002e+00
-6.46181941e-01 8.15834165e-01 1.00369513e+00 -6.50534451e-01
-1.46856236e+00 -1.40755153e+00 1.54311851e-01 3.22963983e-01
1.21975565e+00 -1.45724900e-02 -6.82853639e-01 1.20422876e+00
2.67137170e-01 -4.61166762e-02 -3.66341710e-01 -6.02458656e-01
4.35434759e-01 1.39480948e-01 -1.06295466e+00 1.08901107e+00
6.42718613e-01 -4.52159137e-01 -1.99877948e-01 5.42500675e-01
1.12218654e+00 -6.45367086e-01 -7.05340922e-01 5.12120903e-01
4.09996748e-01 4.76684719e-01 7.30362356e-01 -1.03708851e+00
-1.56065807e-01 -4.83549654e-01 1.29045591e-01 -1.96411467e+00
-5.47225237e-01 -1.49277008e+00 -6.29291415e-01 3.63388270e-01
7.00873315e-01 -9.29253340e-01 7.91003466e-01 5.29819429e-01
-9.00875553e-02 -6.20647490e-01 -5.32960713e-01 -1.24917662e+00
1.92189604e-01 5.16656399e-01 -2.24605218e-01 6.72046542e-01
3.88394326e-01 4.30132687e-01 -7.65828609e-01 7.67237604e-01
3.84260714e-01 -2.55552709e-01 2.67709017e-01 -6.55010760e-01
-3.88127655e-01 -3.32925856e-01 3.44340056e-01 -1.12475502e+00
8.43736291e-01 -4.96575117e-01 6.82869375e-01 -8.79052043e-01
-3.88630897e-01 1.29488096e-01 -3.38261157e-01 4.48800236e-01
2.04330370e-01 -4.55529749e-01 3.15077901e-01 2.16296777e-01
-4.75091040e-02 7.14109898e-01 1.26852548e+00 -1.96172625e-01
-8.45359087e-01 6.70617521e-01 -2.16096088e-01 7.26703286e-01
1.12722635e+00 -2.32192546e-01 -1.06156301e+00 -1.00153238e-01
-1.27394706e-01 8.81170213e-01 7.01889470e-02 -7.92390585e-01
3.71734381e-01 -6.16843045e-01 -4.03919905e-01 -4.38929051e-01
3.99815798e-01 -1.06556547e+00 2.13682085e-01 1.06666231e+00
-8.72536838e-01 3.25146437e-01 1.19386390e-01 8.59773576e-01
-1.39529467e-01 -2.22062081e-01 1.08736312e+00 2.22575158e-01
-1.09256022e-01 3.16650659e-01 -1.04465663e+00 -2.58180290e-01
9.49597239e-01 4.17702854e-01 -1.66779310e-01 -7.85933554e-01
-1.25716031e+00 5.02599776e-01 -1.85795650e-01 2.14521319e-01
3.74709725e-01 -1.07635212e+00 -2.31263444e-01 5.91570772e-02
-6.38717592e-01 -6.92690909e-01 -5.02420723e-01 5.54077446e-01
6.13686554e-02 9.33338404e-01 -2.33977884e-01 -2.45619208e-01
-1.10912883e+00 7.89694726e-01 9.75838423e-01 -1.88749015e-01
-3.87011886e-01 1.58505127e-01 6.82403520e-02 -7.12884426e-01
4.24761415e-01 -8.22144926e-01 -2.16673955e-01 -3.34942579e-01
8.86227936e-02 5.82179010e-01 -3.87427330e-01 -1.63959250e-01
2.16370225e-01 3.24990720e-01 3.83485258e-01 -7.27061689e-01
1.09903562e+00 -2.38138229e-01 3.01385894e-02 6.50662482e-01
1.02450180e+00 -6.54305637e-01 -1.73558187e+00 -2.88684100e-01
3.86899933e-02 2.97542691e-01 1.33723244e-01 -5.12497604e-01
-1.11858404e+00 2.39414662e-01 7.66850352e-01 3.87175620e-01
8.54179263e-01 -9.86350596e-01 1.64144158e-01 1.44391930e+00
1.10944778e-01 -1.31487107e+00 -1.59740955e-01 1.11529255e+00
1.17324555e+00 -7.48119056e-01 -1.26074135e-01 -2.27579802e-01
-5.94738305e-01 1.17091048e+00 5.30907810e-01 -1.00141203e+00
1.05382848e+00 4.64859426e-01 -1.83849081e-01 3.64373088e-01
-1.36415017e+00 5.83867878e-02 1.39854655e-01 1.92897052e-01
-1.11184299e-01 1.18820459e-01 -5.42120874e-01 -9.65234786e-02
3.43883872e-01 1.13823891e-01 1.07111371e+00 9.01480913e-01
-7.21989453e-01 -5.12487352e-01 -3.41359168e-01 1.41259968e-01
-3.76680940e-01 2.71576464e-01 -3.07577550e-01 7.68385828e-01
-9.09378707e-01 7.78304935e-01 -1.50780812e-01 -9.11166742e-02
6.35075331e-01 -9.96648371e-02 2.37999987e-02 -6.02858722e-01
-3.45567763e-01 3.49399745e-01 -2.89232377e-02 -5.01378357e-01
4.01206911e-02 -3.69870961e-01 -1.12773383e+00 2.23821551e-01
-9.36951399e-01 1.44135207e-01 6.13504171e-01 5.01896679e-01
3.83278728e-01 4.72208411e-01 1.15853691e+00 -1.01293695e+00
-1.61366129e+00 -7.73036122e-01 -7.36014545e-01 -5.18061042e-01
7.13479936e-01 -7.27657318e-01 -7.84634292e-01 2.02120796e-01] | [4.904115676879883, 2.4131534099578857] |
31a4972d-0a0a-4359-8342-913ddbe3d23f | self-supervised-scene-flow-estimation-with-4d | 2203.01137 | null | https://arxiv.org/abs/2203.01137v4 | https://arxiv.org/pdf/2203.01137v4.pdf | Self-Supervised Scene Flow Estimation with 4-D Automotive Radar | Scene flow allows autonomous vehicles to reason about the arbitrary motion of multiple independent objects which is the key to long-term mobile autonomy. While estimating the scene flow from LiDAR has progressed recently, it remains largely unknown how to estimate the scene flow from a 4-D radar - an increasingly popular automotive sensor for its robustness against adverse weather and lighting conditions. Compared with the LiDAR point clouds, radar data are drastically sparser, noisier and in much lower resolution. Annotated datasets for radar scene flow are also in absence and costly to acquire in the real world. These factors jointly pose the radar scene flow estimation as a challenging problem. This work aims to address the above challenges and estimate scene flow from 4-D radar point clouds by leveraging self-supervised learning. A robust scene flow estimation architecture and three novel losses are bespoken designed to cope with intractable radar data. Real-world experimental results validate that our method is able to robustly estimate the radar scene flow in the wild and effectively supports the downstream task of motion segmentation. | ['Chris Xiaoxuan Lu', 'Jianning Deng', 'Yimin Deng', 'Zhijun Pan', 'Fangqiang Ding'] | 2022-03-02 | null | null | null | null | ['motion-segmentation', 'scene-flow-estimation'] | ['computer-vision', 'computer-vision'] | [ 2.49133587e-01 -4.69429463e-01 -3.66856754e-01 -4.61655915e-01
-4.86860722e-01 -6.75785065e-01 5.97901762e-01 -3.40508461e-01
-5.55239260e-01 7.44641304e-01 -4.20520812e-01 -5.59297800e-01
-1.35967717e-01 -8.45764160e-01 -3.42319936e-01 -6.10287368e-01
-2.17906803e-01 7.26398170e-01 4.31499541e-01 -9.18680131e-02
2.63996154e-01 1.01097763e+00 -1.71884024e+00 -4.27326024e-01
9.67507362e-01 1.02909064e+00 4.50245053e-01 1.06304276e+00
-2.75070369e-01 7.90955842e-01 -1.74701616e-01 1.08656697e-01
5.88230073e-01 -1.20285936e-02 -2.34560758e-01 1.81454182e-01
1.01574886e+00 -6.47211492e-01 -5.16425550e-01 8.68209541e-01
6.49125800e-02 -3.87298595e-03 5.89989603e-01 -1.44340146e+00
2.82357544e-01 -2.61486918e-01 -6.41770124e-01 4.75164860e-01
5.29715652e-03 3.34269315e-01 6.27205491e-01 -6.71737254e-01
6.18202090e-01 1.09107614e+00 5.52453578e-01 3.45234394e-01
-8.59553576e-01 -7.02913702e-01 4.83062454e-02 3.62616748e-01
-1.27340066e+00 -6.68444693e-01 8.35870862e-01 -5.10196984e-01
3.30282032e-01 2.16817677e-01 7.40178943e-01 6.62210047e-01
3.29650223e-01 5.97645700e-01 9.90117669e-01 9.54895914e-02
3.67128372e-01 1.14121422e-01 2.12560575e-02 7.38683820e-01
6.28756881e-01 2.42787093e-01 -5.55566430e-01 3.27153265e-01
7.00828493e-01 6.11215979e-02 -1.11723430e-01 -7.88679540e-01
-1.21774185e+00 7.74416387e-01 3.06037486e-01 -8.44213590e-02
-2.03083843e-01 3.20820034e-01 1.43913969e-01 2.81980306e-01
3.71253759e-01 -3.04080863e-02 -4.02668446e-01 -2.42871940e-01
-1.27642500e+00 5.05548477e-01 8.15477073e-01 1.03077447e+00
1.12123191e+00 4.71662790e-01 5.44850647e-01 3.73608582e-02
4.47263241e-01 1.32970285e+00 -1.73357561e-01 -1.38449454e+00
6.72131181e-01 5.13684869e-01 2.76268959e-01 -9.68727231e-01
-4.35603827e-01 -3.67946297e-01 -8.89602065e-01 6.43444359e-01
7.50496507e-01 -2.00589761e-01 -8.29197943e-01 1.30168211e+00
6.18211329e-01 5.45456886e-01 2.34756842e-01 1.19103253e+00
6.33305669e-01 5.81915498e-01 -1.24995008e-01 -3.24621350e-01
9.69122946e-01 -3.68256778e-01 -7.01328933e-01 -7.89928675e-01
4.58582073e-01 -4.80602920e-01 4.67490882e-01 2.57891119e-01
-5.87729573e-01 -6.06408179e-01 -1.18617582e+00 1.28692374e-01
-3.05876762e-01 5.60954809e-02 9.78528857e-01 7.73023486e-01
-7.04287589e-01 1.55848544e-02 -8.88420522e-01 -1.96765929e-01
6.71089768e-01 1.91406950e-01 -4.25262928e-01 -3.46706808e-01
-8.24881434e-01 1.00846565e+00 9.97573957e-02 4.63970184e-01
-7.20770419e-01 -1.04407477e+00 -1.19181705e+00 -4.15923148e-01
4.38332200e-01 -6.21007979e-01 9.04643595e-01 -3.93716514e-01
-1.25708830e+00 6.84480071e-01 -3.25563878e-01 -7.03639090e-01
7.39217460e-01 -3.94969046e-01 -2.55119503e-01 1.32169887e-01
2.18413055e-01 7.25687861e-01 9.49969232e-01 -1.25497139e+00
-9.53031838e-01 -5.07648051e-01 -3.34125698e-01 2.72469044e-01
3.00255805e-01 -5.74725747e-01 -3.13134730e-01 1.13340253e-02
1.78355277e-01 -1.02433515e+00 -4.57377881e-01 3.12132865e-01
-9.71599892e-02 3.50682110e-01 1.58320439e+00 -1.55106872e-01
5.99555492e-01 -1.74142694e+00 -3.25259537e-01 -1.28358707e-01
2.65260100e-01 3.38037699e-01 2.03818977e-01 -1.35462716e-01
3.78128678e-01 -3.37827235e-01 -6.54817283e-01 4.17910963e-02
-4.05571133e-01 3.20087492e-01 -6.10328317e-01 8.47340822e-01
2.85341054e-01 8.62901568e-01 -8.23806763e-01 -6.83887601e-01
8.52750361e-01 4.06366318e-01 -3.01743656e-01 6.87746108e-02
-2.75814921e-01 6.87339664e-01 -7.60750532e-01 7.55230069e-01
1.25920784e+00 1.54775307e-01 -1.21655948e-01 -1.78153962e-01
-5.38026690e-01 -2.36024886e-01 -1.29690444e+00 1.59860849e+00
-4.84322339e-01 1.26398170e+00 4.27638799e-01 -9.81406450e-01
1.08969378e+00 -3.74704540e-01 7.31606901e-01 -9.46330309e-01
1.85906857e-01 1.33341551e-01 -9.61490870e-02 -6.83416665e-01
7.47893274e-01 -3.86887550e-01 -2.81433225e-01 1.72543064e-01
-4.11099970e-01 -8.34584296e-01 5.30537441e-02 2.40507439e-01
1.14690888e+00 4.79451492e-02 2.14196905e-01 -7.13239238e-02
7.67400861e-01 5.13155758e-01 8.28702986e-01 6.11519158e-01
-5.51666319e-01 2.66098946e-01 -9.25591663e-02 -5.17403603e-01
-8.02135706e-01 -1.18399644e+00 -1.55647904e-01 2.71149635e-01
7.18429446e-01 1.31330758e-01 -1.07303411e-01 -6.49299324e-01
5.11906624e-01 4.95049775e-01 -7.16584548e-02 2.09816754e-01
-7.29618788e-01 -4.78433430e-01 2.41720706e-01 2.46597067e-01
6.23502851e-01 -4.52469468e-01 -1.26138568e+00 1.74944028e-01
-1.78379372e-01 -1.96479881e+00 -1.53026674e-02 -3.82262021e-02
-1.05595255e+00 -1.02702689e+00 -2.00185195e-01 -2.34616578e-01
3.43540221e-01 9.58082438e-01 9.72580791e-01 -2.93361932e-01
-6.99616134e-01 6.06416762e-01 4.68153926e-03 -5.81187248e-01
-2.39669651e-01 -2.06663832e-01 1.73421636e-01 2.23832428e-01
4.03114974e-01 -5.01087844e-01 -5.01860499e-01 3.90564591e-01
-6.12620413e-01 -4.95018028e-02 5.52285850e-01 1.66343838e-01
4.47103143e-01 2.46836185e-01 3.13551247e-01 -7.77146697e-01
-1.46616504e-01 -4.27450031e-01 -1.16270447e+00 -3.68253052e-01
-2.97728121e-01 3.83459614e-04 3.51108402e-01 3.92652005e-02
-1.11798012e+00 5.39104581e-01 2.63594776e-01 -5.29721558e-01
-4.00468409e-01 -1.81951560e-02 -2.39318445e-01 -2.63647765e-01
3.01224083e-01 -2.13222243e-02 9.15947855e-02 -6.87822029e-02
6.88105941e-01 5.09884715e-01 9.01432872e-01 -7.48048276e-02
1.43449473e+00 1.30681694e+00 5.23987174e-01 -1.55347872e+00
-8.14628720e-01 -9.48887587e-01 -1.02499497e+00 -7.80148149e-01
9.90842819e-01 -1.21689665e+00 -6.15858018e-01 3.00121844e-01
-1.09052193e+00 -3.08049560e-01 -2.61498094e-01 6.21311605e-01
-6.86745584e-01 4.85045075e-01 1.63378239e-01 -1.22809398e+00
-1.12787329e-01 -9.11861479e-01 1.05665720e+00 3.95418972e-01
7.00365826e-02 -9.32310939e-01 7.26770386e-02 6.64967537e-01
3.76095355e-01 4.00617003e-01 3.13966393e-01 9.40163136e-02
-1.45343482e+00 -1.20335937e-01 -5.15558004e-01 -8.79214052e-03
6.05796427e-02 -1.96123309e-02 -9.54619527e-01 -3.87065969e-02
1.14276394e-01 -2.86500286e-02 1.06439090e+00 6.30054355e-01
4.75791156e-01 1.75787836e-01 -3.78767014e-01 7.90594995e-01
1.54667521e+00 -5.77871799e-02 3.88907075e-01 2.51378477e-01
8.84437978e-01 7.99904227e-01 1.19676054e+00 3.16123754e-01
5.26816010e-01 6.49528801e-01 6.99682534e-01 1.21093422e-01
-2.89461434e-01 -5.15786968e-02 3.91383976e-01 4.85875607e-01
1.75534621e-01 -9.36848000e-02 -9.41545844e-01 5.39687693e-01
-1.82660782e+00 -1.13328636e+00 -5.94645917e-01 2.14349699e+00
1.79761514e-01 3.07130605e-01 -2.66898841e-01 2.08341122e-01
2.96776712e-01 4.05710280e-01 -7.33195245e-01 5.02296016e-02
-1.31196707e-01 -1.62761584e-01 1.18804121e+00 8.12045753e-01
-1.17059493e+00 1.17972112e+00 5.67079401e+00 3.40229630e-01
-1.23734105e+00 1.68950967e-02 -2.34651137e-02 -1.20782843e-02
-1.81178316e-01 3.03867519e-01 -1.24884009e+00 3.75368565e-01
8.89034986e-01 1.03920586e-02 -8.38474110e-02 5.13798654e-01
6.05719864e-01 -6.60830140e-01 -6.50148988e-01 1.09741533e+00
1.11839185e-02 -1.53402793e+00 -1.46971405e-01 2.41968125e-01
4.15118068e-01 3.68089080e-01 -1.28312886e-01 6.16520382e-02
3.49624127e-01 -6.85436964e-01 6.72444582e-01 7.28404880e-01
7.45754123e-01 -6.20983422e-01 4.16782737e-01 7.51498759e-01
-1.46296632e+00 -5.54273687e-02 -1.95079178e-01 -7.39454180e-02
7.03983009e-01 9.91453052e-01 -1.10288703e+00 5.00919938e-01
5.46977580e-01 9.80378509e-01 -4.73734349e-01 1.08408284e+00
6.43474534e-02 3.13537747e-01 -4.98135507e-01 2.49006242e-01
3.09329838e-01 -4.52366084e-01 9.46392477e-01 1.20293832e+00
3.45165938e-01 -6.50215074e-02 3.51073712e-01 7.99483836e-01
2.86590755e-01 -4.16527718e-01 -1.22523522e+00 1.75823152e-01
3.14350009e-01 1.53302312e+00 -7.41629004e-01 4.17510010e-02
-2.55024761e-01 4.70098227e-01 -7.92292804e-02 4.02328134e-01
-8.10644269e-01 -1.53427169e-01 1.00938046e+00 4.09761548e-01
2.65683621e-01 -1.09565461e+00 -3.02663505e-01 -9.99817967e-01
-1.20142326e-01 -8.38928595e-02 -3.67155895e-02 -5.66861093e-01
-8.79678726e-01 1.45551294e-01 -3.36458758e-02 -1.71361852e+00
-2.34127343e-01 -6.62641406e-01 -4.61792827e-01 5.75649321e-01
-2.34721851e+00 -1.16701376e+00 -7.70605981e-01 5.19635439e-01
7.46407449e-01 -2.19594941e-01 8.31386149e-02 2.55202442e-01
-3.65950525e-01 -2.98104495e-01 -2.69920737e-01 -1.17529660e-01
5.46622694e-01 -1.00060868e+00 3.24470252e-01 1.13291776e+00
1.95565552e-01 -1.86476201e-01 8.98258090e-01 -7.99148500e-01
-2.07087803e+00 -1.36179757e+00 6.47893071e-01 -6.44641876e-01
6.60903037e-01 -4.47408974e-01 -7.38919914e-01 3.80955040e-01
-2.91646928e-01 4.38300282e-01 2.11309090e-01 -5.07903039e-01
-8.57067108e-03 -6.34425223e-01 -8.72719407e-01 3.27324599e-01
9.45698440e-01 -3.34642410e-01 -2.69858986e-01 -9.92543902e-03
4.48105752e-01 -2.92328000e-01 -3.50268513e-01 6.97610259e-01
3.79926085e-01 -1.03692758e+00 1.13975000e+00 -1.71469942e-01
-1.79128349e-01 -7.14855194e-01 -2.49979347e-01 -8.06312144e-01
2.17789799e-01 -6.28435969e-01 -4.14302617e-01 9.49254692e-01
1.70053899e-01 -4.78897840e-01 1.33596778e+00 3.32195729e-01
7.37286806e-02 7.85151273e-02 -1.14496911e+00 -7.98281312e-01
-3.58527392e-01 -9.84133363e-01 7.26687349e-03 7.82305956e-01
-7.42191732e-01 5.37731051e-01 -3.47307652e-01 4.61868584e-01
1.38610518e+00 4.08001214e-01 1.33408213e+00 -1.72184396e+00
3.90572250e-01 -2.36272991e-01 -7.97204554e-01 -1.39983737e+00
5.86322367e-01 -7.88859010e-01 3.98965865e-01 -1.38222897e+00
-2.82522172e-01 -9.41159785e-01 4.95956928e-01 -1.46406114e-01
1.18814461e-01 2.05423266e-01 2.53273934e-01 2.69587666e-01
-6.03750706e-01 5.45197904e-01 1.12707412e+00 -2.47585222e-01
-3.52470994e-01 3.26655060e-01 -2.25388452e-01 7.94184268e-01
6.60472512e-01 -3.29737723e-01 -5.23475051e-01 -4.72713798e-01
1.01736017e-01 2.18009636e-01 5.06307840e-01 -1.25710618e+00
7.76485741e-01 -4.34248328e-01 3.08099419e-01 -1.34092712e+00
6.13197207e-01 -1.06695473e+00 -1.10304169e-01 3.61866742e-01
3.63979936e-01 -1.55790359e-01 3.28889877e-01 9.07511055e-01
-1.49043456e-01 8.73960927e-02 9.29586530e-01 -5.19531555e-02
-1.30936432e+00 6.69274747e-01 -4.88143295e-01 2.17623457e-01
1.22727990e+00 -5.80034196e-01 -1.80404812e-01 -4.95920986e-01
-1.78726897e-01 4.25698757e-01 2.05253378e-01 5.32328248e-01
8.77068162e-01 -1.00129902e+00 -8.19086611e-01 4.70126748e-01
7.93024972e-02 2.78428704e-01 2.76976496e-01 7.83209503e-01
-7.36345828e-01 6.85913384e-01 -1.49260432e-01 -1.08145726e+00
-1.14752030e+00 1.05288789e-01 3.00491840e-01 3.61921042e-02
-8.76048207e-01 4.47310448e-01 5.15733026e-02 -4.68294412e-01
-1.51277319e-01 -2.08488777e-01 -1.96202740e-01 1.98015302e-01
4.63301659e-01 4.16943073e-01 -2.52058934e-02 -9.25677419e-01
-4.17118728e-01 1.00762856e+00 1.69306114e-01 -1.02023646e-01
1.15104771e+00 -5.15472174e-01 2.46951357e-01 5.26740491e-01
9.71509635e-01 -2.35174969e-02 -1.65988410e+00 -1.84460431e-01
-1.64718758e-02 -6.33829355e-01 5.34095168e-01 -7.06741065e-02
-1.21611571e+00 1.02802634e+00 4.61964399e-01 2.20863316e-02
7.39401460e-01 -1.46489412e-01 9.12178040e-01 4.66458768e-01
4.74460125e-01 -8.67763519e-01 -2.98685759e-01 7.26951897e-01
2.09994793e-01 -1.47385681e+00 3.43140721e-01 -6.61660194e-01
-4.71601486e-01 1.07696366e+00 4.42215562e-01 -5.03045581e-02
6.39139295e-01 6.33313596e-01 2.91428536e-01 -1.52263775e-01
-5.42026818e-01 -6.63246274e-01 -4.64132577e-02 8.02427828e-01
-2.97443360e-01 -1.23838656e-01 4.17964786e-01 -2.57829309e-01
-2.30713814e-01 -6.92462549e-02 6.51037097e-01 9.44406807e-01
-7.66208947e-01 -7.07462192e-01 -4.41102684e-01 3.44123423e-01
2.68421948e-01 5.15781999e-01 -7.97452405e-02 9.52455282e-01
2.07925096e-01 1.01057768e+00 3.80940288e-01 -5.54958731e-02
4.17705208e-01 -3.83407533e-01 5.10325849e-01 -1.98452681e-01
2.00603276e-01 -2.83161610e-01 -5.50389364e-02 -7.70065248e-01
-7.00909674e-01 -9.35415268e-01 -1.40696418e+00 -2.62042880e-01
-9.11525562e-02 -1.15889654e-01 9.86800075e-01 1.01948726e+00
1.58679590e-01 2.10239321e-01 8.59155357e-01 -1.09943819e+00
-5.16238287e-02 -2.33775467e-01 -5.76992810e-01 -1.00976899e-01
9.57330108e-01 -7.88479567e-01 -6.56357110e-01 2.16641769e-01] | [8.231975555419922, -1.9903998374938965] |
9de2eee8-0471-43d2-8b84-0588b873669e | eliminating-background-bias-for-robust-person | null | null | http://openaccess.thecvf.com/content_cvpr_2018/html/Tian_Eliminating_Background-Bias_for_CVPR_2018_paper.html | http://openaccess.thecvf.com/content_cvpr_2018/papers/Tian_Eliminating_Background-Bias_for_CVPR_2018_paper.pdf | Eliminating Background-Bias for Robust Person Re-Identification | Person re-identification is an important topic in intelligent surveillance and computer vision. It aims to accurately measure visual similarities between person images for determining whether two images correspond to the same person. State-of-the-art methods mainly utilize deep learning based approaches for learning visual features for describing person appearances. However, we observe that existing deep learning models are biased to capture too much relevance between background appearances of person images. We design a series of experiments with newly created datasets to validate the influence of background information. To solve the background bias problem, we propose a person-region guided pooling deep neural network based on human parsing maps to learn more discriminative person-part features, and propose to augment training data with person images with random background. Extensive experiments demonstrate the robustness and effectiveness of our proposed method. | ['Junjie Yan', 'Xuesen Zhang', 'Shihua Li', 'Hongsheng Li', 'Xiaogang Wang', 'Shuai Yi', 'Maoqing Tian', 'Jianping Shi'] | 2018-06-01 | null | null | null | cvpr-2018-6 | ['human-parsing'] | ['computer-vision'] | [ 7.03354627e-02 -3.95807803e-01 6.03571460e-02 -5.82625985e-01
-7.80992433e-02 -3.89825344e-01 8.14317763e-01 -1.01650260e-01
-6.81185126e-01 5.30168116e-01 1.94114313e-01 9.56573263e-02
3.90272915e-01 -8.39621007e-01 -7.97655165e-01 -6.33608222e-01
5.85821643e-03 2.03034490e-01 2.49860674e-01 1.34083554e-01
-1.59185398e-02 5.05806386e-01 -1.31836450e+00 3.01690608e-01
3.74652922e-01 6.53522134e-01 -1.87787265e-01 6.14960611e-01
2.79926565e-02 7.23789036e-01 -8.44123900e-01 -8.11078191e-01
6.60850167e-01 -3.98470730e-01 -5.16702771e-01 5.94558597e-01
1.07960010e+00 -8.06381702e-01 -8.71087611e-01 1.35072184e+00
4.47165936e-01 1.63895726e-01 6.20644867e-01 -1.50704920e+00
-8.19002509e-01 -7.86650851e-02 -8.96722138e-01 7.58798182e-01
3.10681641e-01 3.35512400e-01 2.65295655e-01 -5.17822325e-01
2.66467422e-01 1.55197263e+00 9.42940593e-01 9.06391799e-01
-1.01687396e+00 -6.79029107e-01 5.42890668e-01 3.38415533e-01
-1.46261013e+00 -4.34163630e-01 8.37032914e-01 -5.59467971e-01
5.37776232e-01 1.18446656e-01 6.81400716e-01 1.32451975e+00
-1.69057492e-02 7.79707134e-01 1.07955635e+00 -4.38870698e-01
-1.57954097e-01 4.32199478e-01 5.82815409e-01 9.74502683e-01
9.35017645e-01 1.44538790e-01 -1.49126992e-01 -1.83916196e-01
9.31853235e-01 5.55379450e-01 -2.94988602e-01 -4.09119934e-01
-8.98321509e-01 6.49875760e-01 5.63038409e-01 1.85543135e-01
-3.08780074e-01 1.49918482e-01 2.39980027e-01 -1.26004601e-02
3.23340714e-01 -2.24384457e-01 -1.18540347e-01 4.32503253e-01
-6.88274562e-01 4.56443638e-01 4.29047614e-01 8.48126054e-01
7.72853017e-01 -2.58426279e-01 -7.49013841e-01 7.85828769e-01
2.45270416e-01 7.53353119e-01 4.02350396e-01 -7.26461232e-01
3.55434150e-01 7.48379469e-01 4.04006898e-01 -1.19503522e+00
-3.99027914e-01 -4.50644940e-01 -1.05983150e+00 1.75107241e-01
7.99345434e-01 -2.07094818e-01 -1.09704661e+00 1.75207043e+00
3.90738934e-01 2.51630604e-01 8.33512936e-03 9.79391992e-01
9.99520719e-01 4.51117367e-01 2.61967242e-01 1.30089343e-01
1.51236093e+00 -1.14381325e+00 -4.64904040e-01 -5.68790674e-01
5.68397194e-02 -2.70192444e-01 7.00228095e-01 -1.18230022e-02
-8.62479568e-01 -1.09986210e+00 -6.80044115e-01 1.87443942e-01
-4.37985718e-01 2.96600163e-01 5.09645045e-01 1.20514512e+00
-8.95647347e-01 3.13405454e-01 -5.77531695e-01 -8.16069603e-01
5.75675130e-01 2.03910634e-01 -5.00535011e-01 -2.26775959e-01
-9.45141912e-01 6.95325792e-01 2.03132257e-01 1.89840406e-01
-9.55670297e-01 -2.90049732e-01 -9.07944381e-01 -2.38548908e-02
-6.43535890e-03 -1.11038458e+00 9.19224918e-01 -1.39581096e+00
-1.04992449e+00 1.41765714e+00 -5.06816626e-01 -4.79985207e-01
6.69245541e-01 -1.56095013e-01 -5.33282578e-01 1.85928121e-01
1.89219743e-01 6.62461460e-01 9.53184307e-01 -1.42280257e+00
-9.41559196e-01 -6.29156053e-01 5.87291941e-02 -5.33968396e-02
-4.38206404e-01 3.74784857e-01 -8.53914082e-01 -6.19948924e-01
-2.69411892e-01 -7.61461735e-01 -2.46624395e-01 1.38964564e-01
-2.53602773e-01 -2.45276123e-01 5.80886483e-01 -1.04919469e+00
6.98813975e-01 -1.91461825e+00 -2.91766882e-01 1.85661077e-01
2.51666039e-01 4.32296664e-01 -2.44963586e-01 -1.70484975e-01
1.57522380e-01 -5.93201667e-02 1.67637363e-01 -4.42674160e-01
-1.43930778e-01 -1.12758994e-01 1.62628405e-02 7.36166358e-01
1.74168855e-01 9.49051559e-01 -6.94203913e-01 -5.68396509e-01
2.81311780e-01 4.87939954e-01 -1.14269018e-01 4.89321798e-01
5.09798765e-01 4.37049061e-01 -2.01772600e-01 6.62785709e-01
8.85255635e-01 -1.46661624e-01 -2.16654524e-01 -2.96678424e-01
2.38890842e-01 -3.28962445e-01 -8.74608934e-01 1.21170390e+00
9.04333442e-02 7.42060483e-01 -1.34515241e-02 -8.84094715e-01
7.98501134e-01 -1.44567722e-02 2.38130942e-01 -7.61184633e-01
1.88796222e-01 -4.81994689e-01 -1.06949158e-01 -5.93560457e-01
2.78031826e-01 1.05455834e-02 1.74097404e-01 2.72045881e-02
-6.39339909e-02 6.34155631e-01 1.79589421e-01 -3.81523669e-02
9.03895795e-01 -1.23072058e-01 1.76925540e-01 -2.00718164e-01
8.15155208e-01 -2.82735467e-01 7.55250514e-01 1.21276093e+00
-9.56707120e-01 5.97529829e-01 -6.19879365e-03 -1.07642639e+00
-1.06782234e+00 -1.17885816e+00 9.89705324e-02 9.95905697e-01
5.88750422e-01 -1.40506658e-03 -9.88272548e-01 -8.50481510e-01
-1.76966153e-02 3.28798294e-01 -9.32181060e-01 -1.62254963e-02
-7.26257980e-01 -1.15882254e+00 5.89177370e-01 7.50585079e-01
9.37539220e-01 -8.89230072e-01 -5.89399755e-01 -1.46053463e-01
-3.52442950e-01 -1.28249192e+00 -4.55674022e-01 -4.26570475e-01
-4.07315940e-01 -1.31427813e+00 -1.26415205e+00 -1.00242245e+00
9.97514069e-01 7.50314415e-01 1.09397995e+00 2.07646817e-01
-5.78048050e-01 7.31650412e-01 -5.36437659e-03 -3.29239428e-01
-2.12052315e-01 -4.01840597e-01 2.08766818e-01 3.51347417e-01
8.67544413e-01 3.94975177e-05 -9.79615271e-01 3.31243902e-01
-5.49196064e-01 3.51207666e-02 4.36932147e-01 6.02178574e-01
2.18042508e-01 3.69978487e-01 1.24970645e-01 -5.14468670e-01
4.78187621e-01 -8.80435109e-02 -4.35729921e-01 6.46214247e-01
9.25647169e-02 -3.05018097e-01 3.82340282e-01 -3.66748422e-01
-1.19203496e+00 -1.35778859e-01 1.87883705e-01 -3.44349325e-01
-6.78286254e-01 -3.85525614e-01 -3.65928441e-01 -1.51715785e-01
3.47049505e-01 3.96106273e-01 -2.74862260e-01 -2.24464461e-01
1.87842265e-01 6.51968360e-01 8.16353738e-01 -4.23769832e-01
8.63004327e-01 9.56178010e-01 -2.47411832e-01 -7.48338699e-01
-7.75885165e-01 -7.03031659e-01 -7.26498961e-01 -4.24511403e-01
1.10797417e+00 -1.22602308e+00 -6.46314442e-01 7.92161524e-01
-1.30686319e+00 -3.01483691e-01 2.51778275e-01 2.07669318e-01
-1.18933991e-01 7.67529607e-01 -6.30082428e-01 -9.93471980e-01
-3.91662627e-01 -8.00969958e-01 1.11580753e+00 6.70981109e-01
1.31438360e-01 -8.77997160e-01 5.03055975e-02 4.66077715e-01
1.93609551e-01 2.85832852e-01 4.49227422e-01 -4.44694102e-01
-4.49152827e-01 -5.79044342e-01 -6.84262455e-01 2.52348006e-01
4.26229060e-01 -3.17851245e-01 -1.09701979e+00 -6.35876596e-01
-2.05783531e-01 7.19570741e-02 1.22297239e+00 4.58123207e-01
1.15417957e+00 -2.98266053e-01 -7.82415628e-01 6.71088874e-01
1.23671138e+00 1.12291299e-01 6.29464924e-01 5.90339243e-01
8.78996849e-01 8.60933602e-01 2.32351929e-01 3.03674519e-01
4.44589078e-01 6.24823749e-01 1.40660971e-01 -4.89635497e-01
-3.32834601e-01 -1.36688694e-01 3.06658387e-01 -2.33814448e-01
-2.12420687e-01 -2.64983982e-01 -7.98283935e-01 6.22071028e-01
-1.88212287e+00 -1.25988221e+00 -2.25162320e-02 2.37402415e+00
3.68463844e-01 1.26538292e-01 4.80989784e-01 -2.92166680e-01
1.31114113e+00 -1.14639163e-01 -2.59440988e-01 2.99634188e-01
-2.65802264e-01 -3.44870090e-01 6.26064360e-01 2.21028298e-01
-1.69275892e+00 9.96031940e-01 6.18203545e+00 4.33935553e-01
-8.02813232e-01 6.02630228e-02 9.07426059e-01 5.13392612e-02
2.01078102e-01 -5.42622030e-01 -1.12688518e+00 6.91228330e-01
3.61502767e-01 1.16517574e-01 1.89761803e-01 7.26865530e-01
9.34879407e-02 9.75031927e-02 -1.05352986e+00 1.39181638e+00
4.76765603e-01 -9.38571632e-01 1.77307785e-01 -1.45877257e-01
7.21892893e-01 -4.00017411e-01 1.19011067e-01 3.00395489e-01
2.96563655e-01 -1.03257084e+00 6.13111436e-01 7.84457147e-01
1.91298634e-01 -7.24183142e-01 9.30736840e-01 6.80508614e-02
-1.20203495e+00 -2.17833638e-01 -7.51455247e-01 -2.01627865e-01
8.52451771e-02 1.33751199e-01 -6.45941556e-01 1.72825009e-01
1.18452621e+00 4.62449402e-01 -1.16338313e+00 1.30384457e+00
2.53736787e-02 2.81284302e-01 -7.86800012e-02 1.43398702e-01
5.24020456e-02 -3.35621163e-02 3.71128440e-01 1.49635756e+00
3.95868011e-02 -9.34697762e-02 4.25863326e-01 1.05404198e+00
8.37069601e-02 -2.69934714e-01 -6.26761377e-01 3.44307572e-01
2.93039586e-02 1.19412744e+00 -8.55293036e-01 -6.50962472e-01
-7.76997626e-01 1.55441189e+00 2.93700755e-01 6.43379569e-01
-9.51400161e-01 -9.24704298e-02 9.00893331e-01 2.00761780e-01
4.42209899e-01 -1.65501997e-01 8.56762081e-02 -1.26237273e+00
3.90913710e-02 -6.41640246e-01 4.53886837e-01 -6.18596315e-01
-1.85015452e+00 5.93428075e-01 3.69845852e-02 -9.16217089e-01
-4.02639695e-02 -9.21513736e-01 -8.61331165e-01 8.33374023e-01
-1.38818252e+00 -1.49225211e+00 -9.29856777e-01 8.42852831e-01
4.83019143e-01 -5.33717453e-01 5.28037429e-01 2.76665419e-01
-9.53965843e-01 8.18974257e-01 -3.11417487e-02 8.20970058e-01
7.62591183e-01 -1.09768212e+00 7.93789923e-01 1.29264116e+00
-4.89833914e-02 8.76110017e-01 6.80515170e-01 -7.32112229e-01
-9.37262297e-01 -1.41267157e+00 5.07835269e-01 -7.00621307e-01
4.41583479e-03 -3.73914033e-01 -7.18791246e-01 5.88627875e-01
1.50901064e-01 1.69432342e-01 6.99578226e-01 -2.13731099e-02
-4.14548755e-01 -2.79542714e-01 -1.27746427e+00 6.63364351e-01
1.08431792e+00 -3.20812404e-01 -6.43762589e-01 1.25981912e-01
3.51216793e-01 6.65973723e-02 -2.67508417e-01 4.06977922e-01
5.59158206e-01 -1.09988821e+00 1.48358440e+00 -7.23982573e-01
-1.16247579e-01 -4.60738152e-01 3.47782001e-02 -8.50528479e-01
-7.91277766e-01 -1.45219773e-01 9.97516885e-02 1.39643097e+00
-3.58753175e-01 -4.34630930e-01 1.03908765e+00 8.59878421e-01
5.59939861e-01 3.00249662e-02 -5.69254994e-01 -8.34276259e-01
-7.26666162e-03 1.08211659e-01 5.89204311e-01 7.09772170e-01
-5.92731714e-01 1.04878560e-01 -6.33848608e-01 7.03631222e-01
1.09719217e+00 9.40820947e-02 1.23832536e+00 -1.16933167e+00
-2.20659956e-01 -4.44488764e-01 -7.16296732e-01 -8.09932053e-01
2.94074267e-01 -3.41045737e-01 -6.09979108e-02 -1.62794316e+00
9.54260945e-01 1.87163409e-02 -5.83543122e-01 2.96002120e-01
-8.50655496e-01 5.38993597e-01 2.03026310e-01 7.61508942e-02
-8.60521376e-01 3.45891953e-01 7.22676218e-01 -6.65560722e-01
8.62961262e-02 2.60529041e-01 -5.71227670e-01 8.56697023e-01
7.96769023e-01 -5.72864525e-02 5.02353441e-03 -5.39659977e-01
-4.65254366e-01 -5.36034346e-01 1.21917379e+00 -1.30989850e+00
1.16457112e-01 -6.34164289e-02 1.37677741e+00 -4.83050674e-01
2.21424505e-01 -8.98151278e-01 -1.87568173e-01 5.82350671e-01
-1.15381017e-01 6.98362216e-02 3.62746894e-01 7.40759969e-01
1.62168555e-02 -1.75783172e-01 7.46172249e-01 -3.95518005e-01
-1.09394360e+00 5.47092855e-01 -3.62033576e-01 -2.57244676e-01
9.22987461e-01 -4.16600198e-01 -3.75311047e-01 -3.37578565e-01
-3.08345914e-01 9.24259238e-03 6.22042894e-01 5.22197604e-01
5.58570802e-01 -1.22586215e+00 -7.57761598e-01 2.86933184e-01
3.01266015e-01 -4.83846426e-01 3.46759945e-01 2.96791345e-01
-4.58949983e-01 4.42588091e-01 -5.37865162e-01 -5.41639149e-01
-1.67555189e+00 9.00994539e-01 7.07005739e-01 -8.76696110e-02
-5.80610871e-01 9.29686368e-01 8.51316094e-01 -1.83308020e-01
4.85894054e-01 -1.03292309e-01 -1.83200911e-01 -5.42369902e-01
1.03167284e+00 3.43053937e-01 -3.00049871e-01 -8.22716832e-01
-5.89203894e-01 5.49382210e-01 -1.96762189e-01 7.21653402e-02
9.03164148e-01 -2.30404109e-01 5.95103689e-02 -1.74707606e-01
9.47435856e-01 -2.29714036e-01 -1.54154384e+00 -3.33016485e-01
-1.87173754e-01 -7.50146210e-01 -2.13302970e-01 -6.68602049e-01
-1.05525780e+00 9.32184637e-01 1.34177947e+00 -4.59466912e-02
1.02808237e+00 -1.51654989e-01 6.35541379e-01 4.38554138e-01
3.60883713e-01 -8.53645205e-01 2.70320296e-01 7.84157515e-02
5.56976676e-01 -1.76836550e+00 -2.68730558e-02 -3.22208136e-01
-4.45621550e-01 1.08568990e+00 1.03217733e+00 -9.82206240e-02
3.01253319e-01 -1.70381442e-01 2.33470991e-01 7.95529261e-02
1.65642928e-02 -5.77298760e-01 4.42260444e-01 1.18179059e+00
2.16831416e-01 3.40488693e-03 1.63754001e-01 7.71771610e-01
2.11473897e-01 -2.24699736e-01 5.77573776e-02 6.08840764e-01
-4.65987831e-01 -9.67475295e-01 -8.22307050e-01 1.01272397e-01
-4.52359408e-01 6.87253699e-02 -6.47454321e-01 6.84988201e-01
4.76876915e-01 9.81390536e-01 3.41802090e-01 -6.33430779e-02
8.19673836e-02 -1.10868916e-01 8.41445446e-01 -2.52650350e-01
-4.62246537e-01 -2.12655768e-01 -2.79644638e-01 -2.59551764e-01
-6.30844474e-01 -5.17030060e-01 -5.80757678e-01 -2.48942524e-01
1.17446192e-01 -2.49536365e-01 1.32282108e-01 7.92973697e-01
1.43538779e-02 4.10918206e-01 3.01995039e-01 -8.92971337e-01
-2.03429610e-01 -8.46160412e-01 -3.70449424e-01 1.06837797e+00
4.40400213e-01 -5.80140173e-01 3.34776640e-02 3.44805658e-01] | [14.700393676757812, 0.9161237478256226] |
02f676c6-b87d-4a68-b875-04ec6d01f36a | texta3-activation-anomaly-analysis | 2003.01801 | null | https://arxiv.org/abs/2003.01801v3 | https://arxiv.org/pdf/2003.01801v3.pdf | $\text{A}^3$: Activation Anomaly Analysis | Inspired by recent advances in coverage-guided analysis of neural networks, we propose a novel anomaly detection method. We show that the hidden activation values contain information useful to distinguish between normal and anomalous samples. Our approach combines three neural networks in a purely data-driven end-to-end model. Based on the activation values in the target network, the alarm network decides if the given sample is normal. Thanks to the anomaly network, our method even works in strict semi-supervised settings. Strong anomaly detection results are achieved on common data sets surpassing current baseline methods. Our semi-supervised anomaly detection method allows to inspect large amounts of data for anomalies across various applications. | ['Konstantin Böttinger', 'Jan-Philipp Schulze', 'Philip Sperl'] | 2020-03-03 | null | null | null | null | ['supervised-anomaly-detection', 'semi-supervised-anomaly-detection'] | ['computer-vision', 'computer-vision'] | [ 4.44091588e-01 1.10988826e-01 -2.46697769e-01 -6.22071743e-01
-4.94091600e-01 -4.66247022e-01 6.54508591e-01 5.13300896e-01
-2.79583544e-01 3.30717951e-01 -1.41574606e-01 -4.52583522e-01
-7.87885413e-02 -6.29223645e-01 -5.98490298e-01 -6.88276827e-01
-3.65971446e-01 5.33711672e-01 3.56997281e-01 3.49001996e-02
2.97695547e-01 5.51091909e-01 -1.54078698e+00 4.45425510e-01
7.20767260e-01 1.48747480e+00 -7.08283722e-01 6.99734271e-01
-2.28771508e-01 8.02169681e-01 -5.04141271e-01 5.95510788e-02
3.77993375e-01 -3.58401060e-01 -7.04446435e-01 4.13079895e-02
6.37416422e-01 -2.70509183e-01 1.65409930e-02 1.11948168e+00
1.53969809e-01 1.57389387e-01 5.60633957e-01 -1.70482218e+00
-8.26694742e-02 5.96810639e-01 -3.65609497e-01 7.14004576e-01
8.34919140e-02 2.58023977e-01 1.27151728e+00 -8.94302249e-01
2.06167385e-01 7.93269813e-01 7.07234681e-01 6.06666327e-01
-1.39730167e+00 -3.52704287e-01 7.11834729e-01 5.18956594e-02
-8.24349463e-01 -5.91429651e-01 8.01966071e-01 -3.10844600e-01
1.01897740e+00 2.81959087e-01 4.56845075e-01 1.32939792e+00
-1.05675142e-02 1.01280594e+00 5.90473950e-01 -2.79358625e-01
6.00777328e-01 -1.81881264e-01 5.19715130e-01 6.19680166e-01
3.87163848e-01 2.27032155e-01 -4.12847161e-01 -6.22831345e-01
1.85888737e-01 4.90202963e-01 -4.11628038e-02 -4.91654128e-01
-1.04778957e+00 7.01572537e-01 9.33600962e-02 2.23309830e-01
-6.39706314e-01 -6.46742806e-02 8.16660106e-01 7.01674700e-01
7.44719565e-01 5.60619354e-01 -5.99548459e-01 -1.35103390e-01
-8.83167684e-01 1.49719298e-01 7.84703255e-01 4.45599318e-01
4.88952309e-01 4.49520826e-01 -3.00157726e-01 6.96291447e-01
4.27357525e-01 1.86208919e-01 4.97484088e-01 -6.42001271e-01
2.19859213e-01 8.49932373e-01 -1.53024986e-01 -7.34057367e-01
-3.77474189e-01 -5.30658245e-01 -9.06426132e-01 3.80475879e-01
6.37905240e-01 -1.53387427e-01 -9.57980454e-01 1.53298473e+00
2.79084265e-01 4.26112860e-01 8.47206712e-02 4.08023238e-01
1.38010994e-01 2.52450198e-01 -2.26177976e-01 -9.70812440e-02
8.28208268e-01 -7.79109359e-01 -5.32028735e-01 -4.11692709e-01
9.23775375e-01 -1.79685336e-02 9.89050448e-01 8.44173312e-01
-8.43196392e-01 -6.61822483e-02 -9.53574240e-01 6.93212152e-01
-4.77044493e-01 -2.14447752e-01 3.75566244e-01 5.33043981e-01
-9.22431588e-01 7.52288342e-01 -1.09823835e+00 -2.58548647e-01
8.55591059e-01 2.73892701e-01 -1.87689528e-01 -1.92597066e-03
-7.91520298e-01 3.04136217e-01 6.61931694e-01 1.20181307e-01
-1.10091007e+00 -4.38681841e-01 -8.57357144e-01 -4.35261875e-02
5.92326164e-01 -8.00683796e-02 1.37812829e+00 -1.04894364e+00
-1.07101083e+00 7.31255591e-01 -3.67743475e-03 -1.05518794e+00
6.21271014e-01 -3.55415910e-01 -7.71145344e-01 7.94817284e-02
6.05137907e-02 2.47713388e-03 9.80835438e-01 -9.50098276e-01
-8.89896512e-01 -3.76297802e-01 -6.06775522e-01 -3.75414521e-01
-3.19507152e-01 1.81449708e-02 -7.79558420e-02 -6.28484249e-01
2.00369269e-01 -5.61833262e-01 -4.94072407e-01 -3.93035226e-02
-9.83634055e-01 -1.94413185e-01 1.18818188e+00 -1.38067871e-01
1.16782022e+00 -2.24013281e+00 -5.53024173e-01 8.87441754e-01
5.70156336e-01 3.72464448e-01 -7.81461522e-02 5.51030040e-04
-4.90060925e-01 -7.59619288e-03 -5.76119363e-01 -3.82781535e-01
-9.07625929e-02 3.75050753e-01 -6.25883877e-01 6.12467527e-01
5.12570679e-01 5.76681793e-01 -8.84193063e-01 1.17308255e-02
2.58427281e-02 -5.54712303e-02 -5.87650657e-01 4.86817628e-01
-3.21707964e-01 3.21397334e-01 -4.79478151e-01 1.20679986e+00
2.39137366e-01 -9.13579464e-02 -2.33439028e-01 5.13772607e-01
3.59072596e-01 2.17282906e-01 -1.01664197e+00 1.25469720e+00
1.86912809e-03 6.35360062e-01 -6.20635413e-02 -1.49028051e+00
1.02276838e+00 3.03881645e-01 5.11156201e-01 -4.18613374e-01
7.86100850e-02 2.82932729e-01 1.22445188e-01 -2.44982600e-01
-6.05464950e-02 2.26165563e-01 -4.67940904e-02 7.19028890e-01
3.85468565e-02 5.53305268e-01 2.28890330e-01 2.23661646e-01
1.62992752e+00 -5.61354645e-02 1.72301397e-01 -3.10282648e-01
4.96632397e-01 4.71185483e-02 6.95228815e-01 1.18312907e+00
-4.52734798e-01 5.16130924e-01 1.00726664e+00 -8.54536831e-01
-8.19077015e-01 -1.22067320e+00 -1.57477662e-01 1.37444663e+00
-3.66593480e-01 -2.65712291e-01 -5.43761730e-01 -1.34183097e+00
1.56958356e-01 6.27519011e-01 -7.50422895e-01 -5.19255280e-01
-2.71333128e-01 -7.94122338e-01 7.46425211e-01 6.93880856e-01
2.24860758e-01 -1.30960906e+00 -5.49194038e-01 1.48338318e-01
2.42154464e-01 -1.07082975e+00 -1.89191282e-01 6.02953076e-01
-1.09461594e+00 -1.25259018e+00 -5.74531294e-02 -3.33364606e-01
8.14837217e-01 -1.82999492e-01 1.22937357e+00 1.26004651e-01
-2.99117595e-01 3.01991731e-01 -2.14314580e-01 -6.18831873e-01
-5.97333550e-01 -2.75893267e-02 4.87846434e-01 4.51665103e-01
7.01367259e-01 -7.45399475e-01 -3.02605748e-01 3.94784719e-01
-8.79471838e-01 -8.27229023e-01 5.40751874e-01 7.40034401e-01
6.58293903e-01 -4.58169952e-02 8.14279795e-01 -1.30072784e+00
6.34128094e-01 -9.32768345e-01 -6.56898141e-01 -3.66727822e-02
-1.12409198e+00 3.17277551e-01 8.61859977e-01 -4.39998984e-01
-5.42139947e-01 5.53749725e-02 -1.97264493e-01 -6.19459987e-01
-8.24902356e-01 2.35182643e-01 -7.60253370e-02 3.41994047e-01
9.94074643e-01 2.05112621e-01 2.48732924e-01 -5.39467037e-01
-1.06651716e-01 3.35260659e-01 9.05082226e-01 -4.12340581e-01
7.13063300e-01 4.49669838e-01 -9.26045924e-02 -7.05889881e-01
-9.19175565e-01 -6.61660850e-01 -7.30051458e-01 -4.66173477e-02
2.59541541e-01 -6.96799695e-01 -4.66629118e-01 5.65995753e-01
-6.71495914e-01 -2.81141013e-01 -7.36111343e-01 1.83116853e-01
-2.24316955e-01 3.66630942e-01 -3.51374507e-01 -1.04939318e+00
-4.02362198e-01 -7.48212159e-01 8.49026740e-01 -3.16770583e-01
-3.92435938e-01 -1.14123356e+00 2.68339545e-01 -2.65944302e-01
4.58600014e-01 6.02592289e-01 6.17174625e-01 -1.90172303e+00
-1.29145741e-01 -8.04399371e-01 5.13630249e-02 6.60673201e-01
1.18969977e-01 1.94392711e-01 -1.11996937e+00 -2.12020338e-01
-1.96550936e-01 -3.24063748e-01 1.14756131e+00 2.93816119e-01
1.56292009e+00 -6.14166677e-01 -2.92445779e-01 5.76602161e-01
1.07148468e+00 2.32363548e-02 3.09866279e-01 3.47731352e-01
7.76185036e-01 5.03023386e-01 3.80813211e-01 4.63934362e-01
-2.86774784e-01 1.16748095e-01 8.66537631e-01 -7.20271394e-02
7.22825885e-01 -4.66208756e-02 7.17166364e-01 2.70191003e-02
3.07901770e-01 -1.71597987e-01 -1.13275623e+00 8.29144895e-01
-2.04156137e+00 -1.02985418e+00 -2.07638681e-01 2.34007883e+00
4.94235098e-01 7.92726994e-01 6.65798306e-01 4.61723655e-01
5.15563011e-01 2.59987712e-01 -9.69656229e-01 -6.06729031e-01
-2.46876925e-02 -1.29580693e-02 2.54091442e-01 1.57083660e-01
-1.27613270e+00 4.77373511e-01 7.32769156e+00 3.85422438e-01
-8.40808332e-01 -2.79922158e-01 9.04147625e-01 -4.40247655e-01
-1.19521312e-01 -2.40542412e-01 -5.80045700e-01 3.96153897e-01
1.27438128e+00 1.75029397e-01 4.21777181e-02 1.29968190e+00
-4.24923822e-02 5.39678931e-02 -1.44465768e+00 5.68426013e-01
-8.14665388e-03 -1.13511300e+00 -3.18376124e-02 1.32286683e-01
5.18550336e-01 5.67030728e-01 2.20841691e-02 2.80047178e-01
5.15990973e-01 -9.85016406e-01 2.79639065e-01 3.43345731e-01
5.02445519e-01 -9.55620050e-01 8.77561212e-01 3.98984760e-01
-7.93254375e-01 -3.74383301e-01 3.73625830e-02 -1.53642461e-01
-2.81607896e-01 1.07731116e+00 -9.16568398e-01 1.27868474e-01
6.68344140e-01 8.62026215e-01 -5.93057573e-01 7.88452625e-01
-2.08431166e-02 1.10918093e+00 -5.39946675e-01 3.71273220e-01
4.41985756e-01 5.54543026e-02 8.50366354e-01 1.09546995e+00
-5.29445931e-02 -5.74246049e-01 3.06762576e-01 9.24719810e-01
8.77141133e-02 -4.73652743e-02 -1.07184160e+00 -1.53773636e-01
2.01964632e-01 1.16465092e+00 -6.19806290e-01 -3.75925332e-01
-3.06382746e-01 8.39003801e-01 1.45997211e-01 3.45679790e-01
-4.66411829e-01 -4.37637508e-01 7.42023706e-01 6.42061234e-03
1.76228285e-01 2.87527740e-01 -4.11006272e-01 -1.13039422e+00
2.04682767e-01 -8.92648220e-01 8.19531620e-01 4.16936986e-02
-1.47709632e+00 7.67046154e-01 -1.41611665e-01 -1.25571716e+00
-7.98102319e-01 -7.92983651e-01 -1.41406047e+00 4.49465036e-01
-1.17802024e+00 -4.43714619e-01 -2.58248895e-01 6.68730438e-01
3.96281421e-01 -6.69669628e-01 7.97646165e-01 -9.21411961e-02
-1.08415413e+00 8.57885182e-01 1.62429884e-01 5.63539624e-01
4.51180637e-01 -1.63303781e+00 8.86264384e-01 1.41843033e+00
4.39459711e-01 3.08363646e-01 6.61754489e-01 -5.37805319e-01
-7.76696384e-01 -1.31787980e+00 3.93619418e-01 -6.54356480e-01
6.45087302e-01 -2.82147527e-01 -1.42539692e+00 8.71881247e-01
-2.04093277e-01 7.18453348e-01 8.16754818e-01 4.60255027e-01
-6.76390469e-01 -9.41370204e-02 -1.33190346e+00 3.36746484e-01
7.95342565e-01 -3.10639262e-01 -4.71273810e-01 2.39246711e-01
4.63081867e-01 -6.50879890e-02 -3.01562995e-01 4.87460852e-01
3.45995724e-01 -1.10154879e+00 6.87650263e-01 -1.17761302e+00
3.98748159e-01 1.25316053e-03 -1.17502674e-01 -1.23574555e+00
6.67666718e-02 -6.93935156e-01 -8.86726916e-01 8.25201929e-01
7.16440082e-01 -1.07304692e+00 1.01680160e+00 6.10881448e-01
-5.11745997e-02 -8.68242621e-01 -8.55968952e-01 -8.50805521e-01
-3.23513150e-01 -8.43728364e-01 5.42773426e-01 1.09120357e+00
1.26296701e-02 3.78463715e-02 -2.27605164e-01 3.11205000e-01
7.45178759e-01 -1.34100825e-01 5.39035201e-01 -1.86302793e+00
-2.77700096e-01 -6.48862362e-01 -5.26561201e-01 -5.48213363e-01
2.00640082e-01 -8.06550503e-01 1.37632608e-01 -7.35776544e-01
-2.74347126e-01 -2.32389331e-01 -9.11298096e-01 9.81075525e-01
-1.24438427e-01 4.01003778e-01 -5.94565749e-01 1.14390850e-01
-8.13057542e-01 2.71276176e-01 1.46325454e-01 1.15905240e-01
-4.37166303e-01 5.24194956e-01 -6.87667966e-01 1.06639051e+00
1.14995849e+00 -5.75367272e-01 -2.31592968e-01 1.42886803e-01
8.22650790e-02 -4.56168801e-01 4.69381452e-01 -1.21343684e+00
1.54766440e-01 -1.01123095e-01 3.76994252e-01 -6.02258682e-01
-3.00103754e-01 -9.01047707e-01 -7.22597122e-01 5.33061385e-01
-6.29866660e-01 2.14195341e-01 2.19586805e-01 1.02701247e+00
-2.54312724e-01 -2.98469514e-02 6.87743545e-01 2.35963032e-01
-6.12959445e-01 5.08874118e-01 -5.36368072e-01 3.19092572e-01
1.04423034e+00 -2.11938128e-01 -1.56159714e-01 -3.39973718e-01
-7.79060781e-01 5.10827541e-01 9.71421301e-02 3.51335466e-01
6.41329825e-01 -1.26740742e+00 -6.79768741e-01 8.07826221e-01
6.80113852e-01 3.54424715e-01 -1.27945483e-01 9.44310129e-01
-1.53681025e-01 -1.89606789e-02 -2.16490895e-01 -1.04111898e+00
-1.14074767e+00 4.33000892e-01 4.76727724e-01 -3.47278267e-01
-6.96542978e-01 6.30963683e-01 -1.45435646e-01 -5.09736657e-01
6.29086435e-01 -4.74804640e-01 -7.23999739e-02 -8.08646083e-02
7.93748260e-01 3.06459695e-01 2.26669818e-01 -1.50991395e-01
-3.89143854e-01 -2.63980031e-01 -6.35187685e-01 1.87788717e-02
1.25070393e+00 3.41314256e-01 1.22980498e-01 9.22589779e-01
1.04832470e+00 -2.46927932e-01 -1.22183275e+00 -6.89154029e-01
4.44240808e-01 -3.64953727e-01 -3.29170935e-02 -7.33985841e-01
-1.10248590e+00 7.72944391e-01 5.64867020e-01 5.43292642e-01
1.25676322e+00 -1.01204842e-01 4.80368286e-01 9.68593597e-01
-2.16651797e-01 -1.16735232e+00 2.01796412e-01 5.83384037e-01
3.62892359e-01 -1.50637460e+00 -3.31338406e-01 1.65635437e-01
-6.80315495e-01 9.64397073e-01 8.47437978e-01 -2.71601439e-01
5.85953116e-01 2.84674883e-01 8.17993805e-02 -3.56328994e-01
-1.09868252e+00 -6.33338913e-02 3.60599399e-01 5.96800148e-01
-5.19616976e-02 -3.30686808e-01 6.12613797e-01 5.02705395e-01
2.80868918e-01 -4.80837703e-01 4.52331662e-01 1.02624714e+00
-6.20562434e-01 -7.93308020e-01 -2.54389316e-01 1.05707741e+00
-8.68550301e-01 4.84923320e-03 -5.66396236e-01 5.22598803e-01
-3.11043382e-01 7.45657742e-01 4.38929141e-01 -4.09338832e-01
3.78855199e-01 7.00957119e-01 -4.77108717e-01 -6.22597218e-01
-4.59617972e-01 -1.92546532e-01 3.37533318e-02 -1.07096124e+00
-2.63431221e-02 -6.81785822e-01 -1.07247531e+00 2.16023363e-02
-1.55001923e-01 2.01130003e-01 2.53285408e-01 1.20573866e+00
4.90586847e-01 5.38531363e-01 9.19494092e-01 -4.77033854e-01
-7.29018152e-01 -9.44162011e-01 -5.95197380e-01 4.87711519e-01
9.49994504e-01 -3.28058571e-01 -7.26269782e-01 -4.18433219e-01] | [7.604815483093262, 2.420433521270752] |
1d5dbab5-2c26-4f56-9c9e-cdded5b07662 | cattle-detection-occlusion-problem | 2212.11418 | null | https://arxiv.org/abs/2212.11418v1 | https://arxiv.org/pdf/2212.11418v1.pdf | Cattle Detection Occlusion Problem | The management of cattle over a huge area is still a challenging problem in the farming sector. With evolution in technology, Unmanned aerial vehicles (UAVs) with consumer level digital cameras are becoming a popular alternative to manual animal censuses for livestock estimation since they are less risky and expensive.This paper evaluated and compared the cutting-edge object detection algorithms, YOLOv7,RetinaNet with ResNet50 backbone, RetinaNet with EfficientNet and mask RCNN. It aims to improve the occlusion problem that is to detect hidden cattle from a huge dataset captured by drones using deep learning algorithms for accurate cattle detection. Experimental results showed YOLOv7 was superior with precision of 0.612 when compared to the other two algorithms. The proposed method proved superior to the usual competing algorithms for cow face detection, especially in very difficult cases. | ['Vaishnavi Mendu', 'Bhavya Sehgal', 'Aparna Mendu'] | 2022-12-21 | null | null | null | null | ['face-detection'] | ['computer-vision'] | [ 8.25536251e-02 -5.25788069e-02 1.32499397e-01 -1.57470316e-01
6.39686704e-01 -1.97743699e-01 -3.13140824e-02 -2.14126155e-01
-6.39995933e-01 8.07483196e-01 -6.09355271e-01 -1.25551194e-01
-9.78958905e-02 -8.62472534e-01 -6.60156608e-01 -4.82482642e-01
-4.19205785e-01 3.70215684e-01 4.18601662e-01 -3.86724710e-01
4.54547442e-02 8.12300444e-01 -2.09111285e+00 1.22779213e-01
4.17320788e-01 1.00306499e+00 4.74591732e-01 9.53508019e-01
5.09891152e-01 8.65681767e-01 -3.55645269e-01 -5.01998723e-01
5.52393973e-01 -2.63720006e-03 -2.58722752e-01 -7.08443252e-03
7.65211999e-01 -6.69776499e-01 4.64911275e-02 1.20735991e+00
5.20235956e-01 -1.42949596e-01 6.27597451e-01 -1.26244438e+00
-4.61193204e-01 1.31012619e-01 -1.17443633e+00 7.78034091e-01
-8.29140842e-02 5.61372265e-02 1.96618870e-01 -5.13301671e-01
8.14399421e-01 1.42716777e+00 1.06626320e+00 2.70940781e-01
-1.20608211e+00 -9.23742175e-01 -3.30404013e-01 5.59546590e-01
-1.47607553e+00 -4.31031048e-01 4.83431295e-02 -4.50907558e-01
1.04477561e+00 -5.42266713e-03 6.93238199e-01 4.72069740e-01
3.90877455e-01 4.78426188e-01 9.22640085e-01 -4.01009679e-01
-3.58484387e-01 2.99057603e-01 1.65841505e-01 1.18779719e+00
1.00204861e+00 5.24493992e-01 7.74409063e-03 7.29739368e-02
1.05734754e+00 -2.95774406e-03 -1.11373030e-01 -5.41590929e-01
-1.04317784e+00 1.00581169e+00 5.70465922e-01 4.56528589e-02
-8.69185507e-01 1.74846947e-01 3.10965598e-01 3.94298971e-01
3.19253147e-01 2.77474016e-01 -6.05089188e-01 5.46208620e-01
-9.57242191e-01 3.61996323e-01 6.80424452e-01 1.18416607e+00
4.56582099e-01 5.30875087e-01 7.55612552e-02 4.25139397e-01
4.55916286e-01 9.05945361e-01 -2.88937837e-01 -8.74701679e-01
5.64827211e-02 7.97858059e-01 2.01653048e-01 -1.29253948e+00
-5.55724800e-01 -3.45443785e-01 -1.00214088e+00 7.82683074e-01
4.09223557e-01 -6.67910337e-01 -1.26340628e+00 1.00088835e+00
5.26497900e-01 1.59920827e-01 8.50598812e-02 9.02239621e-01
1.17882133e+00 7.55665720e-01 2.36046553e-01 6.96257278e-02
1.87123311e+00 -6.81991696e-01 -6.71211302e-01 -9.66777951e-02
3.46314996e-01 -9.38750863e-01 -2.18406200e-01 4.54520047e-01
-6.92578077e-01 -6.43776417e-01 -1.31258273e+00 2.76851684e-01
-5.76753974e-01 7.66314805e-01 7.20792413e-01 8.83254170e-01
-1.24493408e+00 3.85365695e-01 -6.39790714e-01 -9.18308616e-01
5.96642017e-01 7.34184861e-01 -5.56050122e-01 4.45973389e-02
-8.59291553e-01 1.30768061e+00 7.06907988e-01 5.41403532e-01
-8.89838159e-01 -4.94508922e-01 -8.05427849e-01 -1.19796932e-01
5.19250512e-01 -6.27153814e-01 9.31667686e-01 -1.07579803e+00
-1.08729756e+00 1.32826877e+00 5.43202221e-01 -1.14960289e+00
6.14404261e-01 -3.43380868e-01 -3.05353999e-01 2.74869204e-01
-1.66476071e-01 1.16191721e+00 9.18099642e-01 -8.45065534e-01
-1.08897674e+00 -5.35536706e-01 -6.11895397e-02 -7.81368930e-03
5.70034564e-01 3.34818363e-01 1.72148496e-01 -2.25993589e-01
-1.88616619e-01 -8.73032153e-01 -6.36512712e-02 2.80543089e-01
7.51617625e-02 -1.07905259e-02 1.30200863e+00 -7.18250215e-01
6.29885495e-01 -1.78009033e+00 -3.19220692e-01 4.55117151e-02
1.12587698e-01 9.59790826e-01 -1.19654641e-01 1.65922847e-02
1.28077015e-01 -4.83730108e-01 -7.01145232e-02 7.32092798e-01
-5.54090083e-01 -1.56466275e-01 2.89784759e-01 8.35700035e-01
3.14573199e-01 7.73296654e-01 -6.52126074e-01 -7.83298850e-01
6.77439034e-01 7.01792002e-01 -3.80980283e-01 -4.44433615e-02
1.32819116e-01 -1.21085659e-01 -1.92244709e-01 1.06259882e+00
1.11291409e+00 3.27917337e-01 -1.12637684e-01 -4.98740017e-01
-2.52840579e-01 -9.87932920e-01 -1.20294929e+00 9.08019304e-01
-2.96183117e-02 1.13723481e+00 5.85877657e-01 -1.00931728e+00
9.42749739e-01 4.63420182e-01 1.52235450e-02 3.01291309e-02
7.27341413e-01 -6.26055002e-02 2.56875545e-01 -8.51256430e-01
4.53257948e-01 2.57510722e-01 5.96615672e-01 -3.04362088e-01
4.72819179e-01 1.70528933e-01 3.52961838e-01 -2.48940840e-01
7.26876438e-01 4.21976745e-01 8.54481995e-01 -5.97819328e-01
3.46861452e-01 5.13474166e-01 3.15542132e-01 5.60478210e-01
-4.63601410e-01 3.58313888e-01 3.96040231e-01 -7.21970320e-01
-8.06767225e-01 -5.60057223e-01 -2.82548428e-01 9.36663747e-01
2.78278232e-01 4.66142237e-01 -9.51698422e-01 -3.80421847e-01
3.23496789e-01 3.21450591e-01 -6.23115182e-01 1.83696404e-01
-5.09667218e-01 -1.04946303e+00 5.63842654e-01 2.97808379e-01
1.26336837e+00 -1.27465343e+00 -1.55742252e+00 2.26343691e-01
3.54995638e-01 -1.13687766e+00 3.14679354e-01 4.11948562e-01
-9.01534498e-01 -1.43233931e+00 -9.49705303e-01 -1.12010241e+00
6.52416587e-01 7.77617157e-01 1.00070894e+00 1.33343577e-01
-1.13374126e+00 -9.83246788e-02 -1.45843804e-01 -9.58950996e-01
-8.16530585e-02 -2.30408505e-01 -9.03473049e-02 -3.31036955e-01
1.12344980e+00 -4.35245894e-02 -8.92777503e-01 3.01608413e-01
-5.16426325e-01 -2.87564129e-01 1.02962637e+00 6.88206553e-01
2.67832838e-02 1.65536121e-01 3.05827916e-01 -1.05652511e+00
2.41760254e-01 -4.80766386e-01 -1.30014360e+00 2.36607224e-01
-2.42527977e-01 -2.44011506e-01 -1.02996767e-01 -1.49436608e-01
-9.57317293e-01 5.67856848e-01 4.08435434e-01 -2.97011524e-01
-5.06896257e-01 -7.20434338e-02 2.47262880e-01 -5.70981741e-01
6.35355532e-01 -4.30307776e-01 6.90575540e-02 -3.07189792e-01
1.50495857e-01 6.82458818e-01 6.85970485e-01 4.80089009e-01
4.15605366e-01 2.92200714e-01 2.00655624e-01 -1.60115409e+00
-1.02434307e-01 -5.40532529e-01 -8.71683180e-01 -6.02477193e-01
1.34888673e+00 -1.13819158e+00 -9.71946597e-01 6.42563641e-01
-1.46473312e+00 1.72274724e-01 3.88031721e-01 8.14106762e-01
5.09455204e-02 -2.27301498e-03 -4.57792103e-01 -9.90093589e-01
-6.32009625e-01 -6.27495229e-01 8.33771288e-01 4.30997223e-01
1.12227825e-02 -4.34936255e-01 -3.97985071e-01 3.18977714e-01
2.40973771e-01 7.30522394e-01 4.56231743e-01 -1.76182404e-01
-6.62687302e-01 -4.84033614e-01 -7.92628109e-01 3.50370228e-01
-1.03001013e-01 4.32657987e-01 -1.05527568e+00 -2.35233471e-01
-1.01478226e-01 1.56284034e-01 1.14980888e+00 1.02596807e+00
4.18537825e-01 1.88194700e-02 -7.02476859e-01 7.14142740e-01
1.76807964e+00 6.76634967e-01 5.83103240e-01 3.36366773e-01
4.35548872e-01 7.04523444e-01 7.84914196e-01 1.96342736e-01
-3.07796329e-01 3.18036109e-01 7.65787780e-01 -2.72862315e-01
6.54684827e-02 2.21783698e-01 1.08727865e-01 -1.58412359e-03
-7.84427464e-01 -4.96426284e-01 -7.93377936e-01 4.84326065e-01
-1.66859424e+00 -1.06681287e+00 -4.10651475e-01 1.85295856e+00
-2.65778191e-02 -4.03549671e-02 4.45716567e-02 4.73256409e-02
1.31634164e+00 -1.57982573e-01 -2.39340410e-01 -5.14581263e-01
4.60329372e-03 2.43744165e-01 1.42110038e+00 -1.60793573e-01
-1.56761932e+00 1.11700499e+00 6.01813412e+00 4.30544198e-01
-8.63283217e-01 3.83657813e-02 2.99225092e-01 2.27490976e-01
1.27809870e+00 -5.98994613e-01 -9.58187103e-01 1.62904993e-01
5.48737228e-01 6.06391251e-01 1.10225968e-01 1.03260720e+00
-1.95531473e-01 -7.40917265e-01 -7.29566574e-01 8.92179966e-01
4.47122119e-02 -9.52690184e-01 -1.33106798e-01 -1.87818378e-01
7.31908679e-01 -9.10003036e-02 -1.62293941e-01 6.33295700e-02
5.67704797e-01 -1.12560153e+00 2.39958227e-01 1.09232754e-01
6.64952636e-01 -9.39192474e-01 1.41147125e+00 1.52098730e-01
-1.17456150e+00 4.44699302e-02 -1.05235529e+00 -9.04553011e-02
-1.06430203e-01 -1.32014100e-02 -8.48962367e-01 7.86020979e-02
9.45969999e-01 4.48376954e-01 -4.92070049e-01 1.40223241e+00
1.08086668e-01 2.20099002e-01 -3.72862786e-01 -2.50706166e-01
6.14000440e-01 -2.90481448e-01 6.17275894e-01 1.33127916e+00
4.92059141e-01 4.28349227e-01 -3.68421376e-01 5.91753602e-01
6.64535165e-02 -7.95926303e-02 -1.15447557e+00 1.72354952e-01
1.40209496e-01 1.45414114e+00 -1.19559169e+00 -9.48643684e-02
-4.11437839e-01 7.45944798e-01 -4.27133232e-01 1.86496168e-01
-7.86826134e-01 -9.08599973e-01 4.63456929e-01 1.92997545e-01
7.06409693e-01 2.21211806e-01 5.12086332e-01 -5.26427209e-01
-4.53000307e-01 -6.68037653e-01 2.51095712e-01 -9.53774631e-01
-6.28594279e-01 7.21851885e-01 2.13742584e-01 -1.23619318e+00
1.50477201e-01 -1.20277631e+00 -2.28293508e-01 3.61863732e-01
-1.42442000e+00 -1.40272856e+00 -5.73696852e-01 1.91409901e-01
6.60454273e-01 -6.97269261e-01 6.56624675e-01 3.86288702e-01
-4.54591662e-01 3.34261768e-02 1.75420642e-01 2.80131489e-01
3.37732226e-01 -8.56497407e-01 1.46710277e-01 8.76604795e-01
-1.99498191e-01 1.19441628e-01 7.32241631e-01 -9.18284237e-01
-1.31615603e+00 -1.31812143e+00 4.11198348e-01 -5.98144010e-02
1.31875843e-01 -2.33623609e-02 -4.83436346e-01 7.25810945e-01
6.25765741e-01 6.38149306e-02 6.86431769e-04 -6.90001965e-01
4.35016930e-01 -2.68532157e-01 -1.48272395e+00 2.15013027e-02
7.41418183e-01 2.83054590e-01 -5.21204412e-01 1.66064203e-02
1.65219948e-01 -3.30512792e-01 -1.61320090e-01 7.33036816e-01
9.10311341e-01 -8.84073853e-01 1.11635518e+00 -5.11761665e-01
2.85041362e-01 -3.86141092e-01 4.28717583e-02 -1.01125312e+00
-4.14012671e-01 -4.23831642e-01 1.98418245e-01 1.00016594e+00
1.53576583e-01 -5.89445293e-01 9.84041452e-01 -4.33290392e-01
2.85891265e-01 -1.83407888e-01 -5.34000874e-01 -5.89793026e-01
-7.79894233e-01 3.54411572e-01 4.55325335e-01 5.93236148e-01
-8.19635868e-01 1.93540365e-01 -6.24041677e-01 5.15097439e-01
8.82496774e-01 -7.80469552e-02 6.23663485e-01 -1.69796550e+00
4.96977955e-01 -6.39691204e-02 -1.46500194e+00 -4.83246744e-01
-3.11486185e-01 -4.73618180e-01 1.04665451e-01 -1.41308808e+00
9.50590242e-03 2.07704529e-01 -5.89143597e-02 2.23766211e-02
3.99664193e-02 6.98923409e-01 1.41029907e-02 -3.29254478e-01
-3.82545620e-01 -3.82154107e-01 1.04757452e+00 -1.88536212e-01
-9.02948976e-02 3.69596720e-01 -7.20555261e-02 1.00452232e+00
7.09201515e-01 -4.95254606e-01 -1.81248292e-01 -4.68735516e-01
-1.24765262e-02 4.72609922e-02 6.32204950e-01 -1.36977792e+00
1.76217586e-01 2.73658544e-01 9.14964676e-01 -1.11657357e+00
1.76772997e-01 -1.23458648e+00 4.12551880e-01 1.00011659e+00
1.28430560e-01 1.97678894e-01 4.46103841e-01 6.91790700e-01
-1.28480494e-01 -3.88997197e-01 1.12838805e+00 -4.34832513e-01
-1.27662611e+00 -1.15797222e-01 -7.64722824e-01 -4.80474830e-01
1.64181495e+00 -6.01566494e-01 -2.22445562e-01 1.40853584e-01
-5.67215085e-01 4.46748167e-01 1.17126897e-01 3.12331289e-01
5.37928879e-01 -8.89188170e-01 -1.02139509e+00 3.74686956e-01
-6.85631558e-02 -5.28118424e-02 -3.64500680e-03 7.60175347e-01
-1.95095551e+00 8.04086745e-01 -1.09203482e+00 -7.23842621e-01
-2.00896382e+00 5.45976043e-01 2.37491176e-01 3.04527551e-01
-4.36498612e-01 1.13199425e+00 2.12287679e-01 1.69823673e-02
5.30478477e-01 -5.74161530e-01 -9.42005217e-01 3.06219012e-01
3.94063234e-01 1.04422605e+00 -9.22558233e-02 -7.84291923e-01
-3.47523540e-01 7.23605633e-01 9.76318121e-02 6.47502542e-01
1.50049841e+00 1.50633240e-02 -1.08808085e-01 -1.80537835e-01
6.77280426e-01 -7.19813406e-01 -9.57027435e-01 7.51159340e-02
2.17031986e-01 -3.71220648e-01 4.66157824e-01 -5.12054384e-01
-1.42549717e+00 9.42991912e-01 1.45479345e+00 1.98671743e-01
9.75011706e-01 -5.98361135e-01 4.75590408e-01 6.77530944e-01
3.67809683e-01 -9.94068205e-01 -6.93949819e-01 8.13806430e-02
5.71085274e-01 -1.63795745e+00 5.54609835e-01 -4.61209625e-01
-7.42840469e-01 1.36707556e+00 8.80725145e-01 -5.47732472e-01
5.62065065e-01 2.60640532e-01 1.51383579e-01 -5.91770589e-01
-4.61161464e-01 -5.45110643e-01 5.88507243e-02 9.57107723e-01
2.55210161e-01 7.24432617e-02 -1.58556655e-01 -1.46848500e-01
2.44964331e-01 4.17033255e-01 3.78189415e-01 1.05992806e+00
-8.88800621e-01 -2.04719245e-01 -6.15604460e-01 7.06420481e-01
-8.27829063e-01 5.71880527e-02 -2.68665224e-01 1.38568842e+00
6.90074563e-01 8.28625023e-01 5.33228889e-02 -5.51157966e-02
3.54354590e-01 -2.68441349e-01 5.89143634e-01 -5.90001285e-01
-6.38476849e-01 -1.16125658e-01 1.80866271e-01 -2.58136809e-01
-8.93746257e-01 -3.21684033e-01 -5.64214110e-01 -4.57418412e-01
-1.06247163e+00 -6.84964061e-02 8.07213604e-01 2.81336844e-01
-5.08531602e-03 4.25146341e-01 1.17555067e-01 -9.08518791e-01
-1.62018329e-01 -9.89636779e-01 -8.88100505e-01 -5.31170189e-01
4.40233946e-01 -9.66478169e-01 -1.49288401e-02 5.88474631e-01] | [8.568172454833984, -0.8881064057350159] |
2f977227-3d7a-4745-b608-78ba98ea6644 | multi-attention-network-for-compressed-video | 2207.12622 | null | https://arxiv.org/abs/2207.12622v1 | https://arxiv.org/pdf/2207.12622v1.pdf | Multi-Attention Network for Compressed Video Referring Object Segmentation | Referring video object segmentation aims to segment the object referred by a given language expression. Existing works typically require compressed video bitstream to be decoded to RGB frames before being segmented, which increases computation and storage requirements and ultimately slows the inference down. This may hamper its application in real-world computing resource limited scenarios, such as autonomous cars and drones. To alleviate this problem, in this paper, we explore the referring object segmentation task on compressed videos, namely on the original video data flow. Besides the inherent difficulty of the video referring object segmentation task itself, obtaining discriminative representation from compressed video is also rather challenging. To address this problem, we propose a multi-attention network which consists of dual-path dual-attention module and a query-based cross-modal Transformer module. Specifically, the dual-path dual-attention module is designed to extract effective representation from compressed data in three modalities, i.e., I-frame, Motion Vector and Residual. The query-based cross-modal Transformer firstly models the correlation between linguistic and visual modalities, and then the fused multi-modality features are used to guide object queries to generate a content-aware dynamic kernel and to predict final segmentation masks. Different from previous works, we propose to learn just one kernel, which thus removes the complicated post mask-matching procedure of existing methods. Extensive promising experimental results on three challenging datasets show the effectiveness of our method compared against several state-of-the-art methods which are proposed for processing RGB data. Source code is available at: https://github.com/DexiangHong/MANet. | ['Guorong Li', 'Qingming Huang', 'Laiyun Qing', 'Shuhui Wang', 'Zhenjun Han', 'Yuankai Qi', 'Dexiang Hong', 'Weidong Chen'] | 2022-07-26 | null | null | null | null | ['referring-expression-segmentation', 'referring-video-object-segmentation'] | ['computer-vision', 'computer-vision'] | [ 4.42527086e-01 -2.17046991e-01 -3.58757466e-01 -3.45094413e-01
-8.77797365e-01 -3.26969206e-01 2.66597539e-01 -3.33107203e-01
-5.84823012e-01 2.70350367e-01 2.90655252e-02 -1.27798170e-01
6.19190820e-02 -7.64861345e-01 -9.01521623e-01 -6.51507616e-01
4.37125772e-01 1.42380903e-02 4.60652292e-01 -5.94691224e-02
3.35243285e-01 2.92517751e-01 -1.61789310e+00 3.87821913e-01
9.32572007e-01 1.26269233e+00 5.11833429e-01 5.00229955e-01
-2.98242927e-01 8.89171720e-01 -2.05348402e-01 -4.01380450e-01
1.64666846e-01 -5.19089818e-01 -8.68629456e-01 4.32321727e-01
2.19160080e-01 -6.15708351e-01 -6.88276947e-01 1.25535834e+00
3.53227913e-01 4.03623819e-01 2.93732733e-01 -1.28896213e+00
-6.45224690e-01 4.87852424e-01 -6.80078626e-01 5.26608944e-01
4.01126504e-01 3.20902765e-01 7.53880799e-01 -7.71896482e-01
4.75786865e-01 1.20974326e+00 1.50522709e-01 6.42354965e-01
-7.34214127e-01 -6.56632721e-01 4.56901997e-01 6.90478206e-01
-1.43665028e+00 -5.52220821e-01 9.70587850e-01 -3.04298878e-01
6.56114399e-01 2.83333838e-01 7.45709717e-01 7.87263632e-01
-2.09297955e-01 1.26503289e+00 7.48478472e-01 2.98184380e-02
-1.11708611e-01 -6.48421347e-02 -8.00111368e-02 7.43646622e-01
-1.93530470e-01 -1.29959881e-01 -3.13389212e-01 3.90472472e-01
6.62799358e-01 3.54960084e-01 -6.39331639e-01 -7.87732080e-02
-1.27425325e+00 6.73325777e-01 6.17367983e-01 3.37256074e-01
-5.31779230e-01 2.01261461e-01 3.97558928e-01 -1.21597193e-01
3.33883256e-01 -2.59180754e-01 -4.20336515e-01 -1.44101933e-01
-1.10415149e+00 -4.84519359e-03 4.04356152e-01 1.15119958e+00
8.48511398e-01 5.87809682e-02 -2.48418033e-01 7.08905160e-01
4.84163254e-01 4.48272020e-01 5.86196899e-01 -9.14768577e-01
7.48635173e-01 6.91697180e-01 -1.43116936e-01 -1.10524082e+00
-1.96085632e-01 -1.06050938e-01 -7.89306641e-01 -3.74973208e-01
1.97955817e-01 6.27897456e-02 -1.03630936e+00 1.52473330e+00
5.14328837e-01 4.32451636e-01 4.98965830e-02 1.45452881e+00
1.03880310e+00 1.00882208e+00 1.88883722e-01 -2.30401650e-01
1.39194989e+00 -1.22293890e+00 -7.19863117e-01 -2.96422005e-01
3.89538884e-01 -7.02053130e-01 9.83195841e-01 1.93593368e-01
-1.20210862e+00 -7.63071835e-01 -8.71565223e-01 -3.57678324e-01
-3.49259913e-01 1.81132063e-01 5.05906522e-01 2.94917524e-01
-6.62942588e-01 2.46391132e-01 -8.60786438e-01 -1.44382253e-01
7.28991389e-01 3.89449894e-01 -2.16656983e-01 -4.18244809e-01
-1.17426550e+00 5.06056786e-01 7.58939803e-01 4.13572490e-01
-7.46984005e-01 -4.60211247e-01 -8.28130960e-01 -2.47075055e-02
8.10916603e-01 -5.46138167e-01 1.08488536e+00 -1.14823377e+00
-1.35589302e+00 6.68191612e-01 -3.27809632e-01 -2.29981750e-01
4.11434680e-01 -2.09280938e-01 -2.82543302e-01 4.47734922e-01
6.65646791e-02 9.31925893e-01 9.41034317e-01 -1.19445002e+00
-9.81695414e-01 -3.30629498e-01 2.40693182e-01 4.32398349e-01
-2.68911183e-01 -1.66510753e-02 -1.43815744e+00 -6.10016406e-01
2.69669265e-01 -7.25859582e-01 -4.21596505e-03 -8.59324113e-02
-3.14924598e-01 -2.29830027e-01 1.15057647e+00 -9.67159152e-01
1.24370706e+00 -2.17459011e+00 4.39248919e-01 -1.61921933e-01
6.24441868e-03 3.21121156e-01 -9.19333100e-02 -1.93154559e-01
4.67035174e-02 1.03166409e-01 -3.80476415e-01 -1.91747457e-01
-1.03952557e-01 2.40118533e-01 -5.32876886e-02 6.09649122e-01
4.31139380e-01 9.11906302e-01 -8.08662713e-01 -8.91768515e-01
4.51523334e-01 6.04283512e-01 -5.91266811e-01 3.82276028e-01
-3.04534823e-01 4.83921915e-01 -7.40142524e-01 1.05773091e+00
7.90143967e-01 -1.83311686e-01 -2.93643922e-01 -7.49889791e-01
-1.88558735e-02 -1.67460188e-01 -9.41252053e-01 1.86372626e+00
-3.90694857e-01 4.09700155e-01 1.41808659e-01 -1.32292879e+00
6.37182057e-01 1.10803410e-01 6.03081167e-01 -9.30834115e-01
5.80651164e-01 1.79090071e-02 -1.79176018e-01 -9.11137760e-01
5.09405851e-01 1.27994522e-01 -1.07923679e-01 8.90634432e-02
-3.97197641e-02 1.16252154e-02 3.87378246e-01 1.01968266e-01
6.00002170e-01 5.12166142e-01 -8.97265971e-03 1.65448710e-01
1.00039363e+00 -4.12593558e-02 7.86316097e-01 1.89314827e-01
-3.67849559e-01 5.71473360e-01 3.35434854e-01 -1.54059619e-01
-8.00264478e-01 -6.46221876e-01 9.83366743e-02 1.04431117e+00
7.61393666e-01 -1.09888852e-01 -8.62840354e-01 -6.70958102e-01
-2.12997884e-01 5.77200234e-01 -4.46576118e-01 -2.56857365e-01
-7.48029172e-01 -5.31066895e-01 2.21111283e-01 5.78086197e-01
8.73748302e-01 -1.06339240e+00 -7.68970668e-01 5.66529855e-02
-6.43608928e-01 -1.47818100e+00 -7.20578611e-01 -1.98772073e-01
-7.42994726e-01 -1.08133364e+00 -6.85230196e-01 -7.24308014e-01
5.82835495e-01 4.84528899e-01 7.75493443e-01 2.88435370e-01
-1.24636970e-01 4.51730669e-01 -5.59482038e-01 1.70307572e-03
6.23117387e-02 9.64976698e-02 -3.93074811e-01 3.91924202e-01
5.73371828e-01 -2.14174017e-01 -8.29073310e-01 3.04976821e-01
-1.26211858e+00 2.30222389e-01 8.07833731e-01 7.84317315e-01
7.70945072e-01 -2.28653406e-03 2.98929334e-01 -4.36590075e-01
3.29473317e-02 -6.97381794e-01 -6.27131402e-01 2.94259816e-01
-1.14861377e-01 -2.11812004e-01 5.85872173e-01 -3.83955121e-01
-9.22943234e-01 2.75689185e-01 -2.55568653e-01 -8.33807170e-01
-1.41771048e-01 4.08471584e-01 -5.76210380e-01 6.76737428e-02
-2.38660082e-01 6.42869353e-01 -1.33140489e-01 -2.74601966e-01
3.33694935e-01 8.20545077e-01 6.24603331e-01 -3.66547376e-01
6.67283595e-01 4.29015547e-01 -3.54135305e-01 -7.38881409e-01
-6.78782582e-01 -5.03260195e-01 -5.57714522e-01 -4.06079203e-01
1.31904423e+00 -9.26421106e-01 -7.78102636e-01 2.95023233e-01
-1.22938406e+00 -1.66224241e-01 3.34870480e-02 4.77790803e-01
-6.02669954e-01 4.43488926e-01 -5.17998993e-01 -6.97807372e-01
-3.21926951e-01 -1.55077970e+00 1.22857249e+00 4.85932142e-01
3.70253712e-01 -6.32904708e-01 -6.29577816e-01 8.87353837e-01
1.76727042e-01 1.18881270e-01 5.85424423e-01 -4.19813752e-01
-1.16848135e+00 -4.50360738e-02 -6.45560980e-01 3.97877157e-01
-2.18466949e-02 -9.34896916e-02 -7.67320871e-01 -1.52598605e-01
-3.32463868e-02 -2.83452719e-01 9.52367544e-01 2.14616239e-01
1.54771686e+00 -2.08779737e-01 -2.61366367e-01 9.71932709e-01
1.47169316e+00 4.67054456e-01 6.52596653e-01 2.65669137e-01
1.03898573e+00 4.29726839e-01 1.00808811e+00 2.82857507e-01
5.77955604e-01 6.68435693e-01 5.97211838e-01 4.03255858e-02
-1.49038965e-02 -6.29347190e-02 3.11105102e-01 8.04267883e-01
-5.93093634e-02 -3.97261560e-01 -7.09790170e-01 5.40098667e-01
-1.80867553e+00 -9.30968225e-01 1.34468272e-01 1.80380070e+00
6.30232334e-01 -6.39113635e-02 -3.50832054e-03 8.56309086e-02
7.25780427e-01 2.73974866e-01 -8.08425605e-01 1.13154156e-03
3.61570902e-02 -1.68429434e-01 4.56821233e-01 2.25781173e-01
-1.21630669e+00 1.03362727e+00 3.98459864e+00 1.11295736e+00
-1.31276715e+00 3.77117366e-01 7.71437407e-01 -1.21129297e-01
-2.43198499e-01 -9.93916690e-02 -7.11978197e-01 7.87416339e-01
6.71562076e-01 2.37448085e-02 5.81175566e-01 7.19565928e-01
2.36926734e-01 -2.30516016e-01 -9.19788957e-01 1.35488272e+00
3.04484338e-01 -1.12497652e+00 6.24150969e-02 -1.16153732e-01
4.09471333e-01 1.56970993e-02 -1.53082376e-02 3.16657454e-01
-4.31124777e-01 -6.32525504e-01 1.03473699e+00 6.62380040e-01
7.75660157e-01 -8.51980865e-01 7.70170331e-01 2.25906953e-01
-1.47704279e+00 -2.67728955e-01 -2.42902964e-01 5.22077739e-01
3.52976561e-01 2.12117612e-01 -2.22771645e-01 7.06482887e-01
8.41867328e-01 9.19193745e-01 -5.42437255e-01 8.23875666e-01
1.13214627e-01 4.46422338e-01 -3.53312880e-01 1.25027463e-01
4.81085181e-01 -3.28393519e-01 4.16500270e-01 1.18586040e+00
3.87474179e-01 4.88505572e-01 3.45297277e-01 9.08663690e-01
-9.45270360e-02 6.41064346e-02 -2.62668252e-01 -1.88111126e-01
2.96076328e-01 1.25962031e+00 -9.30446446e-01 -5.23458838e-01
-7.36189246e-01 1.26128626e+00 5.84767200e-02 4.87288624e-01
-1.31625187e+00 -3.37756753e-01 3.78732860e-01 -8.86861514e-03
6.35847151e-01 -1.74355626e-01 8.68143365e-02 -1.31325972e+00
1.82531357e-01 -8.37732911e-01 3.13276768e-01 -8.88302147e-01
-8.34050477e-01 6.46830618e-01 1.43915981e-01 -1.43492699e+00
1.94494799e-02 -4.07968163e-01 -3.76658738e-01 6.72699451e-01
-1.74567306e+00 -1.38059366e+00 -6.18517578e-01 8.70319605e-01
8.90796185e-01 5.10974899e-02 9.10231471e-02 7.40550160e-01
-1.07545531e+00 4.82190102e-01 -2.56161511e-01 2.52763152e-01
3.19763362e-01 -6.83850229e-01 -6.87898621e-02 1.08576524e+00
-5.42989559e-02 3.67038965e-01 3.05946738e-01 -5.44461846e-01
-1.81567359e+00 -1.34511030e+00 2.38012418e-01 9.38757882e-02
4.88061756e-01 -2.21841726e-02 -9.18038905e-01 5.13090849e-01
1.02134049e-01 3.51301879e-01 3.24502140e-01 -7.58041441e-01
-1.29357024e-04 -2.62003154e-01 -9.29973722e-01 3.93035620e-01
1.02993202e+00 -4.70957249e-01 -3.73600364e-01 2.32419863e-01
8.78357708e-01 -5.72981238e-01 -8.56582105e-01 5.00282884e-01
3.89202893e-01 -9.46163476e-01 9.21891153e-01 -2.96772033e-01
6.09729409e-01 -5.48527837e-01 -4.25805837e-01 -6.59842730e-01
-1.37625001e-02 -3.09801787e-01 -2.21114457e-01 1.45748675e+00
2.59666387e-02 -3.16357851e-01 7.07309306e-01 6.07261062e-01
-3.33373666e-01 -1.01620197e+00 -8.56865466e-01 -2.98406273e-01
-3.87820780e-01 -6.00924909e-01 5.53169012e-01 6.63267732e-01
-4.32419717e-01 2.77259201e-01 -3.08535427e-01 2.62996376e-01
5.21806538e-01 3.81227702e-01 6.42898500e-01 -5.44018090e-01
-1.60063744e-01 -4.46368098e-01 -5.16951919e-01 -1.53430021e+00
2.69821137e-01 -8.02543700e-01 1.86585203e-01 -1.45348883e+00
1.27275899e-01 -3.43749315e-01 -2.70228654e-01 2.91137040e-01
-3.35063279e-01 4.39818323e-01 4.60852295e-01 1.49344698e-01
-9.05777752e-01 7.89589584e-01 1.35163903e+00 -3.97310168e-01
-1.05920374e-01 -1.78509429e-01 -6.14401340e-01 6.87926471e-01
7.81472623e-01 -2.86793411e-01 -4.84369248e-01 -6.43790960e-01
-1.67367101e-01 2.98528045e-01 5.67162573e-01 -9.76034939e-01
3.74520600e-01 -2.66675860e-01 3.58394235e-01 -9.38515484e-01
5.28236628e-01 -1.02969241e+00 -9.21290591e-02 4.18751180e-01
-8.67359117e-02 -3.47759873e-02 1.05017714e-01 6.24707520e-01
-5.00300467e-01 -2.08201319e-01 7.80163229e-01 -1.65874347e-01
-1.15070534e+00 6.45048261e-01 -1.68730304e-01 1.02299206e-01
1.18595827e+00 -4.21281397e-01 -1.43991202e-01 -2.20777452e-01
-4.95530099e-01 4.93580490e-01 3.34305942e-01 5.14928758e-01
9.25667882e-01 -1.33217120e+00 -5.26984513e-01 2.23924056e-01
5.29252086e-03 2.90920079e-01 7.16082394e-01 1.19428873e+00
-5.79071164e-01 3.71678978e-01 -1.42403305e-01 -7.81104147e-01
-1.19475555e+00 8.94926131e-01 2.19808832e-01 2.95874208e-01
-5.40515482e-01 9.14646983e-01 1.10674471e-01 6.90847039e-02
2.65728086e-01 -4.78909820e-01 -3.22283506e-01 1.94810286e-01
4.99184132e-01 2.37697452e-01 -1.86017752e-01 -1.18797266e+00
-4.08039302e-01 9.19710755e-01 -3.63109820e-02 1.75874919e-01
1.08679259e+00 -4.65178221e-01 -1.37790546e-01 2.77266890e-01
1.57419372e+00 -4.08786356e-01 -1.29494917e+00 -2.78617918e-01
-3.38352323e-01 -6.99322760e-01 2.70122111e-01 -1.29580349e-01
-1.65148556e+00 9.36326802e-01 6.91212535e-01 2.62499768e-02
1.63132811e+00 3.92191596e-02 1.28740132e+00 1.38816223e-01
1.46124795e-01 -1.04775107e+00 -6.53039292e-03 2.17893571e-01
6.89399660e-01 -1.45373690e+00 6.32517636e-02 -4.68348891e-01
-7.17664778e-01 1.03692317e+00 8.71187150e-01 2.06703562e-02
5.17995358e-01 -9.01331156e-02 -1.18256599e-01 -6.52694106e-02
-5.07631779e-01 -4.46398437e-01 4.00106490e-01 3.22157145e-01
2.31601909e-01 -3.37929785e-01 -2.75516719e-01 6.26268685e-01
1.59972295e-01 1.50598019e-01 2.64483482e-01 8.95948887e-01
-3.04671079e-01 -7.51572430e-01 -3.91835243e-01 4.32502687e-01
-4.50916171e-01 1.51576325e-02 5.62963523e-02 6.69504702e-01
5.23591101e-01 9.66802478e-01 1.59981608e-01 -5.73981881e-01
3.37827325e-01 -1.03683986e-01 2.71506667e-01 -1.92283109e-01
-3.00461471e-01 3.66985798e-01 -2.48575956e-01 -9.05397773e-01
-9.68001902e-01 -7.06236660e-01 -1.43927097e+00 -1.34884015e-01
-3.93616855e-01 5.76932263e-03 4.87512052e-01 9.92699683e-01
2.10213125e-01 7.95981944e-01 5.92643738e-01 -1.24115574e+00
-1.63383052e-01 -7.04803586e-01 -1.92256466e-01 4.51248646e-01
4.18787301e-01 -7.17293501e-01 -1.71099588e-01 3.88974190e-01] | [9.406329154968262, 0.2397836297750473] |
85af4a5a-edf5-456b-8df0-c6e679379553 | online-abuse-detection-the-value-of | null | null | https://aclanthology.org/W19-1303 | https://aclanthology.org/W19-1303.pdf | Online abuse detection: the value of preprocessing and neural attention models | We propose an attention-based neural network approach to detect abusive speech in online social networks. Our approach enables more effective modeling of context and the semantic relationships between words. We also empirically evaluate the value of text pre-processing techniques in addressing the challenge of out-of-vocabulary words in toxic content. Finally, we conduct extensive experiments on the Wikipedia Talk page datasets, showing improved predictive power over the previous state-of-the-art. | ['Robin Cohen', 'Lukasz Golab', 'Dhruv Kumar'] | 2019-06-01 | null | null | null | ws-2019-6 | ['abuse-detection'] | ['natural-language-processing'] | [-4.80374806e-02 1.92737624e-01 -3.88599277e-01 -3.27483922e-01
-5.14699936e-01 -2.37207144e-01 5.66173017e-01 3.12193185e-01
-6.57414675e-01 4.18747276e-01 7.08905816e-01 -4.22794223e-01
-4.96305525e-02 -5.37733316e-01 -2.63745815e-01 1.00474814e-02
-2.66126007e-01 3.11562479e-01 2.33951688e-01 -7.88658559e-01
4.14723188e-01 3.57188642e-01 -8.75331938e-01 5.42920589e-01
5.51389217e-01 7.99597800e-01 -5.41129947e-01 4.82683957e-01
-4.78495508e-01 1.15239036e+00 -9.78567779e-01 -1.02828658e+00
-2.21280470e-01 -1.80170327e-01 -1.07798588e+00 -1.30034074e-01
5.79605043e-01 -4.18065578e-01 -1.04369092e+00 1.21344817e+00
5.90922177e-01 3.46123785e-01 5.82607925e-01 -9.59337831e-01
-9.34909165e-01 1.18980253e+00 -5.60582399e-01 1.22093892e+00
4.95577961e-01 5.55476211e-02 1.48548341e+00 -7.39873052e-01
8.02840710e-01 1.58374143e+00 6.33436441e-01 6.75639987e-01
-8.92060399e-01 -9.16511178e-01 3.92302364e-01 5.70230484e-01
-1.20789230e+00 -4.58197206e-01 1.04229653e+00 -4.74915057e-01
1.40159619e+00 1.99271426e-01 4.18918639e-01 2.00453186e+00
-1.63923666e-01 8.26894760e-01 4.36184049e-01 -3.25009942e-01
-2.12238565e-01 -1.39064953e-01 8.57059538e-01 5.88016570e-01
1.64820299e-01 -3.45610470e-01 -9.22791958e-01 -5.25915444e-01
-1.25236148e-02 -2.81658351e-01 -2.50822127e-01 3.52478355e-01
-4.09734875e-01 1.53786767e+00 4.69263613e-01 6.70632184e-01
-4.48131263e-01 2.31824979e-01 9.16603327e-01 1.96433648e-01
1.14795756e+00 6.18202746e-01 -2.04235375e-01 -2.26773649e-01
-8.27921629e-01 1.71602547e-01 1.07012081e+00 4.48748946e-01
6.53140396e-02 4.90471981e-02 -2.73882806e-01 1.13318729e+00
3.45761597e-01 1.25359014e-01 5.73383093e-01 -6.26264393e-01
7.61230052e-01 2.86041290e-01 -2.97424436e-01 -1.40609133e+00
-5.51900208e-01 -4.30210918e-01 -3.39720577e-01 -5.50333142e-01
2.22051069e-01 -2.96311885e-01 -5.72176754e-01 1.63136506e+00
8.19502100e-02 1.39569864e-01 -3.39221627e-01 4.87664431e-01
8.83492291e-01 4.23983186e-01 5.31983793e-01 -2.33631760e-01
1.25359166e+00 -8.97888601e-01 -1.22320962e+00 -5.86425841e-01
7.34262407e-01 -3.56070876e-01 1.05094635e+00 2.15606019e-01
-8.97207379e-01 1.88449278e-01 -9.75020528e-01 -1.42567664e-01
-7.75394976e-01 -7.62149751e-01 5.78847766e-01 8.39462757e-01
-7.20685601e-01 7.17290938e-01 -1.75975785e-01 -4.04790193e-01
8.42157066e-01 1.54435650e-01 -1.78229526e-01 3.85257125e-01
-1.87185740e+00 1.12776184e+00 1.62476107e-01 -3.34253997e-01
-7.53997147e-01 -6.82526112e-01 -6.54331863e-01 1.25232413e-01
5.87754786e-01 -7.36837760e-02 1.34758914e+00 -9.06738460e-01
-1.28037930e+00 9.77062166e-01 -3.44378613e-02 -6.94664896e-01
2.75961369e-01 -5.17352581e-01 -8.24855089e-01 3.86259973e-01
2.12506894e-02 1.68909937e-01 8.85591805e-01 -8.18906486e-01
-3.43148038e-02 -3.34240645e-01 2.61809766e-01 8.16475675e-02
-1.17360556e+00 7.97780871e-01 -3.44455838e-02 -7.72758245e-01
-5.46443343e-01 -6.06873691e-01 1.95208415e-01 -2.37106726e-01
-6.98743403e-01 -6.45726502e-01 1.02327096e+00 -1.11546195e+00
1.72650850e+00 -2.17337036e+00 1.38329893e-01 2.40828753e-01
6.03487551e-01 5.63653827e-01 -1.07200682e-01 5.04237473e-01
-2.25848064e-01 7.51486480e-01 6.22989573e-02 -6.59202218e-01
-2.28585154e-02 1.13938719e-01 -4.40649986e-01 4.53818858e-01
-3.74601260e-02 9.97119129e-01 -8.45341444e-01 -5.18034160e-01
-2.73379475e-01 4.47902799e-01 -5.49200356e-01 -6.73612114e-03
-1.53708294e-01 -1.76384315e-01 -3.87833238e-01 4.14729834e-01
6.24868646e-02 -9.18412507e-02 9.09082070e-02 1.71286315e-01
4.31557804e-01 1.04155219e+00 -2.55415231e-01 1.25999773e+00
-3.25972825e-01 1.14266670e+00 2.83089072e-01 -8.30762923e-01
5.91930509e-01 2.57759988e-01 9.08646882e-02 -6.24644160e-01
7.67840981e-01 -3.11283916e-01 2.04239771e-01 -8.34716618e-01
5.07608771e-01 -2.57971138e-01 -9.18264166e-02 5.39756119e-01
2.20336750e-01 3.74505520e-01 1.30788192e-01 7.73711562e-01
1.15954792e+00 -8.43419194e-01 3.44249398e-01 -2.51891047e-01
5.10459006e-01 -4.48340535e-01 -1.79542769e-02 8.76362383e-01
-7.98730433e-01 1.04326420e-01 9.11121070e-01 -3.28733414e-01
-7.50438213e-01 -4.74774301e-01 -9.21676215e-03 1.76209128e+00
-3.31338614e-01 -5.33695340e-01 -9.99627948e-01 -1.36122465e+00
1.19096883e-01 1.18211412e+00 -9.74123418e-01 -3.25211436e-01
-6.23785853e-01 -7.36575305e-01 9.89350379e-01 4.54998821e-01
1.65336713e-01 -1.32147050e+00 2.01766133e-01 1.90958068e-01
-4.77940112e-01 -1.45022511e+00 -4.39570487e-01 1.50835767e-01
-3.44487697e-01 -1.08113861e+00 1.48976505e-01 -3.75800401e-01
-1.63476497e-01 2.79798359e-01 1.20058906e+00 5.54858446e-01
-1.51984662e-01 7.31701478e-02 -4.52943057e-01 -5.19061565e-01
-6.40224159e-01 5.49140036e-01 1.20485403e-01 -2.73881797e-02
9.32868779e-01 -6.40054047e-01 -1.37825429e-01 -1.29914269e-01
-8.02146852e-01 -8.40005040e-01 -1.43498480e-01 5.65666258e-01
-4.83740449e-01 -3.15117836e-01 8.72232139e-01 -1.10863137e+00
1.40126574e+00 -1.06298840e+00 1.87372103e-01 -2.31691092e-01
-2.85234720e-01 -2.78866976e-01 2.44922519e-01 -7.34270692e-01
-7.10071921e-01 -7.29228616e-01 -4.50157881e-01 -2.77819216e-01
-1.15544192e-01 5.31375825e-01 5.52941374e-02 5.17456979e-02
8.64872754e-01 -3.22074503e-01 -5.73704652e-02 -4.38866764e-01
4.81977016e-01 1.16566133e+00 5.63991778e-02 3.18239592e-02
5.94567001e-01 3.44763547e-01 -5.13373494e-01 -1.26105022e+00
-1.34304428e+00 -6.61697328e-01 -5.52334487e-01 -2.42198721e-01
9.60820794e-01 -7.07468331e-01 -6.52595282e-01 2.71499544e-01
-1.32044125e+00 -1.37000427e-01 4.92648222e-02 -6.95175007e-02
-5.38533218e-02 7.29946494e-01 -1.25817776e+00 -9.06711817e-01
-6.94813728e-01 -6.18395150e-01 5.96808493e-01 -3.36229563e-01
-8.83903861e-01 -1.26029873e+00 2.09213912e-01 8.72011960e-01
4.34622586e-01 -1.72264859e-01 1.00917399e+00 -1.76369786e+00
4.00416285e-01 -3.08292300e-01 -1.95208475e-01 2.38598689e-01
-4.16796088e-01 -4.57520895e-02 -1.09059489e+00 4.68192883e-02
-1.81197226e-01 -4.59639758e-01 1.10994172e+00 -1.03229865e-01
1.20526075e+00 -6.31188035e-01 -3.52017462e-01 -4.75138314e-02
8.33364308e-01 -1.12469025e-01 4.25008923e-01 4.11922753e-01
7.71811783e-01 7.64983535e-01 1.17781565e-01 4.52796727e-01
2.71134228e-02 5.70002139e-01 6.04814470e-01 4.02921289e-01
-6.13886379e-02 -3.22405189e-01 3.47068310e-01 6.69349313e-01
4.88005131e-01 -7.79968858e-01 -1.05171001e+00 8.10775161e-01
-1.58702505e+00 -1.29658186e+00 -1.74955085e-01 1.20256400e+00
8.74709427e-01 3.91690016e-01 3.92172515e-01 3.29365075e-01
9.39635873e-01 6.92307591e-01 -2.71360785e-01 -9.18042362e-01
1.15133598e-01 1.68769211e-01 3.27056944e-01 8.30167174e-01
-1.53019226e+00 1.40757346e+00 7.61095095e+00 1.05349231e+00
-7.58102059e-01 6.35840893e-01 5.18226206e-01 -6.02772653e-01
-1.22447692e-01 -8.42392862e-01 -8.37414265e-01 6.08567178e-01
1.35502267e+00 8.89311060e-02 4.80859280e-01 1.00585473e+00
6.83999956e-02 4.76520866e-01 -6.28950000e-01 6.93921745e-01
7.88935244e-01 -1.13974524e+00 7.24413842e-02 1.88041672e-01
4.01166737e-01 3.96888226e-01 1.08764386e-02 3.75838071e-01
4.26573455e-01 -9.65874195e-01 6.26260102e-01 -2.80011259e-02
2.15629205e-01 -9.61239338e-01 8.71310711e-01 2.62582034e-01
-2.05071121e-01 -3.66538495e-01 -2.30362564e-01 -2.55487889e-01
2.03646272e-01 5.54162562e-01 -8.93735945e-01 -1.17596425e-01
7.42314875e-01 6.95237577e-01 -5.84203005e-01 3.43245208e-01
-7.11136699e-01 9.77425218e-01 -1.65141150e-01 -6.62544608e-01
4.76055443e-01 3.63259196e-01 9.34755862e-01 1.69415450e+00
-4.80890453e-01 1.96653157e-01 4.03740481e-02 6.87032998e-01
-7.15157330e-01 3.72118682e-01 -8.71039450e-01 -4.42647815e-01
4.76938426e-01 1.21927118e+00 -4.01350081e-01 -3.16380143e-01
-3.48403811e-01 8.77107143e-01 1.07623589e+00 1.55288994e-01
-6.94290936e-01 -3.46217602e-01 1.10258448e+00 2.07278907e-01
3.84152681e-01 -1.41351193e-01 -1.89932317e-01 -9.52926815e-01
-2.49278605e-01 -8.95438373e-01 5.59645593e-01 -5.58137894e-01
-1.79193318e+00 6.53817415e-01 -2.32921243e-02 -1.53185353e-01
-2.90675163e-01 -6.47797942e-01 -6.66017830e-01 3.56029212e-01
-1.14398468e+00 -9.17764008e-01 3.90883610e-02 4.34497237e-01
6.96822464e-01 -2.00993404e-01 6.37973130e-01 3.10293704e-01
-9.28574443e-01 7.44350731e-01 -1.13947116e-01 6.02595150e-01
5.79099238e-01 -8.92253995e-01 6.51604056e-01 7.63037741e-01
2.76344657e-01 6.04535460e-01 7.52822697e-01 -9.29085672e-01
-7.25200593e-01 -8.59451294e-01 1.18622434e+00 -7.16379702e-01
1.53855371e+00 -6.87764287e-01 -1.04378128e+00 9.27433550e-01
5.82116783e-01 -3.91914546e-01 1.11182892e+00 6.54033124e-01
-8.98472726e-01 4.52282846e-01 -1.12775290e+00 7.36737490e-01
1.36945641e+00 -9.64468062e-01 -9.29371774e-01 6.26177192e-01
1.01203156e+00 1.01724848e-01 -4.87100720e-01 -1.13780074e-01
2.81108469e-01 -6.48934543e-01 1.01521373e+00 -1.41758370e+00
7.89155245e-01 7.66728520e-01 -6.67871535e-02 -1.48314369e+00
-6.15480602e-01 -6.38504505e-01 -5.22200465e-01 1.27387762e+00
6.08576834e-01 -2.81434417e-01 6.12331867e-01 4.91288245e-01
1.38634086e-01 -5.71442723e-01 -1.18847561e+00 -4.80316669e-01
4.36003953e-01 -6.99677289e-01 -1.99982361e-03 1.37767529e+00
6.61361217e-01 9.06483889e-01 -5.03175914e-01 -9.62331593e-02
2.06432506e-01 -7.38137722e-01 2.08022699e-01 -1.29819000e+00
9.05007124e-03 -6.68898106e-01 -4.89565849e-01 -5.70420802e-01
1.08749032e+00 -8.41614425e-01 -3.03595811e-01 -1.14360464e+00
3.24955046e-01 4.85831797e-01 -2.23682150e-01 4.36954200e-01
-4.60016429e-01 6.33264005e-01 2.46959493e-01 -1.88854799e-01
-8.98787439e-01 5.22771835e-01 5.66150963e-01 -3.69887710e-01
1.19594149e-02 -5.25587440e-01 -1.02328312e+00 8.52292061e-01
9.74254906e-01 -7.74033368e-01 -8.66596922e-02 -3.01200986e-01
3.16432357e-01 -5.37160456e-01 2.70162970e-01 -4.76493418e-01
-5.53667061e-02 1.49903387e-01 -1.31713241e-01 -3.86808544e-01
5.56445599e-01 -5.25712132e-01 -9.35711682e-01 2.55302608e-01
-8.68788302e-01 -1.89951301e-01 1.33041427e-01 8.28490734e-01
6.94232434e-02 -5.83058536e-01 8.25962126e-01 -1.06593706e-01
-2.80521989e-01 1.67425647e-01 -1.01358533e+00 6.72683954e-01
6.67469978e-01 3.49686086e-01 -5.10893166e-01 -1.02796805e+00
-9.80694592e-01 -1.09967932e-01 -2.75413185e-01 9.03606892e-01
4.85721678e-01 -9.73553598e-01 -7.14351952e-01 -3.61777060e-02
1.74670145e-01 -1.00318158e+00 1.95797645e-02 5.37931263e-01
-3.05015206e-01 3.92913133e-01 2.45458290e-01 1.58127189e-01
-1.62063265e+00 9.49661851e-01 3.81951541e-01 -3.29278260e-01
-3.50668818e-01 9.99197483e-01 -2.50599712e-01 -1.58990636e-01
5.05631268e-01 2.06560194e-01 -6.76847517e-01 4.00593609e-01
9.07713830e-01 4.76471901e-01 6.13374822e-02 -8.62259924e-01
-4.68082100e-01 -1.69270024e-01 -5.02395213e-01 -2.30944052e-01
1.33888578e+00 -2.83317715e-01 -1.92774221e-01 4.54940617e-01
1.51706505e+00 2.12876081e-01 -2.39022583e-01 -4.28944767e-01
3.14573824e-01 -3.30088884e-01 4.71332848e-01 -9.07544494e-01
-8.97318721e-01 9.19975698e-01 1.08401306e-01 7.33378053e-01
3.29856426e-01 1.66916162e-01 9.07940686e-01 6.78113103e-01
-2.89681286e-01 -1.19381940e+00 3.80245000e-01 9.63239968e-01
1.04935968e+00 -1.17218709e+00 7.27945268e-02 -7.60753930e-01
-6.89919233e-01 8.94130826e-01 6.24926865e-01 -2.25427896e-01
1.01102018e+00 1.52462170e-01 2.03582600e-01 -6.04030788e-01
-7.37846971e-01 -1.77261189e-01 2.31626734e-01 3.82697552e-01
5.17816544e-01 -2.25400805e-01 -4.81279641e-01 7.07889795e-01
-3.42755765e-01 -7.06823409e-01 4.68629509e-01 5.74209690e-01
-5.48354447e-01 -6.97333336e-01 -3.02653629e-02 4.55870658e-01
-1.29942632e+00 -6.22493744e-01 -1.40422976e+00 9.10024285e-01
-4.19964761e-01 1.34548044e+00 1.18471794e-01 -5.22944808e-01
2.15855822e-01 6.73532367e-01 -1.70471624e-01 -6.03593588e-01
-1.30015206e+00 -1.53605446e-01 9.64983106e-01 -6.96031034e-01
-7.97404796e-02 -6.31264091e-01 -7.91095436e-01 -5.61892986e-01
-5.01301885e-01 1.94410253e-02 5.80640435e-01 1.14689684e+00
5.05765319e-01 4.59884226e-01 4.01189476e-01 -4.34444338e-01
-7.24448264e-01 -1.60237753e+00 -3.35642219e-01 8.85704637e-01
3.16398591e-01 -6.28523290e-01 -8.21931839e-01 -6.55220091e-01] | [8.801804542541504, 10.560930252075195] |
66ae6221-cd66-408e-8eca-25c0c89e0dda | pava-a-novel-path-based-valley-seeking | 2306.07503 | null | https://arxiv.org/abs/2306.07503v1 | https://arxiv.org/pdf/2306.07503v1.pdf | PaVa: a novel Path-based Valley-seeking clustering algorithm | Clustering methods are being applied to a wider range of scenarios involving more complex datasets, where the shapes of clusters tend to be arbitrary. In this paper, we propose a novel Path-based Valley-seeking clustering algorithm for arbitrarily shaped clusters. This work aims to seek the valleys among clusters and then individually extract clusters. Three vital techniques are used in this algorithm. First, path distance (minmax distance) is employed to transform the irregular boundaries among clusters, that is density valleys, into perfect spherical shells. Second, a suitable density measurement, $k$-distance, is employed to make adjustment on Minimum Spanning Tree, by which a robust minmax distance is calculated. Third, we seek the transformed density valleys by determining their centers and radius. First, the clusters are wrapped in spherical shells after the distance transformation, making the extraction process efficient even with clusters of arbitrary shape. Second, adjusted Minimum Spanning Tree enhances the robustness of minmax distance under different kinds of noise. Last, the number of clusters does not need to be inputted or decided manually due to the individual extraction process. After applying the proposed algorithm to several commonly used synthetic datasets, the results indicate that the Path-based Valley-seeking algorithm is accurate and efficient. The algorithm is based on the dissimilarity of objects, so it can be applied to a wide range of fields. Its performance on real-world datasets illustrates its versatility. | ['Shuangzhe Liu', 'Tiefeng Ma', 'Conan Liu', 'Lin Ma'] | 2023-06-13 | null | null | null | null | ['clustering'] | ['methodology'] | [-2.98331175e-02 -4.00200844e-01 3.54847498e-02 -2.15936497e-01
-3.07910144e-01 -6.57878041e-01 3.87203246e-01 3.32103580e-01
-3.89658928e-01 2.80274481e-01 -2.15764835e-01 -1.24910243e-01
-6.49761617e-01 -9.49370384e-01 -1.91045895e-01 -1.02979398e+00
-2.17063591e-01 6.11401498e-01 5.46048224e-01 1.92890745e-02
6.31737530e-01 6.73594832e-01 -1.55957496e+00 -2.73780644e-01
1.27608812e+00 8.00455928e-01 2.76184916e-01 2.02655375e-01
-3.16363156e-01 -5.08263782e-02 -6.25857413e-01 -5.01284637e-02
3.93554986e-01 -3.77021223e-01 -4.83450055e-01 4.77091700e-01
-6.10441387e-01 2.56500632e-01 3.13365668e-01 1.04370761e+00
3.24457914e-01 1.98904634e-01 1.05156505e+00 -1.24243116e+00
-3.24157208e-01 3.24614733e-01 -1.16745663e+00 -2.10475158e-02
-4.80403565e-02 5.88422269e-03 5.97311437e-01 -9.32227075e-01
2.93219864e-01 1.15212941e+00 5.80169976e-01 -4.52116504e-02
-1.04127395e+00 -5.79900920e-01 -2.00367689e-01 1.64464861e-01
-2.16431022e+00 -1.26448184e-01 1.00457716e+00 -4.84150141e-01
3.64706784e-01 3.99681509e-01 5.20900905e-01 1.06390692e-01
1.25740945e-01 3.31566691e-01 9.66365159e-01 -4.28744197e-01
4.79961663e-01 3.43503892e-01 -6.39625415e-02 3.13400179e-01
6.71578050e-01 -4.55289990e-01 1.37615144e-01 -1.96637228e-01
5.73719084e-01 5.86662963e-02 -2.25950226e-01 -7.98503995e-01
-1.19811118e+00 9.07360733e-01 4.79405016e-01 6.52427554e-01
-2.36796275e-01 -3.75735134e-01 2.01317042e-01 -2.46041447e-01
9.12085697e-02 2.77186334e-01 -9.84554365e-02 1.43862236e-02
-1.16956294e+00 -7.35714361e-02 4.02708501e-01 9.02101219e-01
9.21180487e-01 -2.81375587e-01 1.52188614e-01 8.82744789e-01
5.20879686e-01 4.83787566e-01 4.95337069e-01 -6.86426759e-01
4.44882154e-01 1.03736126e+00 1.68761909e-01 -1.68149567e+00
-4.60143566e-01 -1.74735546e-01 -1.30948186e+00 8.69055614e-02
5.09556890e-01 -2.42282320e-02 -7.53316760e-01 1.33860362e+00
6.71572268e-01 -8.38880166e-02 6.73777908e-02 7.47304201e-01
4.87724870e-01 7.85301983e-01 -1.78072900e-01 -6.59907460e-01
1.32099128e+00 -3.81994069e-01 -6.38332129e-01 1.70692638e-01
4.02960718e-01 -8.08412492e-01 8.60439181e-01 4.87700671e-01
-8.34866464e-01 -5.03890514e-01 -9.95445728e-01 5.57373762e-01
-3.34730774e-01 2.08904177e-01 3.13251704e-01 6.72149062e-01
-9.00554657e-01 2.69758224e-01 -7.36796677e-01 -4.59261805e-01
1.62250534e-01 4.18106198e-01 -3.64608429e-02 2.01564431e-01
-8.67858589e-01 4.27047342e-01 7.50369966e-01 3.12541693e-01
2.70620314e-03 -1.75918713e-01 -6.01760507e-01 7.18645453e-02
2.35422879e-01 -3.59023213e-01 4.16594744e-01 -5.67253411e-01
-9.90863919e-01 5.26294351e-01 -3.68028820e-01 6.95498809e-02
5.69095731e-01 5.24784267e-01 -4.96088922e-01 3.35205615e-01
3.39083105e-01 2.14537591e-01 7.87188172e-01 -1.51885641e+00
-5.81135213e-01 -4.78712320e-01 -6.60958052e-01 3.52254003e-01
-4.96137977e-01 -1.23525374e-01 -6.71787679e-01 -4.80364412e-01
7.48290420e-01 -7.96507478e-01 -5.43509781e-01 -3.69382054e-01
-5.66944420e-01 -4.87212926e-01 1.13182485e+00 -2.81287909e-01
1.73119283e+00 -2.36226034e+00 -5.30757755e-02 1.07958031e+00
2.63105929e-01 3.95065174e-02 4.14214969e-01 4.45354044e-01
9.94297490e-02 2.80925125e-01 -8.39572728e-01 7.38089308e-02
-2.01423049e-01 -1.20086856e-02 2.57260293e-01 4.73305255e-01
1.79717273e-01 2.93948591e-01 -6.92816198e-01 -1.03631330e+00
3.38200033e-01 4.10145581e-01 -3.14335972e-01 -2.13836044e-01
3.08276236e-01 3.22680563e-01 -6.95712328e-01 5.59366763e-01
1.09591103e+00 -6.66037574e-02 2.90438794e-02 -1.83177724e-01
-3.71084958e-01 -6.02307379e-01 -1.86765480e+00 1.08126616e+00
1.50950432e-01 2.10641146e-01 1.05450362e-01 -1.06489968e+00
1.69068944e+00 9.74836722e-02 9.22376335e-01 -3.32029551e-01
2.85317779e-01 4.16156292e-01 1.13705441e-01 -3.40172857e-01
4.88776177e-01 -1.05725862e-01 -2.09723815e-01 4.40509677e-01
-5.81925750e-01 -3.73437077e-01 5.81303716e-01 1.42647550e-01
6.76446557e-01 -4.19121146e-01 2.06544980e-01 -6.26118004e-01
8.43292475e-01 1.77989975e-01 6.85413659e-01 2.13320419e-01
-1.68818161e-01 6.32426560e-01 2.73235381e-01 -1.93590805e-01
-1.02126563e+00 -1.12487447e+00 -5.00513971e-01 3.45705688e-01
6.55174196e-01 -1.86546192e-01 -7.95256495e-01 -3.55254740e-01
-4.43947725e-02 3.25932503e-01 -4.25616860e-01 -1.32348105e-01
-5.43206871e-01 -1.16463995e+00 1.50441200e-01 1.91997334e-01
6.57929838e-01 -1.01591372e+00 -7.09016263e-01 2.38740921e-01
-2.51689613e-01 -6.24681592e-01 -3.68411243e-01 -6.48366064e-02
-1.05358219e+00 -1.20558226e+00 -6.80159628e-01 -9.30271506e-01
9.40956831e-01 3.85983646e-01 6.92842066e-01 2.77254492e-01
-2.66294509e-01 5.97704493e-04 -4.28882599e-01 -1.50426224e-01
-1.39540762e-01 2.80799940e-02 2.17087299e-01 3.34370643e-01
6.56346023e-01 -5.72389543e-01 -7.23513603e-01 8.77483308e-01
-8.62166047e-01 -4.92146164e-01 6.24970317e-01 3.50211173e-01
7.74394929e-01 1.07790446e+00 6.93765759e-01 -3.50258678e-01
8.76382470e-01 -5.35450161e-01 -5.35377026e-01 6.11522347e-02
-5.98409355e-01 -4.36557420e-02 8.64127040e-01 -3.54421556e-01
-8.92336547e-01 7.92648420e-02 2.31600016e-01 -2.02943996e-01
-1.27477303e-01 2.63030618e-01 -3.17299277e-01 1.66072637e-01
6.36382282e-01 3.89122099e-01 1.28621817e-01 -2.39630774e-01
2.69276053e-01 1.01662874e+00 4.27678049e-01 -3.60787481e-01
1.09205079e+00 6.60135567e-01 1.39119491e-01 -9.48359132e-01
2.76058204e-02 -7.72913754e-01 -9.18521941e-01 -2.93975174e-01
8.67543519e-01 -3.75614047e-01 -8.67621124e-01 3.63927752e-01
-6.54190242e-01 2.09553435e-01 -6.24959096e-02 5.54697871e-01
-3.90637785e-01 7.20287681e-01 -1.90381929e-01 -1.12459528e+00
-3.65976036e-01 -1.02141762e+00 6.18170857e-01 6.13663077e-01
-1.89315155e-01 -9.60773230e-01 -6.78886026e-02 -4.31378372e-02
1.35286018e-01 4.85871971e-01 8.46672237e-01 -4.71726149e-01
-4.38991278e-01 -1.13275789e-01 -2.00383887e-01 -7.77688846e-02
4.72172260e-01 6.25189543e-01 -2.76502550e-01 -4.16585982e-01
5.77480532e-02 2.98722327e-01 5.24906695e-01 4.89004046e-01
1.02623975e+00 -1.83446780e-01 -7.38549292e-01 5.07458806e-01
1.46530390e+00 8.59576344e-01 6.39029443e-01 5.06584823e-01
6.10532761e-01 6.94365680e-01 9.04043019e-01 5.85389137e-01
3.28796327e-01 3.62339973e-01 3.05829793e-01 -3.35818619e-01
4.11734104e-01 1.28111333e-01 -9.59566906e-02 1.02239347e+00
-5.79137839e-02 -7.92618766e-02 -1.04582524e+00 8.49153519e-01
-1.73214364e+00 -9.25327897e-01 -5.70947111e-01 2.31667233e+00
7.33668447e-01 2.13066399e-01 3.51008832e-01 7.18555212e-01
1.15341091e+00 -1.56728134e-01 -5.73031127e-01 -5.21021366e-01
4.91131693e-02 -9.96280387e-02 3.20375621e-01 3.07872415e-01
-9.41600084e-01 6.30040407e-01 5.40870667e+00 1.06293583e+00
-1.01055455e+00 -4.12614107e-01 5.11448324e-01 3.41877103e-01
-1.54381320e-01 -2.46957801e-02 -6.38050199e-01 7.92787433e-01
3.29178721e-01 -3.30902368e-01 8.52769166e-02 6.21903896e-01
4.28991497e-01 -4.26432997e-01 -4.60853815e-01 9.39798355e-01
-2.98570901e-01 -6.88810945e-01 -8.78078789e-02 5.65537848e-02
6.11499906e-01 -5.32172263e-01 3.92628461e-02 -2.24815831e-01
2.95246422e-01 -9.48424459e-01 3.32906365e-01 5.36961496e-01
6.69698358e-01 -1.30735612e+00 6.87557101e-01 5.43335199e-01
-1.71469629e+00 -1.13993384e-01 -5.62791288e-01 2.04032868e-01
1.94603741e-01 9.91497397e-01 -9.85981405e-01 7.82119036e-01
9.16939378e-01 4.13860619e-01 -6.13868237e-01 1.31335855e+00
2.92961240e-01 2.05495030e-01 -7.98450232e-01 -3.44785571e-01
2.50756204e-01 -8.99693966e-01 3.86769444e-01 1.22428679e+00
6.71399593e-01 1.90656245e-01 9.17850621e-03 9.22834754e-01
4.66487616e-01 5.07634461e-01 -5.43896616e-01 2.24435538e-01
1.01321805e+00 1.37410283e+00 -1.42421782e+00 -2.18298152e-01
3.72234099e-02 4.95630950e-01 -1.10688932e-01 2.16446027e-01
-7.45237172e-01 -9.00017440e-01 3.09318364e-01 2.44875997e-01
2.89126277e-01 -3.77659857e-01 -5.74940264e-01 -5.31677008e-01
6.69393763e-02 -5.12853026e-01 4.35799897e-01 -5.46328068e-01
-1.17854393e+00 6.06262267e-01 1.79984406e-01 -1.53568149e+00
-9.92980972e-03 -2.27243423e-01 -9.63010669e-01 6.16913795e-01
-1.02177382e+00 -4.88033026e-01 -4.54537809e-01 9.20635045e-01
3.05730522e-01 -1.41953435e-02 3.84718329e-01 1.98827192e-01
-5.78989327e-01 3.68155688e-01 4.71961617e-01 1.15893058e-01
4.95343655e-01 -1.08080542e+00 -7.21628144e-02 8.84737790e-01
-1.71445072e-01 7.23452091e-01 6.43905699e-01 -7.27028549e-01
-8.65820587e-01 -9.17704463e-01 6.98750615e-01 -2.75876492e-01
4.61981952e-01 -4.13073182e-01 -1.00189674e+00 2.88120806e-02
-4.82197143e-02 -3.44594151e-01 4.78541762e-01 -3.59284878e-01
1.94644690e-01 -2.06652418e-01 -1.40246594e+00 5.32218397e-01
5.95681906e-01 1.80530757e-01 -4.14576560e-01 5.87280691e-02
3.20267916e-01 1.21237233e-01 -1.08895695e+00 6.55494750e-01
3.26643229e-01 -1.09120941e+00 9.52079713e-01 1.66015685e-01
1.21384256e-01 -1.03221059e+00 2.50989199e-01 -1.13044059e+00
-4.66421127e-01 -3.96289319e-01 3.81331831e-01 1.42463410e+00
4.30339515e-01 -7.02649593e-01 6.32981777e-01 3.58149141e-01
1.16459899e-01 -7.64582276e-01 -9.45485115e-01 -6.37258589e-01
-6.89169392e-02 -9.96005721e-04 7.29568422e-01 1.29706800e+00
1.20401546e-01 1.62572131e-01 1.38856024e-01 1.75343290e-01
8.31578195e-01 1.32424146e-01 8.37563455e-01 -1.62648010e+00
1.16749041e-01 -5.64570248e-01 -2.81639606e-01 -7.00120032e-01
-6.48201108e-01 -5.75282812e-01 3.19428779e-02 -1.65924561e+00
2.83963848e-02 -1.12110412e+00 -4.72897291e-03 1.64929420e-01
-1.99267030e-01 2.71219373e-01 6.59842938e-02 5.96023381e-01
-4.03274000e-01 5.00114977e-01 1.30223501e+00 2.92309150e-02
-7.15101182e-01 2.05034643e-01 -6.85950041e-01 8.37544560e-01
1.06249118e+00 -3.64231050e-01 -5.55110574e-01 1.59042269e-01
-5.63995354e-02 -2.13140175e-01 -2.32752800e-01 -1.02661479e+00
3.14093083e-01 -1.81167707e-01 3.97601843e-01 -9.84284401e-01
4.43663262e-02 -1.17776906e+00 3.53956163e-01 4.90973979e-01
4.40503836e-01 2.50314325e-01 2.90710218e-02 4.24861223e-01
-1.13570511e-01 -2.91901261e-01 9.19176161e-01 5.05009200e-03
-4.08333063e-01 9.16690528e-02 -3.83958042e-01 -8.47962797e-02
1.67291963e+00 -1.02104175e+00 1.23420022e-01 -1.49741724e-01
-6.47391737e-01 4.11514133e-01 6.64868474e-01 1.46943569e-01
5.39788544e-01 -1.46907043e+00 -5.67124724e-01 3.28749537e-01
3.14245299e-02 5.13946354e-01 1.16341442e-01 9.87702787e-01
-6.61996245e-01 6.08606376e-02 1.00523392e-02 -1.12031901e+00
-1.18948734e+00 8.31485450e-01 5.92147820e-02 -9.06253792e-03
-4.58877832e-01 4.36925143e-01 -9.55344737e-03 -2.93189257e-01
-6.05375506e-02 -2.68825859e-01 -5.51844537e-01 2.80421108e-01
2.22021818e-01 5.03585458e-01 -1.56491622e-01 -8.68627787e-01
-5.60037911e-01 1.24696147e+00 3.40571880e-01 8.71197283e-02
1.20047367e+00 -3.92541230e-01 -2.97194839e-01 3.46485823e-01
1.03006053e+00 2.09381983e-01 -1.06465864e+00 8.55858773e-02
1.91542149e-01 -5.48830152e-01 -4.78997976e-01 -1.40535310e-01
-1.04798412e+00 6.30019546e-01 4.27816808e-01 7.20725656e-01
1.35670316e+00 -8.80813301e-02 5.62926710e-01 1.33273974e-02
2.96942949e-01 -1.34571576e+00 -5.34473620e-02 9.64876562e-02
4.30139214e-01 -8.92481446e-01 -3.88028026e-02 -6.09171629e-01
-6.49257839e-01 1.00728476e+00 5.37396908e-01 -1.26188159e-01
7.09587038e-01 2.81536222e-01 -9.79288593e-02 -1.28387183e-01
-1.50098503e-02 -1.58662662e-01 9.36555862e-02 7.06901133e-01
1.45788833e-01 4.32200059e-02 -7.88107574e-01 4.26562995e-01
-5.09059131e-01 -3.70580196e-01 5.88720620e-01 7.19181418e-01
-9.04977798e-01 -8.21668029e-01 -9.54466939e-01 3.64847392e-01
-8.12779218e-02 2.59045213e-01 -4.13839668e-01 9.98977423e-01
3.41470361e-01 1.27140653e+00 3.66930515e-01 -3.06375057e-01
2.79210299e-01 -2.52290159e-01 -2.94155255e-02 -1.01339363e-01
-2.07353905e-01 3.07689399e-01 -4.66313422e-01 -1.34062558e-01
-4.81285214e-01 -6.04354382e-01 -1.75070238e+00 -3.80554080e-01
-6.36537492e-01 7.54389048e-01 4.82817650e-01 6.53473318e-01
2.25604683e-01 1.82949722e-01 1.09107363e+00 -5.42061031e-01
-5.38686328e-02 -6.47712529e-01 -8.65711868e-01 3.92010927e-01
-1.35355636e-01 -8.43801200e-01 -5.71046650e-01 4.04173918e-02] | [7.590150833129883, 4.59266996383667] |
a527b048-a1e5-4144-b9c9-355614667ba2 | semantic-graph-convolutional-networks-for-3d | 1904.03345 | null | https://arxiv.org/abs/1904.03345v3 | https://arxiv.org/pdf/1904.03345v3.pdf | Semantic Graph Convolutional Networks for 3D Human Pose Regression | In this paper, we study the problem of learning Graph Convolutional Networks (GCNs) for regression. Current architectures of GCNs are limited to the small receptive field of convolution filters and shared transformation matrix for each node. To address these limitations, we propose Semantic Graph Convolutional Networks (SemGCN), a novel neural network architecture that operates on regression tasks with graph-structured data. SemGCN learns to capture semantic information such as local and global node relationships, which is not explicitly represented in the graph. These semantic relationships can be learned through end-to-end training from the ground truth without additional supervision or hand-crafted rules. We further investigate applying SemGCN to 3D human pose regression. Our formulation is intuitive and sufficient since both 2D and 3D human poses can be represented as a structured graph encoding the relationships between joints in the skeleton of a human body. We carry out comprehensive studies to validate our method. The results prove that SemGCN outperforms state of the art while using 90% fewer parameters. | ['Long Zhao', 'Xi Peng', 'Dimitris N. Metaxas', 'Yu Tian', 'Mubbasir Kapadia'] | 2019-04-06 | semantic-graph-convolutional-networks-for-3d-1 | http://openaccess.thecvf.com/content_CVPR_2019/html/Zhao_Semantic_Graph_Convolutional_Networks_for_3D_Human_Pose_Regression_CVPR_2019_paper.html | http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhao_Semantic_Graph_Convolutional_Networks_for_3D_Human_Pose_Regression_CVPR_2019_paper.pdf | cvpr-2019-6 | ['monocular-3d-human-pose-estimation'] | ['computer-vision'] | [ 4.98650745e-02 5.81749678e-01 -2.73793727e-01 -4.63736713e-01
1.56879917e-01 -8.20981711e-02 3.11879128e-01 -1.62292585e-01
-3.15721840e-01 5.23156226e-01 9.14253592e-02 -2.19504349e-02
-1.70881912e-01 -9.70827103e-01 -9.68975425e-01 -2.41886690e-01
-3.53091508e-01 6.05852067e-01 6.54672608e-02 -5.32517731e-01
-2.47162819e-01 4.42846417e-01 -1.11315525e+00 4.65211924e-03
5.07156014e-01 8.04953158e-01 5.25784045e-02 7.51539230e-01
2.06009611e-01 9.54733908e-01 -4.78430837e-01 -3.14278990e-01
2.27823839e-01 -5.12544811e-01 -7.81526864e-01 -5.11668250e-02
5.06408691e-01 -1.00921594e-01 -8.14918280e-01 9.21960652e-01
3.35446000e-01 2.97094464e-01 5.84062874e-01 -1.45812726e+00
-8.68653953e-01 3.83113593e-01 -2.55617470e-01 -1.34463713e-01
2.77532518e-01 -2.94509232e-02 1.22967029e+00 -4.61267948e-01
8.21351707e-01 1.41745448e+00 8.87289226e-01 8.38514388e-01
-1.16136551e+00 -4.92147774e-01 3.75321954e-01 -1.98691748e-02
-1.32737041e+00 4.17870283e-02 9.18721318e-01 -3.36988449e-01
1.18094718e+00 -5.60795180e-02 9.29534495e-01 1.23382831e+00
4.64968264e-01 4.85427201e-01 4.46934909e-01 -3.18150491e-01
-1.03724403e-02 -5.92945397e-01 9.21258517e-03 1.40361583e+00
4.32060033e-01 1.39885977e-01 -7.13961780e-01 1.66450024e-01
1.35227466e+00 -1.81616377e-02 -1.35488525e-01 -8.52406323e-01
-1.06646740e+00 1.04988539e+00 1.18386209e+00 -8.77905115e-02
-5.35618365e-02 9.38272297e-01 3.48484606e-01 3.79172593e-01
4.52174723e-01 2.83626497e-01 -4.93781418e-01 4.33199644e-01
-3.41623247e-01 2.25901335e-01 9.22288835e-01 9.49269414e-01
8.95868421e-01 2.31537730e-01 1.50860464e-02 6.54205620e-01
5.23377001e-01 4.51647490e-01 2.80366719e-01 -9.27807212e-01
4.78547305e-01 7.83001065e-01 -3.95746768e-01 -1.54802501e+00
-6.96152806e-01 -5.50553441e-01 -9.72517252e-01 5.62529489e-02
2.38890439e-01 -1.21314235e-01 -1.32551551e+00 1.93759084e+00
8.31083059e-02 1.67849407e-01 -1.46741509e-01 1.22399616e+00
1.27476394e+00 1.85424805e-01 1.87859446e-01 5.18455863e-01
1.07378185e+00 -1.15927231e+00 -6.24854684e-01 -5.67926288e-01
7.18961298e-01 -1.99321955e-02 8.28612328e-01 -1.06329218e-01
-7.70100296e-01 -6.53737068e-01 -1.14659631e+00 -3.09329361e-01
-3.39609563e-01 1.03922889e-01 9.59244013e-01 1.56557143e-01
-1.19232321e+00 8.77354205e-01 -1.22378337e+00 -5.74697018e-01
3.40223312e-01 6.72706842e-01 -6.74779594e-01 3.96580957e-02
-1.31464350e+00 9.57240760e-01 2.78646439e-01 5.04881740e-01
-1.04567957e+00 -1.72233731e-01 -1.41363239e+00 -1.45753756e-01
5.02770543e-01 -1.19541812e+00 9.81445014e-01 -8.82457554e-01
-1.32015324e+00 1.05039871e+00 2.25672781e-01 -5.85341334e-01
2.46793941e-01 -3.38706762e-01 -1.80111319e-01 1.81791946e-01
7.06823394e-02 7.73041785e-01 7.76847005e-01 -9.69010949e-01
7.20689297e-02 -5.19386351e-01 2.44180262e-01 8.28212276e-02
-7.81736802e-03 -3.53237092e-01 -6.76219404e-01 -8.46157253e-01
4.13600564e-01 -1.06007540e+00 -5.45455396e-01 1.56351939e-01
-6.63839102e-01 -1.96154818e-01 6.55803978e-01 -7.48666108e-01
8.89557838e-01 -1.85529006e+00 6.69911206e-01 4.61610198e-01
4.88661706e-01 -1.11551601e-02 -2.44765803e-01 1.99002340e-01
-3.39254066e-02 -7.57799223e-02 -2.10267305e-01 -1.41435698e-01
2.53365990e-02 7.60962069e-01 1.13613524e-01 5.97241759e-01
3.65759343e-01 1.41775167e+00 -9.70093012e-01 -4.25149947e-01
1.93070412e-01 6.07639492e-01 -5.95543623e-01 2.83184946e-01
-5.16889632e-01 5.71791232e-01 -7.21711934e-01 4.49252695e-01
2.42735103e-01 -5.52559018e-01 4.77562636e-01 -3.87163967e-01
7.38419652e-01 3.05614293e-01 -8.45043123e-01 2.30248117e+00
-3.10857296e-01 5.14530480e-01 -3.81803978e-03 -1.40864527e+00
1.19208884e+00 6.37547895e-02 4.51439410e-01 -6.20449841e-01
3.46903473e-01 -1.19586669e-01 -5.52031808e-02 -2.69097179e-01
8.17281455e-02 1.38657941e-02 -2.82391489e-01 3.67628992e-01
6.22952819e-01 -1.19209535e-01 -2.34988313e-02 3.09517294e-01
1.24406672e+00 5.86536646e-01 2.28138849e-01 -1.20058291e-01
3.74097973e-01 -2.91627403e-02 5.52773237e-01 6.62550330e-01
-5.44493422e-02 5.53173363e-01 5.64107299e-01 -8.03643286e-01
-7.24538386e-01 -1.09775746e+00 6.24915302e-01 1.08938682e+00
2.34082565e-01 -7.62290537e-01 -7.60501981e-01 -8.41400445e-01
1.47843435e-01 2.06801340e-01 -9.50644195e-01 -4.92326885e-01
-8.76835406e-01 -3.48888636e-01 5.35514653e-01 8.56555164e-01
5.84479213e-01 -1.17406046e+00 -6.34744406e-01 1.88774943e-01
-4.38581221e-02 -1.40360057e+00 -2.41514295e-01 2.31397167e-01
-1.08115304e+00 -1.45348394e+00 -2.99791455e-01 -9.67842519e-01
8.45934391e-01 -6.99564219e-02 1.44343591e+00 4.64765042e-01
-4.45320815e-01 6.04982376e-01 -2.00659096e-01 -1.62353694e-01
-1.70202732e-01 2.12851718e-01 -3.15278918e-01 -3.10375303e-01
2.05172524e-01 -6.70126677e-01 -4.54944074e-01 3.29942584e-01
-4.50501084e-01 2.52808809e-01 3.67046952e-01 8.92473280e-01
5.62603533e-01 -2.33015075e-01 1.64976373e-01 -1.02262497e+00
4.54936057e-01 -1.06412962e-01 -3.36995602e-01 1.29041895e-01
-2.36819878e-01 4.32264656e-01 4.73519862e-01 -2.08493367e-01
-6.38384283e-01 2.99354196e-01 2.59718895e-02 -6.78105116e-01
-2.00362690e-02 6.78032100e-01 -6.77442178e-04 -2.65495032e-01
7.38332808e-01 -2.50476778e-01 4.47968990e-01 -4.24899101e-01
5.83903134e-01 -4.77251448e-02 7.73505747e-01 -6.48811162e-01
8.09518456e-01 4.87374783e-01 5.15136361e-01 -5.00784695e-01
-1.06927121e+00 -1.26734033e-01 -9.41489697e-01 -2.86351085e-01
1.09556603e+00 -1.00373793e+00 -7.13711679e-01 2.35525012e-01
-9.71869409e-01 -7.14341283e-01 -1.29717126e-01 4.48767632e-01
-8.91431093e-01 2.12657228e-01 -9.06647980e-01 -2.98412979e-01
-2.69083202e-01 -7.70841300e-01 1.11726522e+00 -1.19548030e-01
-3.40399921e-01 -1.31890261e+00 -1.10955365e-01 2.01959953e-01
1.05770193e-01 7.79096365e-01 8.57152939e-01 -4.62192178e-01
-5.04754961e-01 -1.07723124e-01 -1.04044423e-01 3.52653503e-01
1.35287151e-01 -2.88935930e-01 -4.68418896e-01 -4.87185538e-01
-4.83417571e-01 -4.60754335e-01 1.03479433e+00 3.63408804e-01
1.23818755e+00 -3.45109329e-02 -4.39908087e-01 9.05067623e-01
1.23062336e+00 -4.41291153e-01 4.87236023e-01 3.39961588e-01
1.37844598e+00 6.55228615e-01 3.90552223e-01 8.81130621e-02
3.84597749e-01 6.38693333e-01 8.67816269e-01 -3.43692601e-01
-5.15585601e-01 -6.18507743e-01 1.74003601e-01 7.07011819e-01
-5.84506035e-01 -1.67766988e-01 -9.52248514e-01 2.63703704e-01
-2.14210677e+00 -3.94013703e-01 -9.73733589e-02 1.82627666e+00
4.04013813e-01 1.30658060e-01 -2.67895814e-02 -2.03121901e-01
7.98299253e-01 2.67105371e-01 -4.80525404e-01 -2.58456647e-01
9.16418955e-02 5.81979334e-01 5.32770038e-01 4.12545085e-01
-1.20694280e+00 1.31858540e+00 6.42452955e+00 2.46845976e-01
-1.00435948e+00 -1.06157459e-01 1.55939355e-01 1.54945642e-01
-1.28671288e-01 -2.78347936e-02 -4.20196742e-01 -1.77720428e-01
7.71354437e-01 1.88673139e-01 4.89644438e-01 6.65621519e-01
-1.90989241e-01 4.46188301e-01 -1.25534463e+00 9.73385394e-01
1.32322699e-01 -1.15232778e+00 1.76043421e-01 -1.41785160e-01
5.67899704e-01 9.20580849e-02 -1.85738519e-01 2.48965397e-01
7.77670681e-01 -1.40670562e+00 5.23251534e-01 5.42502999e-01
6.98728740e-01 -6.31215930e-01 5.40553510e-01 9.81345773e-02
-1.21688080e+00 1.92641407e-01 -5.18178821e-01 -2.29646951e-01
-9.27413329e-02 1.75634727e-01 -6.52771890e-01 7.99379170e-01
8.05402994e-01 1.29100406e+00 -5.63798010e-01 4.61509377e-01
-8.69073033e-01 4.36184496e-01 -2.17200339e-01 4.49575856e-02
3.20150793e-01 -1.70581833e-01 3.39698315e-01 9.04582441e-01
3.04382239e-02 -1.41813129e-01 3.04401845e-01 1.01854086e+00
-1.06393069e-01 -1.74612805e-01 -7.99916685e-01 -1.80654377e-01
-1.06036976e-01 9.61884737e-01 -7.85492897e-01 1.03294000e-03
-4.31873143e-01 1.07230115e+00 7.49904513e-01 6.56258345e-01
-8.20530772e-01 -2.36943558e-01 6.86413050e-01 4.09979001e-03
3.10324132e-01 -6.13862693e-01 -1.89917490e-01 -1.09877670e+00
-1.37461334e-01 -6.08003855e-01 6.55844390e-01 -8.45708072e-01
-1.27458429e+00 4.94389951e-01 -8.77956152e-02 -8.36970985e-01
-4.24978077e-01 -9.72026348e-01 -3.20080757e-01 6.68906331e-01
-1.12988186e+00 -1.39692318e+00 -6.46089256e-01 9.43219364e-01
6.37586936e-02 -1.84657350e-01 9.96066749e-01 -7.27412328e-02
-3.18185687e-01 4.90586907e-01 -6.14677787e-01 7.15359569e-01
4.59223032e-01 -1.11611342e+00 8.56832266e-01 5.84831715e-01
3.05644393e-01 6.70672417e-01 5.34809589e-01 -8.75312984e-01
-1.38756299e+00 -1.33591676e+00 7.85408795e-01 -3.33221376e-01
6.45657063e-01 -6.36162400e-01 -6.78604662e-01 1.20050454e+00
-2.69246340e-01 5.36126375e-01 3.77473235e-01 4.06150877e-01
-6.39943659e-01 1.44735975e-02 -7.64855683e-01 5.71805418e-01
1.72234833e+00 -6.28343821e-01 -5.65379560e-01 2.99483716e-01
9.40190315e-01 -8.24282169e-01 -8.21589410e-01 5.94635308e-01
5.06348968e-01 -6.60584152e-01 1.17943287e+00 -1.08837295e+00
5.39381921e-01 -2.90777206e-01 -1.19075894e-01 -1.41560483e+00
-2.30573267e-01 -3.00394595e-01 -2.66191959e-01 3.37792218e-01
2.83640027e-01 -5.25386393e-01 1.04585242e+00 2.40174428e-01
-2.74198860e-01 -6.80021584e-01 -6.76837981e-01 -7.63658345e-01
-1.32052794e-01 -3.45052302e-01 4.19644624e-01 9.51249242e-01
-3.38607758e-01 5.02639174e-01 -5.81902564e-01 1.27799392e-01
6.45282865e-01 7.23054707e-02 9.89231527e-01 -1.33425748e+00
-2.48322532e-01 1.35545731e-02 -1.03512275e+00 -9.24976707e-01
5.89938223e-01 -1.13816369e+00 4.94210012e-02 -1.85623634e+00
4.55023199e-02 -1.35260046e-01 -3.21133047e-01 8.62771094e-01
3.55679430e-02 3.80823851e-01 1.48585275e-01 -9.47962329e-02
-7.35130072e-01 6.33466303e-01 1.67163551e+00 -3.99200320e-01
-7.87345134e-03 -1.99743092e-01 -4.27001566e-01 7.41811335e-01
7.71580458e-01 -3.31875086e-01 -6.41505897e-01 -5.86338997e-01
4.24330354e-01 1.04434632e-01 9.22529399e-01 -9.60297942e-01
2.27712512e-01 4.46211249e-02 4.50860143e-01 -3.86790186e-01
2.67925143e-01 -8.33434045e-01 1.81822747e-01 6.22331679e-01
-3.78624946e-01 -2.46940795e-02 -4.52982746e-02 8.90379488e-01
-2.57928133e-01 2.66149670e-01 3.70295972e-01 -4.42125589e-01
-8.86279404e-01 5.82466185e-01 -1.32110133e-03 3.75043880e-03
6.97196782e-01 -2.35068768e-01 -5.65881506e-02 -5.52126527e-01
-1.29375780e+00 2.50524849e-01 3.18683177e-01 5.81672788e-01
7.97509134e-01 -1.44424307e+00 -4.18754220e-01 3.05814385e-01
1.25230432e-01 3.17024618e-01 -1.99559163e-02 5.26686311e-01
-8.18644404e-01 4.05328482e-01 -5.01973867e-01 -6.52712584e-01
-1.11305869e+00 4.58384097e-01 7.06897080e-01 -2.28388712e-01
-9.64028299e-01 8.98818552e-01 2.85288185e-01 -9.38970804e-01
3.09712976e-01 -4.24628556e-01 -1.61535934e-01 -6.10069215e-01
-2.82911807e-01 4.92346287e-02 -4.16153520e-02 -7.13663280e-01
-3.72976482e-01 6.79704905e-01 2.39451155e-01 3.26937675e-01
1.42899096e+00 2.56550103e-01 -2.32991055e-01 2.11505756e-01
1.17396939e+00 -6.13668919e-01 -1.24651837e+00 -3.17462146e-01
-4.65433933e-02 -2.23182291e-01 -6.02750964e-02 -6.10717177e-01
-1.48409700e+00 8.24354231e-01 2.42345333e-01 -2.77642369e-01
8.68238628e-01 2.41996735e-01 6.86233521e-01 6.46724701e-01
4.78935927e-01 -1.09086943e+00 4.75831389e-01 6.39452636e-01
1.05089927e+00 -1.03227150e+00 1.45764306e-01 -8.88689399e-01
-3.77444357e-01 1.18543601e+00 9.97849047e-01 -7.39827275e-01
7.52226114e-01 -9.86897573e-02 1.15749016e-02 -7.53956795e-01
-5.65378428e-01 -3.88780802e-01 5.90581119e-01 8.87881994e-01
4.96777773e-01 2.29743928e-01 -1.20489411e-01 3.85733426e-01
-3.46267968e-01 -1.87667832e-01 -2.85008494e-02 9.00189400e-01
-1.49477422e-01 -1.10405660e+00 5.70050394e-03 3.28713804e-01
-1.97708890e-01 1.97940692e-01 -6.50424778e-01 1.16865945e+00
-6.83544800e-02 6.95767701e-01 1.26485348e-01 -5.57966173e-01
3.94535840e-01 -2.38436729e-01 8.96567047e-01 -8.28880370e-01
-3.20720404e-01 -1.22643568e-01 2.91694134e-01 -1.12195051e+00
-6.21993959e-01 -8.67343545e-02 -1.56575632e+00 -1.15695275e-01
-5.22012338e-02 -9.21644568e-02 4.57036287e-01 8.77233505e-01
1.73673928e-01 9.18416977e-01 2.58879084e-02 -7.21999586e-01
-3.19719225e-01 -8.68044913e-01 -7.37866700e-01 7.53761411e-01
2.44094089e-01 -1.02840257e+00 -9.97350439e-02 -1.31357312e-02] | [7.062404155731201, -0.5803235173225403] |
50ba1e0b-61f5-4ba7-aa29-5e9007e3daf9 | direct-measurement-of-arbitrary-quantum | 2101.05556 | null | https://arxiv.org/abs/2101.05556v3 | https://arxiv.org/pdf/2101.05556v3.pdf | Direct measurement of density-matrix elements using a phase-shifting technique Tianfeng | A direct measurement protocol allows reconstructing specific elements of the density matrix of a quantum state without using quantum state tomography. However, the direct measurement protocols to date are primarily based on weak or strong measurements with an ancillary pointer, which interacts with the investigated system to extract information about the specified elements. Here, we present a direct measurement scheme based on phase-shifting operations which do not need ancillary pointers. In this method, estimates of at most six expectation values of projective observables suffice to determine any specific element of an unknown quantum density matrix. A concrete quantum circuit to implement this direct measurement protocol for multiqubit states is provided, which is composed of just single-qubit gates and two multiqubit controlled-phase gates. This scheme is also extended for the direct measurement of the density matrix of continuous-variable quantum states. Our method can be used in quantum information applications where only partial information about the quantum state needs to be extracted, for example, problems such as entanglement witnessing, fidelity estimation of quantum systems, and quantum coherence estimation. | ['XiaoQi Zhou', 'Changliang Ren', 'Tianfeng Feng'] | 2021-01-14 | null | null | null | null | ['quantum-state-tomography'] | ['medical'] | [ 4.18339521e-01 7.77472463e-03 1.00315601e-01 -2.52682239e-01
-7.66372025e-01 -5.61372459e-01 2.91808516e-01 -7.15057254e-02
-7.21128225e-01 1.13337612e+00 -5.13047338e-01 -6.61844432e-01
-1.74726710e-01 -1.28842998e+00 -3.61986458e-01 -1.25475478e+00
8.26195627e-02 6.52179837e-01 -1.12973051e-02 -3.50408763e-01
6.37351096e-01 4.71205592e-01 -9.67256963e-01 -1.53737798e-01
5.80923498e-01 6.32587552e-01 -6.59133047e-02 7.72600293e-01
5.99545315e-02 6.54392779e-01 -3.35869074e-01 -8.28147531e-02
3.11943859e-01 -1.07160366e+00 -8.19236279e-01 -4.18627739e-01
-1.85612068e-01 -5.55923402e-01 -8.78723443e-01 1.60340106e+00
2.72832006e-01 8.46007988e-02 4.95288372e-01 -7.48317599e-01
-1.53744161e-01 8.03054094e-01 -7.98845664e-02 1.09021775e-01
4.14606214e-01 4.24544930e-01 1.04441130e+00 -4.84800935e-01
5.10665476e-01 6.40185297e-01 8.00556242e-02 4.36751992e-01
-1.65194976e+00 -8.45101178e-01 -1.22117782e+00 5.01838982e-01
-1.81663978e+00 -5.50065577e-01 6.46249056e-01 -5.18329330e-02
9.57267702e-01 9.57537070e-02 7.50702322e-01 4.31123167e-01
3.89229864e-01 -1.77518323e-01 1.64025533e+00 -8.37591887e-01
4.52146769e-01 4.17797208e-01 5.34188807e-01 7.75658488e-01
5.68007469e-01 6.89642012e-01 -4.82010096e-01 -1.91582650e-01
5.95936894e-01 -3.19165349e-01 -4.09251273e-01 -5.13439119e-01
-1.31769204e+00 7.16829538e-01 2.19837204e-01 5.57166994e-01
-3.75964880e-01 2.59536266e-01 4.16812822e-02 5.21805704e-01
-4.77787405e-01 5.65517783e-01 7.54737109e-02 -3.62356603e-01
-6.53517962e-01 -9.51154232e-02 1.07606769e+00 6.77679241e-01
1.53230536e+00 -3.35668892e-01 -5.19360080e-02 -4.21001405e-01
5.15080579e-02 1.27455914e+00 -3.03520322e-01 -9.19217587e-01
2.37838894e-01 7.77887739e-03 4.32890117e-01 -2.47173294e-01
-2.52451211e-01 1.14249602e-01 -8.50904346e-01 2.39725783e-01
5.25454700e-01 -2.77427226e-01 -8.04854393e-01 1.61642158e+00
1.84374258e-01 -1.40781924e-02 3.64732862e-01 8.66851091e-01
4.68420476e-01 7.31379330e-01 -5.54748297e-01 -4.79457617e-01
1.12304735e+00 -2.51031756e-01 -9.38573599e-01 7.46850297e-02
7.25941360e-01 -6.07278228e-01 2.88447827e-01 2.70868033e-01
-1.08325064e+00 -2.91462719e-01 -1.29251862e+00 4.61926311e-02
-6.14292361e-02 -3.66809189e-01 6.88108206e-01 1.15694726e+00
-7.63593256e-01 8.32434475e-01 -8.55600655e-01 1.78474247e-01
-2.86172301e-01 7.01920927e-01 -7.11120188e-01 -1.74219489e-01
-1.25600576e+00 1.20257246e+00 8.07135582e-01 4.51917678e-01
-3.59122515e-01 -1.08997092e-01 -6.26879573e-01 2.45246127e-01
8.72549266e-02 -6.57129526e-01 8.38933945e-01 -5.47256730e-02
-1.96451068e+00 5.81763029e-01 -1.54923573e-01 -1.59915656e-01
-3.31283361e-01 6.52151942e-01 -4.11279291e-01 4.98789132e-01
-1.20197453e-01 -2.28559628e-01 2.55435795e-01 -4.04885322e-01
6.28500730e-02 -4.59799886e-01 2.03849256e-01 -1.34472296e-01
2.56180555e-01 -2.36025810e-01 1.97278455e-01 8.41726959e-01
7.83023655e-01 -1.10539603e+00 -1.32881463e-01 -4.95905697e-01
-5.66950560e-01 3.24254036e-01 4.57678407e-01 4.53369804e-02
9.14777577e-01 -2.14446974e+00 2.44001955e-01 6.46618187e-01
1.57559782e-01 1.63333520e-01 -1.10572875e-01 1.02305651e+00
1.01707369e-01 -2.13315308e-01 -3.67758453e-01 -3.78929302e-02
1.89375564e-01 1.55710593e-01 1.04537951e-02 8.85071874e-01
1.23947054e-01 8.86640191e-01 -8.99695218e-01 -3.28032792e-01
4.29630876e-01 2.73309290e-01 -5.60820639e-01 2.11939409e-01
4.22090948e-01 8.73927534e-01 -6.53398395e-01 3.57378155e-01
1.15158117e+00 -2.61588693e-01 4.91494805e-01 -1.98586091e-01
-4.76270080e-01 9.00702477e-01 -1.40226936e+00 1.62493753e+00
-1.53311729e-01 4.23532248e-01 1.69782281e-01 -8.26630771e-01
6.83779478e-01 5.11095107e-01 2.43201226e-01 -9.05831337e-01
3.79714906e-01 6.22636259e-01 6.99973524e-01 -4.52644318e-01
7.99657106e-01 -9.01199102e-01 -2.99703449e-01 8.51667881e-01
2.87196487e-01 -8.80374134e-01 3.34388375e-01 4.33350235e-01
1.37564230e+00 -2.08852291e-01 6.09240353e-01 -3.14924568e-01
6.56930327e-01 -3.51814955e-01 3.74061912e-01 9.61867809e-01
-2.77300864e-01 1.64433479e-01 4.97641325e-01 -1.82039873e-03
-1.21283865e+00 -1.22479737e+00 -6.75137579e-01 -1.86726213e-01
7.71072865e-01 -5.96969903e-01 -3.69097739e-01 4.29343730e-02
-3.41396868e-01 7.35149860e-01 -2.86403209e-01 -2.94465452e-01
-1.80104330e-01 -8.26495290e-01 3.80624056e-01 -2.53263712e-02
6.44496262e-01 -9.67661083e-01 -3.30870569e-01 2.23746642e-01
-1.11374833e-01 -1.19754851e+00 1.97894886e-01 5.62625229e-01
-6.73572421e-01 -1.12018049e+00 1.01322912e-01 -2.62419991e-02
8.16382945e-01 2.42468446e-01 6.14758313e-01 -3.03966105e-02
-4.24071364e-02 1.61822960e-01 -7.04392865e-02 2.33843178e-01
-6.67337120e-01 -2.24119976e-01 2.63899803e-01 -1.97194725e-01
8.06152284e-01 -6.10579669e-01 -4.16189969e-01 -5.69600277e-02
-6.74778700e-01 -1.60831049e-01 6.43715680e-01 1.05495381e+00
3.50282133e-01 8.42863843e-02 -1.51709408e-01 -9.12681997e-01
3.09829205e-01 -1.84485093e-01 -9.45524514e-01 -3.98465209e-02
-3.18084747e-01 5.63882649e-01 6.13020062e-01 5.28664552e-02
-7.79378712e-01 -5.18760718e-02 -2.41866246e-01 4.31436598e-01
1.83333755e-02 6.12960756e-01 -2.72542536e-02 -6.59631729e-01
5.82104921e-01 3.80885482e-01 -2.47912794e-01 -8.81888345e-02
1.95352674e-01 7.32346714e-01 4.22247440e-01 -5.57111561e-01
1.30947781e+00 3.15762460e-01 9.44471359e-01 -7.63706088e-01
-5.81770062e-01 -7.51715660e-01 -1.13376689e+00 3.23000580e-01
6.91139519e-01 -5.09754658e-01 -1.32100332e+00 3.91219556e-01
-1.10263121e+00 1.12766279e-02 -3.46586406e-01 1.18110240e+00
-4.97556210e-01 6.68723166e-01 -7.70198286e-01 -1.23675275e+00
-3.04883346e-02 -1.25778258e+00 8.84900331e-01 2.67117083e-01
3.09488028e-01 -8.09163630e-01 3.53977770e-01 1.61063209e-01
6.01186216e-01 -2.73918897e-01 7.01912403e-01 -1.10656552e-01
-1.37369680e+00 -6.24936640e-01 -1.33996472e-01 2.49752462e-01
-4.07422185e-02 -4.74655449e-01 -9.10386264e-01 -5.61162889e-01
1.98470056e-01 -6.29199862e-01 5.86693048e-01 -2.10132394e-02
5.28140306e-01 3.91034245e-01 -2.53000081e-01 5.06029308e-01
1.48065138e+00 1.67401955e-01 1.09472585e+00 -1.32167220e-01
4.93475616e-01 1.11120229e-03 4.08388466e-01 3.29751551e-01
1.07694417e-01 5.35303593e-01 2.03258004e-02 3.87816668e-01
4.18332100e-01 -5.97981587e-02 2.90604889e-01 1.30693293e+00
-3.79222721e-01 -1.13651164e-01 -4.71572578e-01 5.83112463e-02
-1.24855304e+00 -1.46357918e+00 -5.97369671e-01 2.67554021e+00
7.19917178e-01 1.85628161e-02 -5.82296729e-01 4.19910282e-01
5.59553683e-01 5.10067046e-02 -1.79313779e-01 -2.98458725e-01
1.37100741e-01 1.00608385e+00 6.32796645e-01 8.52627814e-01
-5.71399987e-01 6.77022696e-01 6.66786337e+00 2.79999763e-01
-9.26865578e-01 1.98069602e-01 -4.15833473e-01 3.35923076e-01
-5.48841059e-01 1.08560336e+00 -6.32767975e-01 4.23592508e-01
1.23066771e+00 -1.43705487e-01 6.51507318e-01 9.43698958e-02
-1.04046002e-01 -7.73591816e-01 -1.07743490e+00 1.07130599e+00
-4.56378162e-01 -1.03890717e+00 -4.96316850e-01 5.33360004e-01
6.68584764e-01 -1.76846728e-01 -2.53901482e-01 5.34193516e-01
-2.62894332e-01 -5.79444289e-01 3.32126468e-02 6.19650006e-01
9.52972412e-01 -5.46239614e-01 1.03841877e+00 5.89834630e-01
-9.27222669e-01 2.47576237e-01 -6.17569089e-01 -4.95089054e-01
5.61911225e-01 7.38727033e-01 -6.40743732e-01 4.23351437e-01
-2.02085704e-01 3.41938995e-02 1.64584771e-01 8.40633154e-01
-5.07517636e-01 6.91758692e-01 -5.11032224e-01 -2.49600723e-01
1.88290015e-01 -1.04806769e+00 4.95346427e-01 6.60904050e-01
6.97512925e-01 7.51167178e-01 -1.55910432e-01 1.32781482e+00
-8.16550851e-02 -1.41357422e-01 -6.23629868e-01 -2.91713983e-01
5.48085928e-01 1.21733582e+00 -4.43231374e-01 -3.99806678e-01
-3.13332438e-01 9.39553201e-01 5.33180088e-02 2.84036994e-01
-3.96422535e-01 -8.08597207e-01 3.11602592e-01 -1.20635659e-01
2.19787821e-01 -5.99767029e-01 9.56657752e-02 -1.56383944e+00
-2.01456696e-01 -3.29939932e-01 -3.50556970e-01 -4.87232298e-01
-6.79424703e-01 2.26813525e-01 -1.94983348e-01 -1.06526482e+00
-5.67942917e-01 -5.72981119e-01 -5.35400629e-01 1.48524797e+00
-1.61379981e+00 -4.38623041e-01 -9.45395529e-02 4.94397193e-01
-8.51940870e-01 1.21489540e-01 1.34185803e+00 1.05647027e-01
-4.28935051e-01 1.01579979e-01 4.46678370e-01 1.67498037e-01
5.39790392e-01 -1.35959113e+00 1.29608333e-01 1.09052205e+00
1.35867029e-01 1.03497910e+00 7.40632534e-01 -3.93474281e-01
-2.17156339e+00 -1.73839763e-01 9.09464777e-01 -1.85682103e-01
8.51775825e-01 -5.43515146e-01 -6.93352520e-01 6.13862395e-01
9.39617753e-02 4.67993677e-01 7.26938665e-01 1.25201389e-01
-1.26145139e-01 -4.12569046e-02 -1.28479874e+00 -1.85200468e-01
6.52381778e-01 -1.35733294e+00 -3.05771738e-01 1.90631166e-01
4.52485755e-02 -6.37202382e-01 -9.62170541e-01 1.38219088e-01
7.28134811e-01 -1.09323335e+00 6.08153343e-01 -1.80221200e-01
-1.22074798e-01 -6.38639450e-01 -3.49478126e-01 -1.06839883e+00
-4.93156105e-01 -7.99922347e-01 3.00466176e-02 3.37490141e-01
2.50534266e-01 -9.81652558e-01 7.35361814e-01 6.47909164e-01
5.65631017e-02 3.12533885e-01 -1.22428477e+00 -5.93901515e-01
-1.28874153e-01 -1.22051507e-01 3.79558265e-01 7.76817739e-01
7.33590484e-01 6.33488357e-01 -5.06083906e-01 5.08167386e-01
9.45846498e-01 3.66086841e-01 8.36346805e-01 -9.96299267e-01
-8.27598512e-01 1.80093184e-01 -9.36304629e-01 -1.23880231e+00
8.94628316e-02 -1.01667333e+00 1.58505991e-01 -1.04349744e+00
7.33328342e-01 -4.28953677e-01 -5.42935312e-01 -6.69603050e-02
-2.73544881e-02 4.88218814e-01 9.82504413e-02 1.14307687e-01
-4.64536488e-01 6.06207550e-01 1.33923018e+00 -1.83691911e-03
5.99696636e-02 1.80300310e-01 -9.36442316e-02 9.56155881e-02
5.71914613e-01 -7.41293073e-01 -8.52822959e-02 1.51795223e-01
4.22810376e-01 7.49950111e-01 3.41041327e-01 -1.16177571e+00
4.87375021e-01 -1.20507054e-01 -2.49659956e-01 -5.55457771e-01
7.95789540e-01 -5.37404478e-01 4.00321752e-01 8.07573199e-01
1.60118029e-01 -5.11689544e-01 -2.04767346e-01 3.30438435e-01
-3.64594877e-01 -1.01925945e+00 8.41554344e-01 -1.75662395e-02
-6.06888056e-01 2.44264334e-01 -3.50247562e-01 -5.24468303e-01
6.88847780e-01 2.27392931e-02 -5.00925839e-01 -2.30536178e-01
-6.03754342e-01 -4.10955846e-01 5.52869260e-01 -7.82899678e-01
5.28659940e-01 -1.30779016e+00 -4.37531233e-01 5.24347603e-01
6.21016026e-02 -5.39694309e-01 4.53109026e-01 1.16204572e+00
-7.17168868e-01 8.18902194e-01 -3.35371792e-01 -5.85071564e-01
-9.78152096e-01 4.68770534e-01 4.15244401e-01 -1.99845597e-01
-3.01217020e-01 2.95732349e-01 -2.53972441e-01 -3.83173287e-01
-7.78154850e-01 -2.05312282e-01 5.89740932e-01 -6.48618937e-01
7.36791968e-01 1.04646549e-01 3.35222706e-02 -7.18664467e-01
-3.85380030e-01 5.72026491e-01 1.89892650e-01 -4.58548874e-01
8.54755104e-01 -1.71496406e-01 -6.11598015e-01 6.16914868e-01
1.39317632e+00 3.48671347e-01 -6.09314203e-01 -3.96069169e-01
-4.53498155e-01 -5.06013095e-01 3.48269999e-01 -3.65373969e-01
-5.03026247e-01 1.27162015e+00 4.97144252e-01 5.32453477e-01
8.21603060e-01 -6.43522665e-02 7.34715164e-01 1.14370060e+00
1.26346445e+00 -7.11471319e-01 -4.71277833e-01 5.09978354e-01
-1.86196819e-01 -1.39627528e+00 3.64260077e-02 -1.33557558e-01
2.31773958e-01 1.37543964e+00 -3.01124696e-02 8.79860073e-02
6.01829112e-01 3.17106992e-01 -4.55112070e-01 -3.21418554e-01
-4.25768018e-01 -3.77131641e-01 6.23179972e-02 2.71736294e-01
4.59833711e-01 5.10424018e-01 -5.43123662e-01 -4.09038395e-01
-1.33793190e-01 -1.54171720e-01 1.18983912e+00 8.67039382e-01
-4.97376055e-01 -1.71536791e+00 -4.82377619e-01 2.07142249e-01
-1.33643255e-01 -3.65736216e-01 1.10960044e-01 6.64333701e-01
-1.10047072e-01 8.76157522e-01 -1.21299895e-02 -3.81957322e-01
5.38256913e-02 6.52237311e-02 1.31253242e+00 -7.25482523e-01
1.06302276e-01 -4.25032765e-01 3.66124250e-02 -5.39761603e-01
-7.29178309e-01 -6.78187072e-01 -1.47991252e+00 -9.25754786e-01
-9.01984930e-01 6.72743380e-01 9.71965134e-01 1.17469931e+00
-1.62358209e-01 3.01166289e-02 7.11425364e-01 -5.75893760e-01
-8.30104589e-01 -9.64435458e-01 -1.36942029e+00 5.69996871e-02
4.09963816e-01 -4.18630123e-01 -5.68288267e-01 -5.95882297e-01] | [5.603762149810791, 4.888608455657959] |
ab944a3f-68b4-4c5f-a6cd-434a71311b18 | introducing-tales-of-tribute-ai-competition | 2305.08234 | null | https://arxiv.org/abs/2305.08234v1 | https://arxiv.org/pdf/2305.08234v1.pdf | Introducing Tales of Tribute AI Competition | This paper presents a new AI challenge, the Tales of Tribute AI Competition (TOTAIC), based on a two-player deck-building card game released with the High Isle chapter of The Elder Scrolls Online. Currently, there is no other AI competition covering Collectible Card Games (CCG) genre, and there has never been one that targets a deck-building game. Thus, apart from usual CCG-related obstacles to overcome, like randomness, hidden information, and large branching factor, the successful approach additionally requires long-term planning and versatility. The game can be tackled with multiple approaches, including classic adversarial search, single-player planning, and Neural Networks-based algorithms. This paper introduces the competition framework, describes the rules of the game, and presents the results of a tournament between sample AI agents. The first edition of TOTAIC is hosted at the IEEE Conference on Games 2023. | ['Damian Kowalik', 'Dominik Budzki', 'Katarzyna Polak', 'Radosław Miernik', 'Jakub Kowalski'] | 2023-05-14 | null | null | null | null | ['card-games'] | ['playing-games'] | [ 5.41944355e-02 2.67682344e-01 8.32265913e-02 2.93880016e-01
-1.00137389e+00 -8.99261653e-01 5.26568592e-01 -2.65042305e-01
-7.78691947e-01 1.37261915e+00 -1.15463249e-01 -4.00753826e-01
-5.14250875e-01 -7.61856139e-01 -5.37863016e-01 -3.78306448e-01
-3.53110313e-01 1.16777980e+00 4.47355956e-01 -1.02328181e+00
4.56212908e-01 1.91312551e-01 -1.36618090e+00 2.45565087e-01
7.49047875e-01 8.87986720e-01 -1.17168620e-01 9.42529976e-01
9.59634408e-02 1.27590656e+00 -1.01103699e+00 -6.95339322e-01
8.70855629e-01 -6.73876464e-01 -8.44020247e-01 -6.36802614e-01
-1.72712415e-01 -5.46240807e-01 -2.18390495e-01 8.44330907e-01
6.97669566e-01 1.73568532e-01 3.75378340e-01 -1.73400784e+00
1.82947069e-01 1.07288158e+00 -2.25569740e-01 1.96156487e-01
7.49047399e-01 3.88896912e-01 1.03059578e+00 -4.10722978e-02
7.21895278e-01 9.97768760e-01 5.96814096e-01 5.98586738e-01
-7.29996920e-01 -8.47903371e-01 8.81837904e-02 2.90826082e-01
-1.22522581e+00 -6.75004721e-02 4.31915909e-01 -2.82294393e-01
1.03941560e+00 5.21785140e-01 1.23058999e+00 1.04332542e+00
3.83932978e-01 1.15081620e+00 1.23340690e+00 -4.70172554e-01
6.91390693e-01 -4.56736445e-01 -5.53510368e-01 3.33360612e-01
2.68368512e-01 8.94255042e-01 -3.73995125e-01 -2.44764552e-01
6.74084067e-01 -5.08716464e-01 2.58581191e-01 -3.63863975e-01
-7.24053383e-01 9.44502354e-01 1.10499397e-01 1.42142519e-01
-4.61400777e-01 4.91425425e-01 3.77768725e-01 4.37095284e-01
-3.33575793e-02 1.09353197e+00 -1.46169335e-01 -9.63551342e-01
-9.26194251e-01 1.07219970e+00 1.28027248e+00 8.59628558e-01
1.34475783e-01 1.03614688e-01 1.24528512e-01 1.79362461e-01
1.83403328e-01 1.57917380e-01 1.18445031e-01 -1.41971993e+00
5.56903601e-01 -1.33751109e-02 3.80955070e-01 -9.96933818e-01
-6.30997479e-01 -3.12579572e-01 -3.33999157e-01 9.19373631e-01
6.50684059e-01 -6.81317270e-01 -6.66141629e-01 1.33134902e+00
-8.68684798e-02 -4.17592078e-02 1.35696650e-01 1.04301536e+00
5.27167916e-01 5.30077994e-01 -3.36391866e-01 1.58740599e-02
1.02093852e+00 -1.05065298e+00 -4.39989686e-01 -4.47226644e-01
2.58512139e-01 -4.85022485e-01 4.10528004e-01 9.38599586e-01
-1.61471307e+00 4.89918813e-02 -1.33041251e+00 5.87723911e-01
-4.14841592e-01 -8.48113060e-01 1.02423084e+00 8.77164185e-01
-8.96542847e-01 5.44430256e-01 -8.22088003e-01 -1.42958537e-01
1.78893745e-01 6.10852778e-01 4.47133482e-02 -2.54032850e-01
-1.51005268e+00 1.24489367e+00 7.25404918e-01 -1.34224847e-01
-1.10214448e+00 -2.65635550e-01 -5.04878819e-01 -6.16210774e-02
1.12721908e+00 -3.28534216e-01 1.34623206e+00 -7.14598656e-01
-2.18099546e+00 6.25836432e-01 8.40430915e-01 -8.56523275e-01
1.02088046e+00 -1.26856327e-01 -9.47508961e-02 -5.86234592e-02
1.60053849e-01 6.24006212e-01 2.16617599e-01 -9.75021303e-01
-9.54351783e-01 -3.65948230e-02 7.67089427e-01 6.22897625e-01
6.04027450e-01 2.60756135e-01 -3.08661699e-01 -5.41283607e-01
-3.16918910e-01 -9.44723248e-01 -7.51119852e-01 -6.35953248e-01
-3.89483720e-01 1.54539958e-01 -1.68955490e-01 -8.80368724e-02
1.32869816e+00 -1.84051573e+00 2.18687862e-01 3.27296406e-01
1.14066266e-01 -4.00827266e-02 -7.47239813e-02 8.49178374e-01
4.29604113e-01 5.92940412e-02 4.35170606e-02 2.49372438e-01
4.10291076e-01 3.05205643e-01 -1.09474003e-01 6.41579032e-02
-3.61162692e-01 1.03152621e+00 -1.18828714e+00 -1.33167744e-01
-1.53227270e-01 -5.37153363e-01 -7.97804952e-01 -2.47936308e-01
-3.39914441e-01 1.17073745e-01 -6.16547406e-01 5.77279568e-01
4.04423714e-01 3.30164284e-01 2.71280974e-01 7.96576262e-01
-3.46486032e-01 2.95704424e-01 -1.35423493e+00 1.70623648e+00
2.30031803e-01 3.13353449e-01 2.17788860e-01 -7.79348969e-01
7.41909504e-01 1.99124500e-01 5.02584934e-01 -7.18804002e-01
2.18418851e-01 6.59774303e-01 3.77540380e-01 8.43165144e-02
9.94397938e-01 -1.57284513e-01 -7.23555982e-01 6.12209320e-01
-2.64635712e-01 -7.84404159e-01 6.27533734e-01 2.91942865e-01
1.37285995e+00 4.29192245e-01 3.58254611e-01 -3.24398816e-01
-2.97006648e-02 6.22913957e-01 6.41115606e-01 1.25948489e+00
-5.35288811e-01 5.09924293e-01 5.88849425e-01 -8.08963895e-01
-8.87828052e-01 -8.18406582e-01 4.93581891e-01 9.91058588e-01
6.00431621e-01 -6.90152109e-01 -7.58148849e-01 -3.52073431e-01
-2.13885993e-01 8.27387094e-01 -5.91470718e-01 -1.35311857e-01
-5.30955970e-01 -3.80828142e-01 9.92038190e-01 2.35525399e-01
6.72767222e-01 -1.42027712e+00 -1.17367339e+00 5.98136783e-01
-1.09904870e-01 -8.23382199e-01 -4.61032420e-01 4.59266633e-01
-2.08993703e-01 -1.05415058e+00 -4.94241685e-01 -5.95613956e-01
-1.79225609e-01 -1.60541520e-01 1.12321556e+00 -7.28829280e-02
-3.07030678e-01 1.54830009e-01 -4.32582825e-01 -6.51386082e-01
-3.28359425e-01 2.75122464e-01 -2.46559419e-02 -8.09033811e-01
2.51537800e-01 -5.15787840e-01 -3.33739996e-01 2.93830156e-01
-4.14003491e-01 2.73682058e-01 5.54272771e-01 9.04871881e-01
1.61990017e-01 3.45053971e-01 3.17557305e-01 -7.19199598e-01
9.04468715e-01 -2.30441362e-01 -8.75816286e-01 6.85539320e-02
-3.68144512e-01 -1.56795055e-01 5.78090489e-01 -2.52486050e-01
-6.45143688e-01 -4.15090192e-03 1.06038041e-01 1.22816833e-02
-6.19925968e-02 6.07457399e-01 2.68697250e-03 -1.84684262e-01
8.70858550e-01 2.20047355e-01 -4.63847863e-03 1.50733203e-01
2.57651955e-01 3.38971019e-01 7.38903940e-01 -9.55755234e-01
8.66874337e-01 5.33277504e-02 -2.26757508e-02 -2.36798331e-01
-3.73691767e-01 1.46964237e-01 -2.17938915e-01 -4.84380901e-01
8.48579705e-01 -5.38039505e-01 -1.13841558e+00 8.40513587e-01
-9.02637482e-01 -5.53338528e-01 -5.90920150e-01 6.08324349e-01
-1.00470126e+00 -7.88985491e-02 -6.21622562e-01 -8.62639844e-01
-3.56691144e-02 -1.14964056e+00 3.01677048e-01 5.07833719e-01
-2.57645547e-01 -4.91610020e-01 5.37561893e-01 6.15551829e-01
5.94360054e-01 5.04585207e-01 4.90912527e-01 -8.87130737e-01
-8.02046716e-01 -5.69001019e-01 4.66839910e-01 -1.84858873e-01
-4.69813019e-01 -3.08970332e-01 -2.32590213e-01 -3.48821342e-01
-5.90409875e-01 -9.08512115e-01 1.83663741e-01 4.53576803e-01
2.17048034e-01 -1.74831882e-01 -1.85366884e-01 3.93121481e-01
1.11596632e+00 1.00949132e+00 1.00657439e+00 1.17978072e+00
-4.29671910e-03 1.80159420e-01 7.00081706e-01 7.34677494e-01
4.32190984e-01 7.79823661e-01 7.21018136e-01 3.94340485e-01
5.62550187e-01 -4.86577779e-01 2.85083920e-01 3.04333508e-01
-6.52293444e-01 -4.70625967e-01 -9.52164352e-01 1.05098061e-01
-1.81078100e+00 -1.34249735e+00 3.13998342e-01 1.98213673e+00
5.46059966e-01 7.74327815e-01 5.37542641e-01 9.92226601e-02
4.80148464e-01 -5.73333120e-03 -5.82396269e-01 -8.84677827e-01
-2.35697776e-01 5.55459380e-01 6.68493986e-01 5.57523310e-01
-1.01776755e+00 1.28465760e+00 7.46049070e+00 1.17954731e+00
-5.32352686e-01 -3.08665514e-01 4.25470680e-01 -3.25859308e-01
-1.70562103e-01 2.49171063e-01 -5.31533122e-01 4.01554316e-01
6.48362041e-01 -6.52922988e-01 1.14249122e+00 6.90161586e-01
-2.38868639e-01 -4.56386864e-01 -6.53119922e-01 5.79098821e-01
4.47314829e-02 -1.23678458e+00 -4.22062337e-01 3.68116558e-01
7.95502484e-01 -1.56002432e-01 3.94922420e-02 7.92132080e-01
1.26052713e+00 -1.41643226e+00 1.02428603e+00 1.62686318e-01
5.16838431e-01 -1.17267632e+00 7.03021407e-01 5.10958612e-01
-8.55038226e-01 -3.73960763e-01 -1.96020722e-01 -7.26538718e-01
1.93801641e-01 -5.91492534e-01 -4.31194365e-01 7.57353306e-01
5.98955989e-01 5.24518229e-02 -1.04998909e-02 1.46545541e+00
-2.46539623e-01 2.46285185e-01 -6.19374156e-01 -5.61166763e-01
7.32842684e-01 -4.41559792e-01 8.19528043e-01 4.68042672e-01
1.57269642e-01 7.17906237e-01 4.86805111e-01 6.35177910e-01
3.30864698e-01 -2.14814529e-01 -4.08366591e-01 -1.37560636e-01
6.54829025e-01 7.28431582e-01 -7.35698104e-01 1.04414143e-01
9.33223125e-03 9.62347627e-01 -6.69567958e-02 5.91656789e-02
-9.40222800e-01 -4.52765018e-01 3.62134308e-01 -9.17215124e-02
2.18471527e-01 -3.14965397e-02 -3.46000314e-01 -7.99867809e-01
-2.85250545e-01 -1.48547769e+00 4.02375370e-01 -7.12545216e-01
-9.97641861e-01 8.43498945e-01 2.73880780e-01 -1.17811203e+00
-9.26287234e-01 -4.56004202e-01 -7.73281991e-01 5.47682285e-01
-6.72029018e-01 -8.86349738e-01 1.15112327e-01 4.23463404e-01
3.67589891e-01 -7.67265022e-01 9.01924491e-01 5.71847856e-02
-3.24421883e-01 8.37200403e-01 3.34608078e-01 -1.16301894e-01
2.26393784e-03 -1.19039416e+00 5.47193885e-01 5.96228659e-01
-1.13260761e-01 -5.96726723e-02 8.07598889e-01 -5.81535995e-01
-1.45537424e+00 -2.46155962e-01 2.21611753e-01 -2.90680528e-01
7.22652733e-01 -2.21282691e-01 7.58343264e-02 5.47892928e-01
3.10001343e-01 -6.24661624e-01 2.67517686e-01 -5.15491627e-02
1.78601459e-01 2.34294951e-01 -9.68861520e-01 8.15727174e-01
1.00714004e+00 -5.13829552e-02 -4.88056034e-01 9.65791661e-03
3.78348678e-01 -9.83587325e-01 -3.36043835e-01 1.02758370e-01
7.85046875e-01 -9.81491029e-01 7.54897058e-01 -8.45609367e-01
6.06860459e-01 -8.33008513e-02 -1.33553252e-01 -1.39066935e+00
-3.89332503e-01 -1.33741903e+00 4.24701542e-01 6.96085751e-01
6.44524157e-01 -4.92042542e-01 1.30439878e+00 8.42294693e-01
-1.81101009e-01 -7.43050158e-01 -1.23612857e+00 -1.02645111e+00
5.15342295e-01 -4.34293658e-01 6.28398359e-01 5.80875814e-01
4.73539859e-01 1.36940107e-01 -9.03254271e-01 -3.37307334e-01
5.99091828e-01 -1.17097192e-01 9.25409257e-01 -9.55275536e-01
-9.34832633e-01 -7.72823989e-01 -7.93612599e-01 -9.42093194e-01
-3.90124083e-01 -5.64940989e-01 3.28417778e-01 -1.39246106e+00
-1.09004349e-01 -4.51654673e-01 -2.14394229e-03 2.69645154e-01
7.24419132e-02 1.93255499e-03 8.60915124e-01 5.78274913e-02
-9.53782201e-01 2.74467319e-01 1.21244633e+00 -2.30348051e-01
-3.07947040e-01 3.18478882e-01 -7.27868199e-01 5.79313934e-01
9.05741513e-01 -3.12596023e-01 -3.82278711e-01 -2.23498568e-01
5.08102834e-01 4.85001773e-01 -5.21181487e-02 -1.33711112e+00
7.26398826e-01 -5.76604843e-01 -2.03874409e-01 -3.16296667e-01
5.85958600e-01 -5.16070843e-01 4.96081471e-01 9.00467217e-01
-2.81301320e-01 1.23878561e-01 3.71019363e-01 2.48485446e-01
-1.65947154e-01 -4.13260072e-01 4.16681767e-01 -5.00878215e-01
-6.75773740e-01 7.07283244e-02 -1.11590338e+00 6.63981915e-01
1.41118097e+00 -5.63693941e-01 -3.96861970e-01 -8.72929037e-01
-5.63769817e-01 6.85265899e-01 3.39276135e-01 9.70012397e-02
4.25157368e-01 -1.11202812e+00 -9.23636198e-01 -1.24074064e-01
-3.28618526e-01 1.83270536e-02 1.55557901e-01 2.66519785e-01
-1.15991294e+00 2.85405844e-01 -8.54243517e-01 2.78553069e-01
-8.51960659e-01 5.05432427e-01 5.77601612e-01 -1.00908864e+00
-5.84784329e-01 9.51000810e-01 -1.53541684e-01 -4.52168196e-01
2.95755208e-01 4.13286388e-01 -1.24278136e-01 -3.72552425e-01
5.44068694e-01 4.31990951e-01 -2.88111418e-01 -1.16749786e-01
-3.42561215e-01 1.31857932e-01 -1.89881861e-01 -7.79809654e-01
1.31954801e+00 2.42600605e-01 2.25531235e-01 1.42764464e-01
1.35916919e-01 -2.37116456e-01 -1.09807611e+00 2.09677592e-01
2.31404901e-02 -3.99584562e-01 -2.25747719e-01 -1.27119267e+00
-8.42821002e-01 4.71007288e-01 1.93927765e-01 3.00014764e-01
9.43098187e-01 -5.56628346e-01 8.40879142e-01 4.54125404e-01
1.20912242e+00 -1.22778964e+00 -5.05405143e-02 1.05331707e+00
8.27362239e-01 -5.62633812e-01 -1.04626857e-01 7.74478987e-02
-1.10677361e+00 1.04370725e+00 8.58073175e-01 -3.94997925e-01
3.07673514e-01 7.40175307e-01 -6.05136994e-03 -5.62020279e-02
-9.59651232e-01 -9.70463306e-02 -2.88072646e-01 9.12830234e-01
-3.04390103e-01 2.46854886e-01 -3.75898510e-01 9.96691108e-01
-8.33992064e-01 1.67825624e-01 7.77089596e-01 1.36451578e+00
-4.83014941e-01 -1.17946219e+00 -4.82723147e-01 2.53365278e-01
-5.05194306e-01 -3.25225115e-01 -7.96026051e-01 1.09945619e+00
6.72866479e-02 9.49852705e-01 -2.30079740e-02 -6.83230817e-01
3.59341592e-01 -3.59154493e-01 5.80454350e-01 -1.88489392e-01
-9.93346095e-01 -2.59505332e-01 4.29285794e-01 -7.41745532e-01
9.16399211e-02 -5.79834819e-01 -9.69557941e-01 -9.80440199e-01
-1.81270495e-01 7.08070278e-01 3.43134135e-01 8.97399127e-01
1.85860656e-02 2.82995135e-01 3.86934906e-01 -9.36594307e-01
-6.08315408e-01 -5.84967852e-01 -9.46195722e-01 -1.78274289e-01
-3.89904797e-01 -6.48452699e-01 -6.63753524e-02 -7.77374923e-01] | [3.479564905166626, 1.5097851753234863] |
91e963e8-3e6a-4eda-83c9-bf9946f466ca | kgboost-a-classification-based-knowledge-base | 2112.09340 | null | https://arxiv.org/abs/2112.09340v1 | https://arxiv.org/pdf/2112.09340v1.pdf | KGBoost: A Classification-based Knowledge Base Completion Method with Negative Sampling | Knowledge base completion is formulated as a binary classification problem in this work, where an XGBoost binary classifier is trained for each relation using relevant links in knowledge graphs (KGs). The new method, named KGBoost, adopts a modularized design and attempts to find hard negative samples so as to train a powerful classifier for missing link prediction. We conduct experiments on multiple benchmark datasets, and demonstrate that KGBoost outperforms state-of-the-art methods across most datasets. Furthermore, as compared with models trained by end-to-end optimization, KGBoost works well under the low-dimensional setting so as to allow a smaller model size. | ['C. -C. Jay Kuo', 'Bin Wang', 'Xiou Ge', 'Yun-Cheng Wang'] | 2021-12-17 | null | null | null | null | ['knowledge-base-completion', 'knowledge-base-completion'] | ['graphs', 'knowledge-base'] | [-1.02270424e-01 5.94440877e-01 -1.33332157e+00 -4.63414192e-01
-4.67815548e-01 -8.32806602e-02 3.30763519e-01 4.58176970e-01
-8.34488869e-02 1.11482620e+00 -1.43563911e-01 -4.12436217e-01
-6.91613853e-01 -1.17115843e+00 -8.57589364e-01 -3.76660436e-01
-3.63495618e-01 8.88478816e-01 9.23747849e-03 -1.83299825e-01
-1.57876134e-01 1.23196132e-01 -1.01051080e+00 1.99206457e-01
1.09255171e+00 1.17809045e+00 -2.79390663e-01 1.77924424e-01
-4.17503566e-02 9.09313858e-01 -4.20182198e-01 -1.22323847e+00
2.92881966e-01 -7.87497535e-02 -1.02220905e+00 -3.18083018e-01
4.41585034e-01 4.79436591e-02 -3.24304432e-01 9.13410604e-01
4.05607432e-01 6.88423216e-02 6.56189442e-01 -1.39874375e+00
-8.53765249e-01 8.42895091e-01 -4.84103292e-01 -8.35305676e-02
3.93324196e-01 -3.18107367e-01 1.50930274e+00 -8.57156694e-01
7.87335396e-01 1.24167717e+00 8.75719011e-01 1.76005855e-01
-1.63722157e+00 -5.19642174e-01 1.65328413e-01 5.63535035e-01
-1.44080210e+00 -1.43372178e-01 9.05625045e-01 -2.70844609e-01
8.72150660e-01 3.01617712e-01 8.18688214e-01 1.00921261e+00
2.58941799e-01 9.53151822e-01 8.72880518e-01 -6.56249404e-01
4.27796513e-01 1.05858393e-01 6.75005317e-01 9.48170900e-01
7.61509597e-01 -3.26519199e-02 -9.64833498e-01 -5.88810563e-01
1.75696447e-01 -5.05252108e-02 -2.76000559e-01 -7.06854105e-01
-8.95808518e-01 9.78908718e-01 6.08777881e-01 -1.61894083e-01
-4.58323449e-01 -1.51662687e-02 2.11404935e-01 5.27996361e-01
7.63557553e-01 4.16662812e-01 -7.47581363e-01 4.54931051e-01
-6.81719184e-01 2.96411246e-01 1.22048795e+00 9.88772690e-01
7.36513615e-01 -3.13071698e-01 -3.71054530e-01 9.69681799e-01
4.09027964e-01 9.50293317e-02 4.10962403e-01 -4.42798287e-01
6.68977082e-01 8.43876481e-01 -1.82828024e-01 -9.38925803e-01
-4.51496154e-01 -9.92218673e-01 -6.82749033e-01 2.52437349e-02
3.14915895e-01 -1.33892104e-01 -9.32614923e-01 1.45629048e+00
5.01317739e-01 4.56905738e-02 2.52053708e-01 7.24814475e-01
8.40509772e-01 2.05374971e-01 4.15022224e-01 -3.26855391e-01
1.09991241e+00 -1.23092222e+00 -8.03495228e-01 -5.46616912e-01
6.88486099e-01 -3.28024626e-01 6.06285572e-01 5.58219433e-01
-8.03663254e-01 -3.70626718e-01 -1.23440146e+00 2.40041479e-01
-7.23105788e-01 5.69939204e-02 1.38937998e+00 8.46193612e-01
-7.24316299e-01 6.18266881e-01 -5.12359977e-01 -2.66201645e-01
6.15012527e-01 3.98566097e-01 -3.54393005e-01 -3.90779525e-01
-1.31030095e+00 1.00114298e+00 9.36766088e-01 1.83688328e-01
-5.49821138e-01 -6.10448480e-01 -8.22488606e-01 2.39233649e-03
7.53084898e-01 -1.17134321e+00 7.57679284e-01 -4.49199170e-01
-1.36585307e+00 6.84160352e-01 -1.15734525e-01 -5.89470685e-01
4.82542187e-01 -2.44795874e-01 -5.37939727e-01 -1.34163871e-01
4.39754315e-02 3.22255880e-01 7.30726838e-01 -1.19030058e+00
-6.14150524e-01 -6.29246593e-01 -3.42142396e-02 3.37461308e-02
-4.90129203e-01 -4.09190714e-01 -6.34638309e-01 -6.61620080e-01
4.51956302e-01 -7.25766659e-01 -1.86890706e-01 -4.11175966e-01
-8.32976639e-01 -3.79161865e-01 5.65489709e-01 -7.22526848e-01
1.27325153e+00 -1.61539900e+00 8.85945335e-02 6.35501504e-01
3.38479906e-01 1.35967121e-01 1.25907063e-01 1.79399103e-01
-1.47766218e-01 -4.15859148e-02 9.21554491e-02 -3.00489396e-01
3.23340930e-02 1.64893478e-01 -9.59395394e-02 2.99557239e-01
1.56938806e-01 1.29540324e+00 -1.00804210e+00 -5.65771878e-01
-2.71671772e-01 5.01090959e-02 -2.56089568e-01 -1.98920481e-02
-4.95997190e-01 -1.87789261e-01 -5.42257130e-01 1.19561923e+00
7.08686590e-01 -5.09281337e-01 7.64606118e-01 -1.96720958e-01
7.05784500e-01 3.49640250e-02 -1.09131205e+00 1.51244748e+00
-2.58108936e-02 1.68190360e-01 -2.04896674e-01 -1.32025301e+00
1.08762002e+00 6.50670677e-02 2.92605549e-01 -6.53690875e-01
-5.77429235e-02 1.34109154e-01 -2.92929351e-01 -4.07901883e-01
2.26978734e-01 -9.48481485e-02 1.30207151e-01 2.38429848e-02
3.49627793e-01 3.65021378e-01 3.92336786e-01 3.35482180e-01
1.08168399e+00 9.73828807e-02 4.38143015e-01 -2.17223186e-02
7.73895979e-02 3.48484606e-01 8.17778766e-01 9.36600268e-01
1.30312607e-01 -1.11772418e-01 6.08878851e-01 -5.00941813e-01
-3.83812934e-01 -9.76651549e-01 -3.32470179e-01 1.15162981e+00
2.39425853e-01 -6.87338769e-01 -2.05427140e-01 -1.25387383e+00
7.86023140e-01 6.38199449e-01 -5.08727789e-01 -3.36684257e-01
-3.05443015e-02 -1.38743246e+00 1.83104008e-01 5.00436008e-01
2.19984502e-01 -6.83354378e-01 3.88467252e-01 5.22334456e-01
-9.53423977e-03 -8.98161709e-01 2.62412071e-01 6.51591063e-01
-1.01137280e+00 -1.46640766e+00 -3.79919052e-01 -8.22103500e-01
5.72684884e-01 -1.03679309e-02 1.29078650e+00 -1.14847568e-03
-3.60671818e-01 1.14096500e-01 -5.52439690e-01 -5.06411850e-01
9.00642797e-02 2.81862468e-01 -1.12509511e-01 -3.78428288e-02
6.61171734e-01 -4.58252192e-01 -3.64943117e-01 3.28708887e-01
-5.01665592e-01 -1.65726483e-01 8.12382996e-01 1.14934254e+00
6.99747086e-01 3.96653086e-01 9.60378647e-01 -1.16047788e+00
8.50912392e-01 -7.00873613e-01 -4.70846266e-01 7.73815989e-01
-1.37028980e+00 1.03417739e-01 3.77811700e-01 -3.13482851e-01
-9.15473163e-01 -1.18281217e-02 2.55013376e-01 -9.76430699e-02
3.31920177e-01 1.09496093e+00 -1.53482169e-01 -2.34240815e-01
7.37599492e-01 -1.84945494e-01 -1.38980031e-01 -6.82201326e-01
5.59956074e-01 5.24068236e-01 3.85522246e-01 -5.87569952e-01
5.37921607e-01 2.75887668e-01 3.93904209e-01 -3.65659595e-01
-1.09684980e+00 -4.99775052e-01 -6.05236888e-01 -1.23410791e-01
4.56861973e-01 -9.76012945e-01 -9.02848303e-01 1.22430317e-01
-8.48927259e-01 -3.06143016e-01 -5.81308529e-02 6.05105698e-01
-2.91376621e-01 1.19384676e-01 -5.24096727e-01 -7.73767054e-01
-5.21570146e-01 -4.26669687e-01 5.19221544e-01 1.06285922e-01
-1.66869953e-01 -1.14065135e+00 2.06709467e-02 7.40305424e-01
-1.07415996e-01 1.61065802e-01 1.12462378e+00 -8.08824360e-01
-4.64331001e-01 -7.27793813e-01 -1.26878291e-01 2.46091187e-01
-1.63626805e-01 -2.51524389e-01 -8.37825060e-01 -2.72901237e-01
-4.99452114e-01 -5.62171161e-01 1.36795247e+00 1.84199244e-01
9.03682947e-01 -3.14755142e-01 -1.00072873e+00 5.77599466e-01
1.33457315e+00 3.27143259e-02 3.97177011e-01 5.29629707e-01
7.06993639e-01 4.82256889e-01 9.68702614e-01 1.38668433e-01
6.31130874e-01 7.65768588e-01 5.39707065e-01 -1.85695589e-01
6.52818456e-02 -4.12091315e-01 -1.53162226e-01 2.46217042e-01
3.17242406e-02 -3.76949698e-01 -9.29168403e-01 3.30282688e-01
-2.46146131e+00 -6.45412743e-01 -2.71828294e-01 2.06011438e+00
1.05547965e+00 4.01502579e-01 2.81587709e-02 1.28345653e-01
6.41335189e-01 -3.72747183e-02 -3.78137589e-01 8.48748684e-02
-4.07788247e-01 2.87240475e-01 7.16388881e-01 2.67098665e-01
-1.22513974e+00 9.36240673e-01 7.07334948e+00 8.51634920e-01
-7.01935470e-01 1.28551483e-01 7.94742763e-01 -1.64597612e-02
-2.59136166e-02 2.79729337e-01 -9.86515343e-01 3.56432229e-01
5.28438985e-01 -5.45057058e-02 2.89119035e-01 1.20546865e+00
-3.16704720e-01 -1.86355352e-01 -1.08377504e+00 7.83344388e-01
-1.11553259e-02 -1.33966660e+00 -2.23092183e-01 -1.41160740e-02
9.36019897e-01 -6.46629483e-02 -2.79130399e-01 5.51586688e-01
7.19153881e-01 -8.42551589e-01 4.89164770e-01 6.43904388e-01
4.05034602e-01 -6.43471539e-01 7.39771903e-01 2.68229663e-01
-8.54925454e-01 -2.75788665e-01 -4.87775207e-01 -2.46659778e-02
6.19226843e-02 1.27821481e+00 -1.13499618e+00 1.08703017e+00
8.30584109e-01 7.08535016e-01 -7.29553759e-01 1.25954378e+00
-6.04058087e-01 7.57050455e-01 -2.35027254e-01 -8.10797513e-03
-2.12202579e-01 1.85481180e-02 1.53840378e-01 9.98222232e-01
-1.71981230e-01 -1.54488578e-01 3.96340102e-01 5.54299593e-01
-4.01516140e-01 2.95742720e-01 -3.11891705e-01 1.11161537e-01
4.82477397e-01 1.33456278e+00 -4.84923303e-01 -3.56281936e-01
-2.75165558e-01 6.42588437e-01 8.50787640e-01 5.77550292e-01
-3.33994657e-01 -3.94123226e-01 1.97595447e-01 -7.83349648e-02
3.47033262e-01 2.60982722e-01 -5.00778854e-01 -1.04800916e+00
2.27652684e-01 -4.65868324e-01 1.05295396e+00 -6.26104116e-01
-1.70221519e+00 1.25312462e-01 -1.38542861e-01 -8.21512461e-01
-2.12832376e-01 -7.68258512e-01 -5.49083292e-01 7.32278168e-01
-1.67010248e+00 -1.34201717e+00 -3.96606266e-01 2.85458744e-01
-2.65692890e-01 -2.86799252e-01 7.34848917e-01 3.43135327e-01
-7.57801235e-01 7.05777526e-01 3.21288586e-01 3.16780135e-02
8.59132886e-01 -1.28023577e+00 3.61788757e-02 3.24550122e-01
3.10108904e-02 6.36657119e-01 4.18481141e-01 -1.19652045e+00
-1.57620835e+00 -1.25124896e+00 9.50808942e-01 -2.52425849e-01
5.66275179e-01 -2.02444166e-01 -7.53125906e-01 7.92441547e-01
-2.88031191e-01 4.49879080e-01 9.19415176e-01 1.06850684e+00
-4.17063475e-01 -5.22534251e-01 -1.09996235e+00 1.87956065e-01
1.15786695e+00 -1.91736698e-01 -4.38041061e-01 7.15783656e-01
4.25038725e-01 -2.26965442e-01 -1.24721181e+00 6.76027954e-01
5.60346007e-01 -5.05099416e-01 1.16636825e+00 -1.11691654e+00
2.98026681e-01 -1.61842063e-01 4.14824784e-02 -1.44861686e+00
-5.48005521e-01 -4.96245205e-01 -8.59784007e-01 1.12446070e+00
7.85056055e-01 -6.88231945e-01 1.31949508e+00 4.25329298e-01
1.80754900e-01 -1.05651677e+00 -8.27041805e-01 -1.05492270e+00
-5.11075556e-01 -2.97699600e-01 6.26202226e-01 1.37995493e+00
5.33234417e-01 6.87152147e-01 -3.96040291e-01 -2.36661248e-02
1.05316508e+00 4.23471034e-01 7.78283298e-01 -1.65628171e+00
-5.72212219e-01 -3.58388275e-01 -7.00193048e-01 -7.79768646e-01
4.70327765e-01 -1.30523324e+00 -3.33138436e-01 -1.73323524e+00
4.17663872e-01 -6.54255331e-01 -4.48526174e-01 9.22863901e-01
-5.67265391e-01 3.72046560e-01 -2.24593505e-01 1.14941522e-01
-8.12608421e-01 6.06063306e-01 1.06417644e+00 -7.09929526e-01
-3.54017764e-01 2.16245487e-01 -9.84863043e-01 3.75123888e-01
6.07124329e-01 -4.65060830e-01 -3.48919302e-01 3.56459543e-02
4.23925877e-01 1.16741233e-01 4.60299313e-01 -5.46508551e-01
3.43840212e-01 -1.97013035e-01 7.50644743e-01 -6.54522121e-01
3.05475593e-01 -5.72116792e-01 1.92973286e-01 3.03029686e-01
-1.36874586e-01 -5.97610652e-01 -1.59702837e-01 8.56951952e-01
-2.83812732e-01 -2.92203993e-01 1.89451724e-01 2.13865429e-01
-7.23404586e-01 1.33471847e-01 4.46863741e-01 -1.57973886e-01
1.15758908e+00 -1.66902378e-01 -7.27956772e-01 -1.04895934e-01
-1.02519882e+00 6.68524086e-01 -6.01438917e-02 2.55598664e-01
4.92347330e-01 -1.50198770e+00 -6.07868195e-01 -1.41502032e-02
4.96093988e-01 5.40324859e-02 -1.85827404e-01 7.53363729e-01
-2.01286003e-01 5.46910167e-01 1.47983149e-01 -2.09637299e-01
-1.03810024e+00 7.18458772e-01 3.91519144e-02 -5.06184280e-01
-3.06849718e-01 9.55279648e-01 -3.93992543e-01 -3.01310629e-01
5.32089651e-01 2.63483316e-01 -1.40638858e-01 2.53369957e-01
1.71865553e-01 5.73723733e-01 5.18964171e-01 4.53246906e-02
-3.23597968e-01 7.70267621e-02 -3.55006248e-01 3.65498275e-01
1.52721524e+00 3.34956259e-01 -3.05563241e-01 -1.96842514e-02
9.31342602e-01 -3.26733500e-01 -8.27294886e-01 -4.90551323e-01
3.64808172e-01 -4.34059203e-01 3.13983589e-01 -1.20623577e+00
-9.70606446e-01 1.48998592e-02 2.16258869e-01 2.26956204e-01
7.56645203e-01 1.96525142e-01 3.32763374e-01 7.69863427e-01
4.30367261e-01 -1.29403663e+00 -1.79652348e-01 2.30474219e-01
6.95468485e-01 -1.48900068e+00 5.73181808e-01 -9.67670262e-01
-4.30387020e-01 1.00291944e+00 6.52226388e-01 3.05335999e-01
8.79312038e-01 -1.11065455e-01 -2.60239601e-01 -4.49171603e-01
-7.67897964e-01 -2.63686538e-01 6.56260550e-01 6.67068541e-01
1.59515947e-01 2.45848358e-01 -5.19469917e-01 8.95967484e-01
-1.75229043e-01 1.03053696e-01 -2.43210152e-01 1.10842466e+00
-2.49396622e-01 -1.33796287e+00 -3.76854897e-01 9.96802509e-01
-2.70921528e-01 4.14897166e-02 -6.53926611e-01 7.02745855e-01
1.47217676e-01 1.09320498e+00 -4.20792878e-01 -5.92272520e-01
3.43418330e-01 2.46303126e-01 4.42755103e-01 -3.72122437e-01
-3.46870035e-01 -2.34117210e-01 5.56028903e-01 -4.41728652e-01
-1.23447634e-01 -1.84285462e-01 -8.76843452e-01 -2.16103971e-01
-8.10849965e-01 1.85450509e-01 7.18296647e-01 8.29433262e-01
2.22314671e-01 5.79572201e-01 3.76783878e-01 -4.34849828e-01
-7.16408253e-01 -9.12013769e-01 -9.14507806e-01 4.56728101e-01
-9.84149203e-02 -9.29327786e-01 8.40705261e-02 -9.47452560e-02] | [8.813680648803711, 7.912006855010986] |
9598d837-f812-42ff-9e4b-1b8ab595d2fd | multi-perspective-scientific-document | null | null | https://aclanthology.org/2022.sdp-1.33 | https://aclanthology.org/2022.sdp-1.33.pdf | Multi Perspective Scientific Document Summarization With Graph Attention Networks (GATS) | It is well recognized that creating summaries of scientific texts can be difficult. For each given document, the majority of summarizing research believes there is only one best gold summary. Having just one gold summary limits our capacity to assess the effectiveness of summarizing algorithms because creating summaries is an art. Likewise, because it takes subject-matter experts a lot of time to read and comprehend lengthy scientific publications, annotating several gold summaries for scientific documents can be very expensive. The shared task known as the Multi perspective Scientific Document Summarization (Mup) is an exploration of various methods to produce multi perspective scientific summaries. Utilizing Graph Attention Networks (GATs), we take an extractive text summarization approach to the issue as a kind of sentence ranking task. Although the results produced by the suggested model are not particularly impressive, comparing them to the state-of-the-arts demonstrates the model’s potential for improvement. | ['Abbas Akkasi'] | null | null | null | null | sdp-coling-2022-10 | ['scientific-article-summarization', 'extractive-document-summarization', 'document-summarization'] | ['natural-language-processing', 'natural-language-processing', 'natural-language-processing'] | [ 5.17089784e-01 6.08391404e-01 -2.07428873e-01 -2.76474297e-01
-1.43022585e+00 -6.77457809e-01 8.44510674e-01 9.33447301e-01
-2.24951804e-01 9.40126836e-01 8.90120327e-01 -5.67654252e-01
-1.79049745e-01 -6.16771817e-01 -6.49848461e-01 -3.81341428e-01
3.56838524e-01 7.07918346e-01 -2.30458856e-01 -1.17529154e-01
1.03315926e+00 4.64320213e-01 -1.01222980e+00 2.05355957e-01
1.28183877e+00 2.44473889e-01 3.47528309e-01 9.79010880e-01
-5.38372874e-01 6.90321982e-01 -1.35914648e+00 -6.12389863e-01
-3.02999407e-01 -6.44995749e-01 -9.91115570e-01 -2.73612201e-01
1.03545642e+00 1.12562053e-01 -1.46393934e-02 1.03198206e+00
6.07300162e-01 2.60284424e-01 8.53653431e-01 -8.52459013e-01
-1.01207769e+00 9.87708807e-01 -5.09122252e-01 4.61347789e-01
4.96687979e-01 -1.55937850e-01 1.33160710e+00 -5.44528425e-01
8.26573908e-01 1.32599723e+00 5.38886905e-01 4.07442421e-01
-1.06647503e+00 -2.36231133e-01 -1.19161475e-02 -1.87109470e-01
-6.91087067e-01 -5.64648867e-01 6.61979675e-01 -2.71440804e-01
9.51804698e-01 6.51997805e-01 6.28006220e-01 8.64663661e-01
6.79965079e-01 4.35628057e-01 7.78847396e-01 -2.76988417e-01
2.37579256e-01 -1.59138799e-01 6.55278027e-01 4.31489110e-01
1.11031473e+00 -8.15854847e-01 -6.30169034e-01 -2.86893874e-01
5.12572043e-02 -2.76335150e-01 -3.91145468e-01 3.08832139e-01
-1.32109666e+00 8.17285478e-01 6.88131452e-02 4.23868924e-01
-4.70801890e-01 1.64893493e-01 7.19565034e-01 1.20087087e-01
8.38474631e-01 1.35770464e+00 1.12468034e-01 -1.61538273e-01
-1.54918134e+00 5.05978465e-01 1.09307897e+00 7.82175481e-01
1.10772736e-01 1.23874106e-01 -5.52349508e-01 5.35821021e-01
6.82870373e-02 2.69385934e-01 3.58913928e-01 -1.04292190e+00
5.84488273e-01 6.24092519e-01 1.83489412e-01 -1.37187541e+00
-3.50220233e-01 -6.74289227e-01 -7.73342907e-01 -6.49883449e-02
2.72993267e-01 -1.11864336e-01 -7.30401754e-01 1.32477415e+00
-1.83959320e-01 -2.92227834e-01 8.31104591e-02 5.17024636e-01
1.50777066e+00 1.01550972e+00 1.72054857e-01 -5.05679250e-01
1.25772774e+00 -1.13780940e+00 -8.61392617e-01 -3.00962240e-01
4.09406126e-01 -8.48065257e-01 9.27956104e-01 3.46706599e-01
-1.58523762e+00 -4.19124514e-01 -1.26017594e+00 -5.71271896e-01
-4.09081161e-01 -4.53960849e-03 5.28633058e-01 2.40676254e-01
-1.40690494e+00 1.10051942e+00 -5.04515350e-01 -5.33105552e-01
5.01803517e-01 1.23144068e-01 -2.88158029e-01 -5.04639447e-02
-7.42519021e-01 1.17122018e+00 2.41354778e-01 -1.04511201e-01
-5.88562071e-01 -9.02154326e-01 -6.14575267e-01 3.61705869e-01
1.91888809e-01 -1.11741686e+00 1.13443947e+00 -3.49662960e-01
-1.18270755e+00 7.61477411e-01 -3.66578013e-01 -4.21596110e-01
4.08113301e-01 -1.41390488e-01 -1.76085141e-02 2.68452853e-01
4.27244484e-01 2.68730670e-01 2.07818449e-01 -1.20548785e+00
-1.92139268e-01 -3.71497691e-01 -1.89457476e-01 4.16195244e-01
-1.58974111e-01 2.52656907e-01 -1.31707519e-01 -5.69461465e-01
-3.15464765e-01 -3.84107351e-01 -3.52211833e-01 -5.96171975e-01
-8.31345439e-01 -5.87440372e-01 4.49773163e-01 -1.03160226e+00
1.29184985e+00 -1.54194641e+00 3.56029421e-01 -3.03544968e-01
5.80938995e-01 6.63706064e-02 -3.36590946e-01 8.38247359e-01
1.52750924e-01 7.40172505e-01 -2.24330962e-01 -5.98979592e-01
3.86821404e-02 -1.55130342e-01 -4.00458455e-01 1.63722590e-01
6.36490136e-02 9.91182923e-01 -1.27226222e+00 -4.76446390e-01
-2.15197146e-01 4.83465493e-01 -1.45401135e-02 -5.03562987e-02
-3.35590661e-01 2.78001815e-01 -6.45195663e-01 3.04216504e-01
2.69552320e-01 -6.61698163e-01 1.49645582e-01 -1.30559564e-01
-3.62786323e-01 6.88274443e-01 -5.07343233e-01 1.72776330e+00
-2.02279344e-01 1.03272164e+00 -3.25374395e-01 -1.00175047e+00
8.18765402e-01 3.30766022e-01 1.50733739e-01 -2.49077007e-01
2.35269181e-02 2.36392349e-01 3.30216847e-02 -3.08299273e-01
1.15342724e+00 -6.08349731e-03 -6.68928623e-02 7.86004782e-01
4.03621756e-02 -6.57570481e-01 8.69820297e-01 8.30153346e-01
1.33868980e+00 -1.19267359e-01 3.39189202e-01 -5.71272671e-01
1.91491216e-01 5.37815094e-01 2.32473865e-01 1.26383793e+00
1.77855819e-01 7.40522861e-01 8.72749984e-01 -1.62995338e-01
-1.35033000e+00 -6.80560231e-01 2.51774490e-01 8.69034410e-01
-2.82957286e-01 -7.01995015e-01 -7.84484386e-01 -4.41195607e-01
-1.83655694e-01 1.32562172e+00 -6.22912884e-01 1.32137224e-01
-4.17836100e-01 -7.35290110e-01 5.42675912e-01 2.84682870e-01
1.52373001e-01 -1.12892950e+00 -6.97498322e-01 2.16764331e-01
-2.36560389e-01 -7.44680345e-01 -6.78486049e-01 -1.07951857e-01
-9.85777080e-01 -8.64903390e-01 -1.05877841e+00 -6.08462512e-01
6.78671360e-01 4.70501035e-01 1.44573128e+00 6.26633391e-02
-1.07210137e-01 3.34985286e-01 -1.78321242e-01 -7.80517519e-01
-9.10393238e-01 2.11081520e-01 -2.67291516e-01 -8.07115376e-01
8.59401897e-02 -3.90241623e-01 -4.45482582e-01 -7.64212072e-01
-8.63767207e-01 2.11921006e-01 7.63427556e-01 6.01053178e-01
4.85309184e-01 -2.16835484e-01 9.44555521e-01 -1.22338033e+00
1.41979718e+00 -3.88864696e-01 -7.42368475e-02 5.61209738e-01
-6.67106807e-01 7.74823427e-02 7.83522546e-01 -1.49659505e-02
-1.00904977e+00 -7.03725874e-01 1.70694843e-01 1.86575100e-01
1.09717846e-01 1.08372653e+00 2.70390391e-01 1.88617498e-01
7.43011832e-01 1.34176880e-01 -6.30190820e-02 -4.24801946e-01
5.03928959e-01 3.92665446e-01 5.33852994e-01 -2.30002612e-01
3.94548327e-01 9.16852728e-02 1.20338358e-01 -1.08695722e+00
-1.31066632e+00 -3.23696524e-01 -2.40992740e-01 -1.89292237e-01
9.14663374e-01 -5.64917743e-01 -5.47628760e-01 -1.96007043e-01
-1.59333050e+00 -1.86291821e-02 -4.03230160e-01 1.67888448e-01
-3.80806148e-01 6.53456330e-01 -5.78119099e-01 -5.42167723e-01
-1.07579637e+00 -1.01117063e+00 9.31001902e-01 4.75919306e-01
-7.42352188e-01 -1.13818789e+00 1.80439487e-01 5.87907016e-01
4.84714121e-01 5.49780667e-01 1.16042268e+00 -1.05588937e+00
-3.12320441e-01 -3.76525313e-01 -2.96862423e-01 7.94550925e-02
1.39900491e-01 3.94466221e-01 -7.19863415e-01 -1.37984484e-01
-1.58742279e-01 -1.50720328e-01 9.68019068e-01 6.94709420e-01
1.00276887e+00 -7.24133015e-01 -3.25539410e-01 -9.25178304e-02
1.32444990e+00 1.87168702e-01 4.93108511e-01 2.34940007e-01
8.78047466e-01 6.72658265e-01 1.25573665e-01 6.79138228e-02
4.38624769e-01 9.56537724e-02 -6.22788705e-02 1.54292881e-01
-4.82164472e-01 -1.77719444e-01 1.37126878e-01 1.42433155e+00
-1.93931207e-01 -7.44419098e-01 -9.59751129e-01 6.89343333e-01
-1.62545562e+00 -1.27224994e+00 -3.33877593e-01 2.05259395e+00
7.71739960e-01 1.25147909e-01 -5.84074408e-02 -1.53457969e-01
5.66145003e-01 5.48475862e-01 -2.51973093e-01 -8.78259420e-01
-1.77926525e-01 1.87675104e-01 2.87058800e-01 5.36369503e-01
-6.26339972e-01 5.95476329e-01 6.83824968e+00 7.85001516e-01
-8.96526158e-01 -2.03095630e-01 8.09199512e-01 -3.52571271e-02
-7.56124735e-01 8.42177942e-02 -5.29927433e-01 4.18790519e-01
1.26868927e+00 -1.03630090e+00 4.03003991e-02 5.83164394e-01
4.49535608e-01 -3.21173102e-01 -1.08392763e+00 5.29853284e-01
5.49027503e-01 -1.83692038e+00 5.89927077e-01 -1.08656488e-01
8.56493592e-01 -3.34164058e-03 -2.73414940e-01 4.64855433e-02
5.49813449e-01 -1.31352031e+00 4.41092789e-01 6.53373480e-01
4.65387136e-01 -7.60750651e-01 7.55966544e-01 1.41590238e-01
-5.47543645e-01 3.82884651e-01 -5.89780688e-01 1.75698486e-03
2.73430169e-01 8.51438940e-01 -7.10248351e-01 9.07538533e-01
2.67978996e-01 8.54213893e-01 -8.38676691e-01 1.17793882e+00
-2.60941803e-01 7.05248356e-01 2.01994225e-01 -5.70204556e-01
2.66230762e-01 -3.97822171e-01 9.27791774e-01 1.43512821e+00
6.11735642e-01 1.44302040e-01 -5.95933311e-02 7.98666596e-01
-4.78609920e-01 3.74002635e-01 -9.63349402e-01 -8.40450346e-01
3.48481387e-01 1.32275367e+00 -1.00160313e+00 -7.55386353e-01
-7.48503655e-02 7.14390874e-01 3.17777663e-01 2.22293317e-01
-2.36704975e-01 -6.74490511e-01 -9.81751457e-02 -3.03106725e-01
-1.62393689e-01 -9.77412090e-02 -1.01079905e+00 -9.68369961e-01
-1.70323998e-01 -8.91701579e-01 2.90357590e-01 -1.08406711e+00
-1.12462568e+00 5.99429488e-01 -2.24479452e-01 -7.07862496e-01
5.35113700e-02 -1.06222965e-01 -1.10500920e+00 8.04263711e-01
-1.24623299e+00 -8.20975780e-01 -2.04672381e-01 -5.60282111e-01
7.93537974e-01 7.63802975e-02 6.96162343e-01 -1.04972221e-01
-4.33176249e-01 1.44925445e-01 2.49663606e-01 -3.71884674e-01
7.88345158e-01 -1.51638281e+00 7.09013581e-01 7.73142040e-01
1.59706876e-01 7.97211051e-01 1.29272938e+00 -1.00098169e+00
-1.37403691e+00 -8.96328449e-01 1.58015561e+00 -6.69236243e-01
6.98353648e-01 2.69037247e-01 -1.08848834e+00 5.27787805e-01
8.90768290e-01 -9.30038810e-01 7.73590088e-01 8.48842487e-02
-3.12339943e-02 2.23915264e-01 -7.24086106e-01 8.42490733e-01
8.78524423e-01 -2.95329504e-02 -9.51493204e-01 7.90796697e-01
7.61685431e-01 -2.66478777e-01 -9.22886968e-01 -8.08227658e-02
3.01277608e-01 -6.12337053e-01 7.33101368e-01 -7.09882915e-01
1.25856054e+00 -5.48906438e-02 3.68286043e-01 -1.78945994e+00
-3.90470624e-01 -6.87946498e-01 1.25128999e-01 1.26687121e+00
6.42161489e-01 -4.25330460e-01 5.91715693e-01 7.78090954e-01
-7.05235362e-01 -5.94536185e-01 -5.13178229e-01 -5.18203676e-01
3.85518610e-01 1.59934551e-01 3.78613442e-01 9.47563648e-01
3.25294465e-01 9.03219044e-01 -7.26553202e-02 -3.11529785e-01
7.95278490e-01 3.06842953e-01 6.76267982e-01 -1.56105852e+00
1.08953185e-01 -9.30319905e-01 2.51403637e-02 -4.45482552e-01
1.85417846e-01 -1.20967579e+00 8.06026831e-02 -2.78245187e+00
6.63987935e-01 1.78247288e-01 -7.82671571e-02 2.19338208e-01
-4.56017405e-01 1.46022663e-02 2.27948874e-01 1.38757721e-01
-7.69972026e-01 2.47779891e-01 1.51918757e+00 -4.51161921e-01
-5.04342802e-02 -3.57444853e-01 -1.44152653e+00 5.26806474e-01
8.19477975e-01 -5.45107782e-01 -3.37931842e-01 -4.85641092e-01
5.28723657e-01 2.15420812e-01 3.58782299e-02 -8.26662004e-01
5.21249831e-01 -1.48676679e-01 2.16668963e-01 -6.87083423e-01
-4.09888998e-02 2.33155876e-01 9.48696956e-02 3.36358309e-01
-8.25488567e-01 3.70210081e-01 3.54863286e-01 5.47833562e-01
-9.30318832e-02 -4.78887528e-01 4.09272492e-01 -5.02754092e-01
-6.31965743e-03 -9.50315073e-02 -4.19416338e-01 3.95475626e-01
4.64524835e-01 -9.78830606e-02 -8.82278800e-01 -5.77683389e-01
-9.54582617e-02 2.80762166e-01 4.82156307e-01 1.27909020e-01
4.97929037e-01 -7.11019099e-01 -1.11561310e+00 -7.96689212e-01
-1.40181392e-01 5.96011616e-02 2.98686057e-01 5.72850704e-01
-8.09749126e-01 6.95174515e-01 -1.31661668e-01 1.10514369e-02
-1.26591837e+00 3.77700716e-01 -2.87620008e-01 -6.74307644e-01
-8.37044120e-01 7.59240687e-01 -5.13425842e-02 1.12596285e-02
-1.02482818e-01 -9.08037797e-02 -6.32137239e-01 2.36644626e-01
7.43721664e-01 7.17328966e-01 8.77640471e-02 -3.16490799e-01
-4.39517722e-02 2.93771774e-01 -3.16787213e-01 -1.38132855e-01
1.59259593e+00 6.17004149e-02 -5.83923817e-01 6.32848740e-01
8.57251883e-01 2.13159442e-01 -6.07761204e-01 3.87815446e-01
2.17775717e-01 -6.86988235e-02 1.07875034e-01 -9.93859112e-01
-5.41663826e-01 9.25725937e-01 -4.01603937e-01 5.87603450e-01
4.24517870e-01 -1.85052171e-01 6.63489044e-01 5.77555716e-01
-9.74134356e-02 -1.13533747e+00 -1.15449261e-02 3.97201955e-01
1.27224898e+00 -1.10120642e+00 7.60208964e-01 -1.22529991e-01
-7.10608363e-01 1.21442056e+00 1.82273805e-01 -7.80614987e-02
-6.76818863e-02 -1.32101119e-01 -7.59724826e-02 -6.35594547e-01
-8.14988315e-01 4.58286703e-01 5.85536182e-01 2.33710960e-01
8.20081651e-01 8.19415879e-03 -9.03765798e-01 2.12254331e-01
-4.04535055e-01 -1.19356602e-01 1.28924990e+00 6.44996583e-01
-5.90831935e-01 -7.53116250e-01 -1.31580517e-01 1.04993892e+00
-8.32987010e-01 -2.46507004e-01 -7.43738115e-01 5.97876012e-01
-7.85589814e-01 1.25569499e+00 -4.98095378e-02 2.68750757e-01
1.67488694e-01 8.08234960e-02 4.41167384e-01 -1.01927364e+00
-8.86490524e-01 -2.04040989e-01 4.42000180e-01 -2.55065691e-02
-4.46247965e-01 -4.18000609e-01 -1.08836758e+00 -6.33726478e-01
-5.04825599e-02 6.60292923e-01 7.74111450e-01 8.30090702e-01
6.59676731e-01 1.04164386e+00 -3.80777195e-02 -9.19747055e-01
-5.64536870e-01 -1.03087783e+00 -3.64036649e-01 2.79936731e-01
1.96026534e-01 -1.29558280e-01 -2.85609275e-01 1.15566589e-01] | [12.438920974731445, 9.610702514648438] |
09d21ee9-c3f2-4cf7-970f-9fe64e87bcbe | my-way-of-telling-a-story-persona-based | 1906.06401 | null | https://arxiv.org/abs/1906.06401v1 | https://arxiv.org/pdf/1906.06401v1.pdf | "My Way of Telling a Story": Persona based Grounded Story Generation | Visual storytelling is the task of generating stories based on a sequence of images. Inspired by the recent works in neural generation focusing on controlling the form of text, this paper explores the idea of generating these stories in different personas. However, one of the main challenges of performing this task is the lack of a dataset of visual stories in different personas. Having said that, there are independent datasets for both visual storytelling and annotated sentences for various persona. In this paper we describe an approach to overcome this by getting labelled persona data from a different task and leveraging those annotations to perform persona based story generation. We inspect various ways of incorporating personality in both the encoder and the decoder representations to steer the generation in the target direction. To this end, we propose five models which are incremental extensions to the baseline model to perform the task at hand. In our experiments we use five different personas to guide the generation process. We find that the models based on our hypotheses perform better at capturing words while generating stories in the target persona. | ['Alan W. black', 'Khyathi Raghavi Chandu', 'Shrimai Prabhumoye', 'Ruslan Salakhutdinov'] | 2019-06-14 | null | null | null | null | ['visual-storytelling'] | ['natural-language-processing'] | [ 2.81071782e-01 5.23934066e-01 2.70480335e-01 -5.01848936e-01
-5.94605744e-01 -5.43815911e-01 1.23037577e+00 -2.71173716e-01
1.06303710e-02 7.34109044e-01 9.62773085e-01 8.21076706e-02
4.40427154e-01 -7.97850311e-01 -6.85039818e-01 -3.81282240e-01
5.54488897e-01 7.40644574e-01 6.68406412e-02 -3.86208177e-01
4.28361535e-01 9.83892903e-02 -1.41323376e+00 1.01223660e+00
5.07258892e-01 3.27547908e-01 3.71006638e-01 9.63875473e-01
-1.78229257e-01 1.15780401e+00 -9.99248028e-01 -6.64062262e-01
4.43062223e-02 -1.07948589e+00 -8.70391011e-01 5.33982337e-01
5.41427076e-01 -4.24596578e-01 -2.74480909e-01 5.13453960e-01
7.08008707e-01 8.76348466e-02 1.07100391e+00 -1.28015041e+00
-9.42791224e-01 1.07208169e+00 -4.83024985e-01 -2.18430966e-01
8.05516005e-01 2.51998752e-01 6.88592196e-01 -9.19435501e-01
9.76463616e-01 1.52656543e+00 4.11628932e-01 1.12790954e+00
-1.19505024e+00 -3.35877746e-01 1.40592352e-01 -4.13043983e-02
-1.18965518e+00 -6.03377283e-01 7.53177166e-01 -6.99932218e-01
7.65565217e-01 8.37101489e-02 9.11763072e-01 1.72727036e+00
-1.95226297e-01 1.03324485e+00 1.03900802e+00 -7.07682848e-01
1.05323322e-01 3.58853370e-01 -2.88144946e-01 4.06043261e-01
-2.55222227e-02 2.16191206e-02 -8.44100952e-01 1.67964529e-02
9.00069654e-01 -4.12467569e-01 -1.10072032e-01 -3.58369887e-01
-1.47501278e+00 1.03741324e+00 1.84086680e-01 1.87406138e-01
-3.43013257e-01 3.24556321e-01 3.38251829e-01 5.39432792e-03
3.79096597e-01 7.89804459e-01 3.33866179e-01 -6.07102439e-02
-1.16359782e+00 1.02394509e+00 7.54347265e-01 1.18221962e+00
3.18748057e-01 7.63436481e-02 -1.07081091e+00 7.08104014e-01
2.41850361e-01 1.68328673e-01 4.28080320e-01 -6.66087210e-01
7.01145291e-01 4.74628180e-01 4.09501195e-01 -7.36303568e-01
-5.44485822e-02 8.67782161e-02 -5.05537391e-01 2.31259733e-01
6.06507719e-01 -3.09706956e-01 -1.25893736e+00 1.63778472e+00
5.42521626e-02 -2.15495855e-01 1.39394641e-01 8.73610318e-01
9.05479014e-01 9.47195530e-01 8.05929676e-02 1.81468382e-01
1.50724411e+00 -1.10569870e+00 -7.17789412e-01 -4.30117846e-01
3.27615291e-01 -8.07468891e-01 1.15699804e+00 1.89864442e-01
-1.35421884e+00 -7.49970555e-01 -1.09350216e+00 -3.75610620e-01
-2.80143410e-01 2.17340603e-01 3.11309665e-01 4.12750959e-01
-1.14184630e+00 3.14440280e-01 -3.08009505e-01 -7.28004336e-01
3.93698066e-01 -3.46323013e-01 -1.10432036e-01 -7.40120336e-02
-1.14379621e+00 1.05408025e+00 5.35446227e-01 -1.76541775e-01
-1.18871057e+00 -2.20843062e-01 -9.10221398e-01 -2.55863637e-01
1.81098267e-01 -1.17348802e+00 1.47722733e+00 -1.09914303e+00
-1.24708986e+00 9.64994729e-01 -2.49321371e-01 -5.20901442e-01
9.68980312e-01 -1.35599837e-01 1.11412823e-01 -3.19620669e-02
3.48325521e-01 1.28480375e+00 8.99990201e-01 -1.55705214e+00
-4.36038405e-01 -1.97380811e-01 1.92386031e-01 4.90452975e-01
-1.18005700e-01 1.33519202e-01 -3.97427976e-01 -9.29887116e-01
-4.96767998e-01 -8.22654068e-01 -2.96584159e-01 -2.91700125e-01
-7.73713291e-01 -2.72834986e-01 5.99512875e-01 -7.13368237e-01
9.49125290e-01 -1.75644350e+00 5.08469641e-01 -1.06459945e-01
1.73738405e-01 -5.60942106e-02 -1.40487939e-01 8.83091271e-01
5.11915237e-02 1.89379022e-01 -2.03628447e-02 -6.86356664e-01
-7.27928989e-03 -1.79361165e-01 -4.71714944e-01 -1.61415204e-01
3.33713740e-01 9.63269949e-01 -8.78023446e-01 -7.08830118e-01
7.88319949e-03 6.56347930e-01 -3.72681290e-01 5.17681956e-01
-5.68331659e-01 5.80130756e-01 -4.05964226e-01 1.63601428e-01
7.41517544e-02 -6.33569285e-02 2.50407457e-02 8.92531052e-02
-9.56552699e-02 2.93252915e-01 -9.56738174e-01 1.79848409e+00
-3.04003775e-01 9.08073843e-01 -4.77142543e-01 -4.76180345e-01
1.01497710e+00 6.57168627e-01 -1.27442822e-01 -2.72207141e-01
3.82235944e-02 -1.61455899e-01 -1.63198739e-01 -6.73759222e-01
8.46146345e-01 -4.74985480e-01 -3.44804645e-01 7.65197873e-01
-1.59002542e-02 -5.01238227e-01 5.52356958e-01 4.51474994e-01
7.71557927e-01 5.28362691e-01 2.99240261e-01 9.73775908e-02
1.66055039e-01 2.58007288e-01 -1.37288168e-01 1.00998569e+00
9.02236998e-02 1.20044684e+00 5.21831930e-01 -4.32069600e-01
-1.56854141e+00 -8.64458978e-01 4.06870425e-01 8.94222558e-01
-2.49723375e-01 -6.32221520e-01 -9.84676778e-01 -4.83620882e-01
-4.07036811e-01 1.23138177e+00 -8.44940066e-01 4.59773876e-02
-6.52965069e-01 -3.28832865e-01 5.63825548e-01 6.04057193e-01
4.19617593e-01 -1.48107088e+00 -9.04925823e-01 1.02883391e-01
-4.65881884e-01 -9.71075296e-01 -4.97008562e-01 -4.77665216e-01
-3.35979015e-01 -5.47146857e-01 -1.26776814e+00 -7.75690556e-01
7.49321699e-01 1.83969676e-01 1.23170161e+00 -1.73485443e-01
-3.94983552e-02 3.30570936e-01 -5.71219921e-01 -9.17164385e-01
-8.53842795e-01 1.70216620e-01 -5.06826162e-01 -1.99613683e-02
1.09179206e-01 -2.59114683e-01 -4.11700249e-01 -7.22642615e-02
-9.75014865e-01 1.06301630e+00 4.24138963e-01 5.70882857e-01
7.32984617e-02 -1.50863960e-01 4.38980073e-01 -9.96228933e-01
1.01612103e+00 -4.39307183e-01 1.82120483e-02 1.79890171e-01
-1.50789514e-01 6.31952435e-02 4.77041662e-01 -4.00380522e-01
-1.27711105e+00 1.76835924e-01 1.46372184e-01 -1.61642015e-01
-2.84701347e-01 1.49477348e-01 -1.20663881e-01 7.84011424e-01
7.00588942e-01 1.48165628e-01 -1.61033705e-01 -1.38329864e-01
7.51834154e-01 5.84867775e-01 3.40113759e-01 -4.23236787e-01
8.68152142e-01 3.92975986e-01 -4.59295899e-01 -5.03066003e-01
-8.65346193e-01 -9.92364716e-03 -4.67560887e-01 -8.33988309e-01
1.23343146e+00 -9.35538471e-01 -1.43521219e-01 4.55930650e-01
-1.56893635e+00 -4.86982971e-01 -4.04402614e-01 -3.56846936e-02
-1.01945090e+00 -1.42900363e-01 -3.07872891e-01 -9.09179270e-01
-1.88625470e-01 -1.00916111e+00 1.28317058e+00 2.98514038e-01
-8.18832517e-01 -7.35991180e-01 2.22436622e-01 5.52876234e-01
2.63528645e-01 5.62946022e-01 7.10455000e-01 -3.85255396e-01
-4.98349637e-01 -1.68247923e-01 -1.11466847e-01 -1.40715227e-01
-1.51756005e-02 -1.18075229e-01 -9.66807485e-01 -3.90097761e-04
-1.13901459e-01 -6.23008966e-01 8.70717645e-01 2.64515281e-01
7.94514894e-01 -3.71634871e-01 -3.12032074e-01 1.74147606e-01
1.08066118e+00 2.83579439e-01 9.57729697e-01 2.74663478e-01
9.99285221e-01 1.07665527e+00 6.43926382e-01 3.81672591e-01
7.51774907e-01 8.63020718e-01 8.32743570e-02 -1.01120040e-01
-4.79935259e-01 -9.34363782e-01 5.47091067e-01 2.05419362e-01
-3.58344823e-01 -6.62937284e-01 -8.52957487e-01 9.90984857e-01
-2.04136252e+00 -1.44856894e+00 -1.36885002e-01 1.82260132e+00
8.63557756e-01 -8.38889182e-02 5.73420584e-01 8.91438685e-03
8.28684509e-01 4.68871564e-01 -1.27623975e-01 -6.58517063e-01
-1.14545308e-01 -3.60198021e-01 1.40272364e-01 4.42281157e-01
-8.55421603e-01 1.06402886e+00 6.54500771e+00 4.48035657e-01
-8.68312299e-01 -7.08628744e-02 7.85975337e-01 -4.04255062e-01
-4.43882406e-01 9.05571878e-02 -8.45216274e-01 3.37260425e-01
7.91752160e-01 -2.46544614e-01 3.49262238e-01 7.16518819e-01
6.09998286e-01 3.52304392e-02 -1.25241625e+00 7.78469384e-01
6.97868645e-01 -1.42752731e+00 4.75376099e-01 -1.86633646e-01
9.35690045e-01 -7.60255754e-01 -2.57053394e-02 2.27228761e-01
5.81266165e-01 -1.30279207e+00 1.49849796e+00 7.11317003e-01
6.70085788e-01 -6.87497318e-01 3.47759813e-01 3.15007895e-01
-6.51874304e-01 1.50412172e-01 -1.91526666e-01 -2.25251168e-01
6.77305102e-01 2.49983028e-01 -1.42034733e+00 2.21413359e-01
4.31607574e-01 5.37546217e-01 -6.19605184e-01 7.15831697e-01
-4.81236815e-01 3.23041171e-01 4.47436064e-01 -2.39454865e-01
1.12659752e-01 9.60333496e-02 6.12512529e-01 1.24340844e+00
4.77989972e-01 -1.52963042e-01 1.51429191e-01 1.18357301e+00
8.62109214e-02 1.05506729e-03 -1.02204645e+00 -2.94818372e-01
1.81835011e-01 1.05959308e+00 -7.40340710e-01 -5.34461737e-01
-2.96258986e-01 1.27803373e+00 3.17397535e-01 2.96118796e-01
-8.63502502e-01 -2.29788885e-01 -3.80725078e-02 6.24946296e-01
2.54983068e-01 -1.10145226e-01 -3.38628709e-01 -9.96814728e-01
-1.15785532e-01 -9.59629059e-01 7.40803108e-02 -1.55922139e+00
-1.19686103e+00 6.49751604e-01 4.40780967e-01 -8.95153046e-01
-7.54996717e-01 -2.51217395e-01 -8.48925769e-01 9.08020735e-01
-9.25730824e-01 -1.68337023e+00 -3.97641987e-01 3.50628734e-01
1.11146641e+00 -1.14120908e-01 5.83221436e-01 -2.28191197e-01
-2.42887288e-01 2.17528895e-01 -6.16028666e-01 1.50791854e-01
8.97637963e-01 -1.31760943e+00 8.69770885e-01 9.77914333e-01
3.31416667e-01 4.33927745e-01 1.13828242e+00 -9.16769385e-01
-7.94187903e-01 -9.72409844e-01 1.26897657e+00 -7.16923058e-01
3.47225308e-01 -7.38901913e-01 -4.83645260e-01 8.99878323e-01
7.77730048e-01 -9.70374823e-01 5.36236823e-01 -1.80301383e-01
-2.36726582e-01 5.08100629e-01 -8.93647611e-01 1.10998821e+00
1.16352737e+00 -2.31621534e-01 -6.66767597e-01 3.09003592e-01
6.41093910e-01 -4.58341867e-01 -2.88616896e-01 -1.48077220e-01
5.27507007e-01 -1.04121161e+00 8.17183316e-01 -7.09390879e-01
1.30736291e+00 -4.27170336e-01 2.19477549e-01 -1.52483296e+00
-4.12255645e-01 -5.77017367e-01 6.85025901e-02 1.59454024e+00
4.83938009e-01 -2.03938386e-03 7.52182126e-01 4.93505865e-01
-7.86489099e-02 -2.92717606e-01 -3.38690370e-01 -3.41430664e-01
-2.80720647e-03 -2.70280689e-01 5.66229761e-01 5.71097314e-01
-3.23052146e-02 8.20395172e-01 -9.44167554e-01 -4.25594300e-01
3.39417577e-01 -6.76850497e-04 1.19695568e+00 -8.27437341e-01
-3.78394008e-01 -1.75226182e-01 -2.04029784e-01 -8.18954468e-01
-1.48304448e-01 -8.10403287e-01 3.50481868e-01 -2.11634707e+00
6.95477784e-01 1.45107716e-01 4.57319677e-01 3.63748401e-01
-3.63851905e-01 3.42657804e-01 7.02754200e-01 1.05791695e-01
-4.81662065e-01 4.32534665e-01 1.59872043e+00 -8.77751261e-02
-1.49430349e-01 -1.21415488e-01 -1.16501856e+00 6.70716584e-01
8.62172365e-01 -3.16787779e-01 -7.69118905e-01 -6.63102031e-01
4.02649701e-01 1.09837867e-01 6.66932166e-01 -9.83539581e-01
-4.26442772e-02 -2.43379280e-01 7.51320541e-01 -6.78087473e-01
5.89945912e-01 -1.91968843e-01 2.20949054e-01 9.50337052e-02
-8.73238623e-01 2.14768678e-01 -7.27787390e-02 4.14243191e-01
-5.34480959e-02 -2.95137823e-01 6.19284213e-01 -6.11840844e-01
-4.20481801e-01 -6.50985315e-02 -6.69792056e-01 7.45620057e-02
1.10070586e+00 -5.42821586e-01 -3.43628764e-01 -1.14279628e+00
-6.62037611e-01 1.75517902e-01 7.55770087e-01 7.04526007e-01
7.29775608e-01 -1.56726635e+00 -1.21639788e+00 -1.57012969e-01
3.34410489e-01 3.62894200e-02 1.35784641e-01 1.47534087e-01
-4.68789637e-01 3.48760277e-01 -4.12986875e-01 -2.88652390e-01
-1.23716986e+00 4.61949319e-01 1.76124126e-01 -3.12035531e-01
-5.25056303e-01 8.77317786e-01 4.59633887e-01 3.37535553e-02
-4.70723696e-02 3.03391993e-01 -5.66572547e-01 1.70650765e-01
9.11702096e-01 2.13830456e-01 -5.17538369e-01 -8.38980556e-01
2.36589685e-01 2.28165224e-01 -2.78847277e-01 -8.58771384e-01
1.32452786e+00 -1.41395703e-01 2.68869072e-01 7.64810324e-01
5.88641882e-01 2.64544357e-02 -1.45012152e+00 2.70421535e-01
-8.94227177e-02 -4.26852942e-01 -4.90453452e-01 -1.01031935e+00
-6.61232710e-01 8.59454095e-01 1.61484122e-01 3.72455329e-01
7.96951950e-01 3.40648293e-01 5.89708328e-01 -1.77188694e-01
2.53073573e-01 -1.07190859e+00 4.04732108e-01 3.60504508e-01
1.54566026e+00 -9.77549076e-01 -5.75061031e-02 -2.49029607e-01
-1.31734264e+00 1.01679778e+00 7.83877850e-01 -1.23189658e-01
-2.04572365e-01 -3.30490731e-02 1.57599345e-01 -3.33506078e-01
-8.98933113e-01 -1.84845850e-01 2.76950121e-01 9.01125014e-01
7.57983387e-01 4.33976203e-02 -3.86177599e-01 4.54185665e-01
-6.64630055e-01 4.56439564e-03 8.98286402e-01 7.36977875e-01
-1.86352924e-01 -1.09679365e+00 -6.03747666e-01 2.85633415e-01
-2.52003521e-01 3.80594879e-02 -1.07836509e+00 6.78721130e-01
1.09218724e-01 1.05541515e+00 1.83366276e-02 -1.75061345e-01
3.41111511e-01 2.92879313e-01 7.06597447e-01 -9.70535755e-01
-5.33355236e-01 -8.48173723e-02 5.60284555e-01 -1.85287669e-01
-4.91560698e-01 -9.27217543e-01 -9.17723179e-01 -1.23413481e-01
1.30280674e-01 -1.87435761e-01 4.54671502e-01 8.55722964e-01
1.03440076e-01 5.14358640e-01 3.02625090e-01 -1.18837810e+00
-1.02342792e-01 -1.17624259e+00 -1.83646798e-01 8.21771502e-01
-6.32915795e-02 -4.25241321e-01 3.46356928e-02 5.15939415e-01] | [11.165410041809082, 0.7519330978393555] |
2319434f-87d7-4dc3-95b2-3f00e472f1d6 | digital-twin-tracking-dataset-dttd-a-new-rgb | 2302.05991 | null | https://arxiv.org/abs/2302.05991v2 | https://arxiv.org/pdf/2302.05991v2.pdf | Digital Twin Tracking Dataset (DTTD): A New RGB+Depth 3D Dataset for Longer-Range Object Tracking Applications | Digital twin is a problem of augmenting real objects with their digital counterparts. It can underpin a wide range of applications in augmented reality (AR), autonomy, and UI/UX. A critical component in a good digital-twin system is real-time, accurate 3D object tracking. Most existing works solve 3D object tracking through the lens of robotic grasping, employ older generations of depth sensors, and measure performance metrics that may not apply to other digital-twin applications such as in AR. In this work, we create a novel RGB-D dataset, called Digital Twin Tracking Dataset (DTTD), to enable further research of the problem and extend potential solutions towards longer ranges and mm localization accuracy. To reduce point cloud noise from the input source, we select the latest Microsoft Azure Kinect as the state-of-the-art time-of-flight (ToF) camera. In total, 103 scenes of 10 common off-the-shelf objects with rich textures are recorded, with each frame annotated with a per-pixel semantic segmentation and ground-truth object poses provided by a commercial motion capturing system. Through extensive experiments with model-level and dataset-level analysis, we demonstrate that DTTD can help researchers develop future object tracking methods and analyze new challenges. The dataset, data generation, annotation, and model evaluation pipeline are made publicly available as open source code at: https://github.com/augcog/DTTDv1. | ['Allen Y. Yang', 'Zekun Wang', 'Yichen Chen', 'Adam Chang', 'Chuanyu Pan', 'Seth Z. Zhao', 'Weiyu Feng'] | 2023-02-12 | null | null | null | null | ['3d-object-tracking', 'robotic-grasping'] | ['computer-vision', 'robots'] | [ 1.80759951e-01 -2.52880931e-01 -1.18214592e-01 -1.70871958e-01
-6.81679487e-01 -7.81098127e-01 3.01112562e-01 -3.31084728e-01
-7.43449479e-02 8.42167363e-02 -2.26343840e-01 -2.78680712e-01
7.47708697e-03 -6.54281974e-01 -9.93494928e-01 -4.46797580e-01
7.16484338e-02 7.30636120e-01 5.17675340e-01 -2.97050357e-01
-6.73113624e-03 8.11120450e-01 -1.77727962e+00 9.76381302e-02
3.65487099e-01 1.46535230e+00 4.88535255e-01 6.67583644e-01
3.56372632e-02 3.18450451e-01 -3.15563709e-01 -2.62780994e-01
8.29319417e-01 2.19140738e-01 -3.58133495e-01 8.79634023e-02
5.63132823e-01 -7.02632189e-01 -5.61781228e-01 8.93709719e-01
7.25781381e-01 -1.32891670e-01 4.91892770e-02 -1.57537544e+00
-5.77888489e-01 6.42408505e-02 -4.89540070e-01 -1.76427796e-01
7.25296915e-01 4.16306615e-01 3.77422601e-01 -9.80107486e-01
7.99299359e-01 1.29333985e+00 1.01669240e+00 7.39889026e-01
-8.84369195e-01 -7.59247005e-01 2.78339442e-02 -3.20497394e-01
-1.17303801e+00 -3.77409399e-01 8.23514879e-01 -4.34257329e-01
7.87286103e-01 4.06004727e-01 1.00389707e+00 1.41578877e+00
1.00642718e-01 7.69141197e-01 8.70487690e-01 -3.39901835e-01
2.24049985e-01 -3.03969830e-01 -1.17846116e-01 6.18957996e-01
5.11335790e-01 2.79281795e-01 -6.58948362e-01 -1.92862481e-01
1.41560626e+00 2.97475278e-01 -3.84784847e-01 -1.09683263e+00
-1.65219212e+00 2.85428941e-01 4.34625387e-01 -1.88644245e-01
-4.10414696e-01 6.49151504e-01 2.27551367e-02 1.45206479e-02
3.72899204e-01 6.35008663e-02 -8.36827040e-01 -5.40399969e-01
-1.44806638e-01 4.03003156e-01 4.67229664e-01 1.68799233e+00
4.06818122e-01 -2.63952285e-01 4.19566184e-01 3.79569083e-01
7.61470318e-01 8.09587300e-01 3.11470866e-01 -1.41640246e+00
4.24585253e-01 7.00669706e-01 4.13698941e-01 -6.17202222e-01
-3.22194397e-01 1.88063353e-01 -1.74263433e-01 6.40696645e-01
5.48316777e-01 1.52447701e-01 -1.02821362e+00 1.06833529e+00
8.93917620e-01 1.39506683e-01 -1.31828472e-01 1.24011278e+00
9.28262532e-01 1.97413385e-01 -2.48654768e-01 2.62376636e-01
1.43484664e+00 -6.90926850e-01 -6.94243789e-01 -3.60380083e-01
7.04874754e-01 -8.84058893e-01 1.16541719e+00 5.94796896e-01
-1.01075125e+00 -4.24528420e-01 -1.03297174e+00 -3.35505992e-01
-3.58441204e-01 6.50687795e-03 9.35008168e-01 6.59769714e-01
-6.30452454e-01 4.53614205e-01 -1.37413430e+00 -5.28322697e-01
5.98949194e-01 4.48401153e-01 -5.06480515e-01 -4.25753236e-01
-4.73599941e-01 8.85133147e-01 8.06646869e-02 1.49949640e-01
-7.12004244e-01 -9.69478726e-01 -7.70484209e-01 -7.48478115e-01
5.88186383e-01 -7.39367247e-01 1.77401721e+00 -4.93768305e-01
-1.54598832e+00 1.08256543e+00 2.58038282e-01 1.93923283e-02
7.05765545e-01 -6.89637780e-01 -5.65733090e-02 6.58785626e-02
4.52859104e-02 6.37805879e-01 4.58062172e-01 -1.52543986e+00
-5.73974490e-01 -8.95269752e-01 2.03774452e-01 2.13504776e-01
-8.18389002e-03 -1.03520021e-01 -8.09272528e-01 -6.39534712e-01
6.92112565e-01 -1.16527700e+00 -2.11679086e-01 9.33753610e-01
-7.43310750e-02 1.52351916e-01 1.27047694e+00 -4.89751756e-01
3.05581897e-01 -2.24236250e+00 5.90578765e-02 -2.54638910e-01
1.89489790e-03 4.86709140e-02 1.71635196e-01 1.18094988e-01
2.33773485e-01 -3.15631747e-01 7.68262846e-03 -5.26615739e-01
1.19289145e-01 3.78656089e-01 -2.49565661e-01 6.73532307e-01
-2.67786860e-01 9.15718257e-01 -9.20963168e-01 -3.14853579e-01
6.68095887e-01 6.85579360e-01 -3.21842343e-01 2.10858509e-01
-5.81739724e-01 6.15786850e-01 -5.94280243e-01 1.51318872e+00
8.88358772e-01 -7.47300908e-02 -1.98800862e-01 -5.20466208e-01
-1.73255950e-01 6.63278252e-02 -1.52690291e+00 2.55832767e+00
-1.22034721e-01 5.09184480e-01 2.28578508e-01 -1.22733250e-01
8.23311150e-01 1.75752297e-01 9.25003588e-01 -6.00947917e-01
3.62849444e-01 4.37017381e-01 -4.90816057e-01 -5.73048711e-01
7.19684422e-01 2.60718703e-01 8.47508758e-02 2.86154211e-01
-1.63020283e-01 -4.68595058e-01 -4.67450500e-01 -7.52238184e-02
1.14921331e+00 8.93661737e-01 -1.00596160e-01 1.39079884e-01
-3.09777200e-01 6.49071693e-01 3.44541878e-01 5.12767673e-01
-2.28570595e-01 1.07628822e+00 -2.37317428e-01 -2.73128390e-01
-1.14008403e+00 -1.18263364e+00 -3.87545496e-01 6.88575745e-01
7.49516368e-01 -1.70238942e-01 -4.31167394e-01 -2.64242500e-01
6.00349128e-01 2.49396279e-01 -4.06121820e-01 8.34140107e-02
-5.16477823e-01 -3.75190258e-01 4.21245784e-01 9.02587771e-01
4.26715076e-01 -7.46301055e-01 -1.29220808e+00 5.45909889e-02
6.27119243e-02 -1.36184740e+00 -1.39957309e-01 2.26054102e-01
-1.15607119e+00 -1.14335632e+00 -7.57912278e-01 -5.29583216e-01
4.13710892e-01 7.36118913e-01 9.18454230e-01 -1.46186367e-01
-3.61912787e-01 9.91855323e-01 -7.50395596e-01 -6.56898975e-01
-1.74110569e-02 -3.31228167e-01 3.00268054e-01 -5.75553596e-01
2.86307037e-01 -2.63799936e-01 -6.58777535e-01 6.50182784e-01
-7.93897748e-01 1.85435921e-01 2.58523792e-01 1.54740632e-01
8.96791101e-01 -4.98139977e-01 -2.59283006e-01 -2.18991056e-01
-3.18637267e-02 -1.66781604e-01 -9.27165627e-01 -8.87062103e-02
-2.10260764e-01 -4.49526489e-01 -3.43175203e-01 -8.42829466e-01
-8.64163697e-01 5.42172492e-01 7.60582536e-02 -1.16188169e+00
-7.65020102e-02 1.21787719e-01 -3.79658818e-01 -4.25054282e-01
5.96709669e-01 -2.56127775e-01 2.66978562e-01 -7.01661110e-01
4.87124145e-01 7.79969096e-01 8.78455877e-01 -6.60978556e-01
6.54335737e-01 8.33159447e-01 -1.86997920e-01 -5.10794461e-01
-5.98224044e-01 -5.25532842e-01 -8.05201173e-01 -4.06823933e-01
7.40117133e-01 -1.13091826e+00 -8.82905602e-01 7.05332518e-01
-1.24916565e+00 -7.27755785e-01 -4.92721975e-01 6.92510307e-01
-7.27630913e-01 8.44495744e-03 -4.06840324e-01 -9.03545558e-01
-5.36482856e-02 -1.27128482e+00 1.81374478e+00 2.13460550e-01
5.67409880e-02 -4.25607145e-01 -9.03812274e-02 5.27683198e-01
-4.84787636e-02 6.05552256e-01 4.54630377e-03 -8.04632204e-04
-1.00070035e+00 -3.58576685e-01 1.26101507e-03 1.10728638e-02
2.41881162e-01 5.31785823e-02 -1.06383395e+00 -1.89359263e-01
4.34732111e-03 -2.15030298e-01 1.38407290e-01 4.57429737e-01
1.01435566e+00 2.01932162e-01 -6.53223217e-01 8.66917253e-01
1.32069826e+00 3.51130486e-01 5.82049072e-01 7.59936750e-01
1.12850642e+00 3.75321835e-01 1.38656628e+00 4.94213462e-01
4.66057658e-01 1.05049908e+00 9.87063825e-01 1.02867521e-01
-2.15979889e-01 -8.50032568e-02 3.00773859e-01 4.25597936e-01
-2.63912648e-01 -1.12878546e-01 -1.21741796e+00 3.09441060e-01
-1.90482152e+00 -5.69219708e-01 -5.58207989e-01 2.25258923e+00
6.07673705e-01 -2.01222263e-02 1.37093142e-01 7.64823779e-02
5.20969272e-01 -3.52166086e-01 -6.58942521e-01 3.85585338e-01
-1.05711661e-01 1.61692873e-01 8.76034796e-01 1.55857831e-01
-9.87114787e-01 8.57349098e-01 5.16396284e+00 1.69447601e-01
-1.10170293e+00 2.27322981e-01 -1.03256151e-01 -2.37065986e-01
-2.99753547e-02 -9.93153229e-02 -7.02834606e-01 2.28418931e-01
5.37477136e-01 1.49288759e-01 2.59182602e-01 1.32544565e+00
-3.53512657e-03 -1.35465786e-01 -1.25327325e+00 1.31504786e+00
-1.10043868e-01 -1.24366367e+00 -4.21656013e-01 3.74629468e-01
4.93696779e-01 3.79411370e-01 -1.55700684e-01 -1.77816078e-01
2.08238542e-01 -6.30303085e-01 1.35747588e+00 4.52800721e-01
9.10430193e-01 -2.46837243e-01 5.61233997e-01 2.63638079e-01
-1.28611517e+00 -8.20820313e-03 -2.75032640e-01 2.01377254e-02
2.90782601e-01 2.19596535e-01 -6.28766179e-01 6.00970507e-01
1.27175069e+00 7.39932716e-01 -4.17337656e-01 1.14251602e+00
2.89088815e-01 -1.61039919e-01 -6.81147814e-01 2.08653197e-01
-2.57359147e-01 -4.94758552e-03 5.66776395e-01 5.37231743e-01
5.82225740e-01 4.69544381e-01 1.74879078e-02 6.50511384e-01
5.88717423e-02 -6.40408218e-01 -7.35671520e-01 7.38624260e-02
5.94984353e-01 1.04809225e+00 -9.00125325e-01 -9.96566713e-02
-3.31052721e-01 1.06337750e+00 -2.78783053e-01 -3.93998343e-03
-9.12353635e-01 -1.94058139e-02 1.08067536e+00 3.70513976e-01
2.46711701e-01 -7.73995936e-01 -6.29652202e-01 -1.12362003e+00
4.19269383e-01 -7.48583257e-01 -7.12771937e-02 -1.35451555e+00
-1.10254729e+00 3.14808756e-01 1.55611366e-01 -1.87323344e+00
1.53216437e-01 -1.16216731e+00 1.38687164e-01 4.91811931e-01
-1.13032830e+00 -1.39478683e+00 -1.12137365e+00 6.38542593e-01
6.29479587e-01 2.68047154e-01 7.36230791e-01 5.33965290e-01
-1.97682619e-01 8.53403509e-02 8.58826935e-02 -4.50125746e-02
5.66419005e-01 -9.15200174e-01 5.47819674e-01 7.00294137e-01
8.57971832e-02 5.07908881e-01 6.64832532e-01 -9.21009421e-01
-2.47799730e+00 -9.25366342e-01 -2.29433253e-01 -1.32935429e+00
4.27761644e-01 -5.76012075e-01 -6.70736194e-01 1.10350788e+00
-5.91427863e-01 5.87798536e-01 4.78583239e-02 -4.94492650e-01
1.78884715e-02 1.50657341e-01 -1.30281782e+00 4.29297954e-01
1.71038163e+00 -3.49106759e-01 -4.70146090e-01 4.26448256e-01
1.13450623e+00 -1.55412173e+00 -1.04545367e+00 5.70704341e-01
1.17061055e+00 -7.50032187e-01 1.36151230e+00 -2.60498021e-02
3.03429849e-02 -6.32549465e-01 -6.41774058e-01 -7.98115134e-01
1.30079880e-01 -4.94231761e-01 -5.11296749e-01 1.07205522e+00
-1.77829340e-01 -5.30950785e-01 1.06148541e+00 1.04011166e+00
-5.67765474e-01 -5.37316680e-01 -1.09590030e+00 -1.03899288e+00
-5.15124261e-01 -9.96781766e-01 7.63019621e-01 9.18782771e-01
-3.59022498e-01 -5.10473669e-01 1.01349413e-01 6.52436554e-01
8.01541924e-01 5.94774112e-02 1.29923940e+00 -1.42057431e+00
2.39348356e-02 -1.07098691e-01 -6.26985729e-01 -1.16236174e+00
-4.65757728e-01 -5.18999398e-01 2.09893748e-01 -1.54330242e+00
-5.20523131e-01 -9.41972613e-01 3.11959565e-01 4.29961145e-01
3.09510857e-01 4.96721864e-01 2.19049364e-01 4.64905202e-01
-4.25263077e-01 5.66450953e-01 1.25363123e+00 5.48256524e-02
-2.79356003e-01 -4.20626625e-02 -2.40095273e-01 7.21600235e-01
4.11932886e-01 -5.56171894e-01 -5.82546033e-02 -8.16454947e-01
-5.54646850e-02 -2.46555842e-02 8.54829848e-01 -1.09893870e+00
2.06862733e-01 -2.15482712e-01 3.94459665e-01 -7.91029692e-01
1.01543307e+00 -1.41222191e+00 7.56477594e-01 4.96027052e-01
3.25501740e-01 2.34594524e-01 3.90135109e-01 4.06420171e-01
3.79116565e-01 5.34617491e-02 3.81191880e-01 -2.33282924e-01
-9.69750941e-01 5.24869919e-01 3.50322634e-01 -4.14418370e-01
1.34828568e+00 -8.88684630e-01 -4.57277149e-01 1.55518278e-01
-4.38724816e-01 6.80104271e-02 1.17577791e+00 8.08057666e-01
8.25198174e-01 -1.57112765e+00 -1.21246107e-01 1.88419357e-01
5.01786947e-01 8.37978482e-01 -2.68319878e-03 7.38751233e-01
-1.00579393e+00 1.14307635e-01 -2.66219020e-01 -1.14738083e+00
-1.21268404e+00 3.30252528e-01 2.60896146e-01 7.06836402e-01
-1.09806991e+00 8.03186774e-01 -1.74710080e-01 -6.56278372e-01
3.96833748e-01 -7.80716956e-01 5.84124863e-01 -3.82185668e-01
3.88451785e-01 5.07933438e-01 2.47556925e-01 -6.00431681e-01
-5.89573920e-01 8.38715732e-01 4.56095278e-01 -2.37726614e-01
1.46513128e+00 -9.81463417e-02 2.11115927e-01 5.85361958e-01
7.76504338e-01 -2.57375389e-01 -1.72015834e+00 -7.80022144e-02
-1.99943304e-01 -1.11112988e+00 1.84241191e-01 -5.66540062e-01
-9.16625559e-01 5.08530855e-01 1.19315386e+00 5.94916046e-02
7.65753806e-01 4.81244802e-01 7.67609596e-01 2.03858837e-01
1.01841068e+00 -7.59350121e-01 8.30927864e-02 2.30217412e-01
1.02671111e+00 -1.41587090e+00 1.00328863e-01 -6.25521243e-01
-4.47471529e-01 1.09841132e+00 9.20534253e-01 -4.59342860e-02
3.84853125e-01 6.89369977e-01 1.80251718e-01 -4.97715592e-01
-1.47234723e-01 -4.04372215e-02 1.39111253e-02 9.43012476e-01
7.66780898e-02 -1.91753916e-02 4.51944262e-01 4.83670533e-01
-2.99999774e-01 3.21360618e-01 3.43843549e-01 1.62962222e+00
-1.29044294e-01 -9.51460004e-01 -8.19868684e-01 2.53626466e-01
6.29257858e-02 4.07878637e-01 -1.13789670e-01 9.72311437e-01
1.88188836e-01 6.23017669e-01 2.91381061e-01 -4.96230006e-01
7.33772993e-01 -3.69725943e-01 9.41720665e-01 -5.33100665e-01
-3.56243640e-01 5.20739425e-03 -5.49796149e-02 -1.07534516e+00
-5.77641189e-01 -9.94020581e-01 -1.45558023e+00 -3.79611731e-01
-6.09660685e-01 -6.55408621e-01 1.34764087e+00 5.52232146e-01
5.08798897e-01 4.04547185e-01 9.07446966e-02 -1.75943398e+00
-2.28796288e-01 -8.24436486e-01 -3.88946086e-01 1.10137977e-01
4.35585409e-01 -1.08577180e+00 -6.21105544e-02 2.03774884e-01] | [7.072671890258789, -2.175894021987915] |
1a1b8324-c4cb-4e20-bdbf-194bd7c3b9fc | adaptive-dnn-surgery-for-selfish-inference | 2306.12185 | null | https://arxiv.org/abs/2306.12185v1 | https://arxiv.org/pdf/2306.12185v1.pdf | Adaptive DNN Surgery for Selfish Inference Acceleration with On-demand Edge Resource | Deep Neural Networks (DNNs) have significantly improved the accuracy of intelligent applications on mobile devices. DNN surgery, which partitions DNN processing between mobile devices and multi-access edge computing (MEC) servers, can enable real-time inference despite the computational limitations of mobile devices. However, DNN surgery faces a critical challenge: determining the optimal computing resource demand from the server and the corresponding partition strategy, while considering both inference latency and MEC server usage costs. This problem is compounded by two factors: (1) the finite computing capacity of the MEC server, which is shared among multiple devices, leading to inter-dependent demands, and (2) the shift in modern DNN architecture from chains to directed acyclic graphs (DAGs), which complicates potential solutions. In this paper, we introduce a novel Decentralized DNN Surgery (DDS) framework. We formulate the partition strategy as a min-cut and propose a resource allocation game to adaptively schedule the demands of mobile devices in an MEC environment. We prove the existence of a Nash Equilibrium (NE), and develop an iterative algorithm to efficiently reach the NE for each device. Our extensive experiments demonstrate that DDS can effectively handle varying MEC scenarios, achieving up to 1.25$\times$ acceleration compared to the state-of-the-art algorithm. | ['Song Guo', 'Jianxin Liao', 'Haifeng Sun', 'Jingyu Wang', 'Qi Qi', 'Dezhi Chen', 'Xiang Yang'] | 2023-06-21 | null | null | null | null | ['edge-computing'] | ['time-series'] | [-1.28884792e-01 -1.43215939e-01 -4.41143036e-01 7.57998005e-02
-4.28341888e-02 -6.05720758e-01 -9.70061049e-02 -4.47657973e-01
-5.97080529e-01 6.99487686e-01 -2.02659756e-01 -7.15562940e-01
-4.02655602e-01 -8.63995671e-01 -5.44019103e-01 -6.66129053e-01
1.52229935e-01 7.87835002e-01 3.86540204e-01 1.91001981e-01
-2.62466818e-01 7.08352149e-01 -1.44007027e+00 -3.18614841e-01
8.18651199e-01 1.35475004e+00 7.11540997e-01 5.78755021e-01
-2.46016681e-01 6.55633092e-01 -4.88671929e-01 -6.40800118e-01
2.91820943e-01 -4.05207127e-02 -4.99711335e-01 -9.21628773e-02
-1.83800519e-01 -7.38750160e-01 -5.15249610e-01 1.16753697e+00
5.98609030e-01 -5.79579361e-03 2.79426455e-01 -1.78471732e+00
-2.14792620e-02 6.79023921e-01 -4.70846206e-01 5.62309504e-01
-4.42849845e-01 -1.57716691e-01 7.49343097e-01 -4.31330621e-01
7.61843443e-01 6.78086638e-01 4.07305270e-01 7.08169043e-01
-8.26159358e-01 -8.07532966e-01 2.63625145e-01 3.87647152e-01
-1.28834939e+00 -7.32273281e-01 4.90634233e-01 -5.97752742e-02
9.81895328e-01 1.37754351e-01 8.74462008e-01 7.21380413e-01
2.22431757e-02 7.75516331e-01 1.57312170e-01 -1.39522836e-01
5.92971563e-01 -3.17811310e-01 -2.78837353e-01 4.35082972e-01
6.06269062e-01 -5.15966177e-01 -4.13000435e-01 4.91236374e-02
9.57604468e-01 2.51602709e-01 -1.50231123e-01 -2.12233022e-01
-6.98174596e-01 4.31005657e-01 2.76397020e-01 1.36727318e-01
-7.89206564e-01 4.25030947e-01 5.14189482e-01 -5.19399159e-02
2.70685673e-01 -2.23926485e-01 -6.84579670e-01 -4.62839216e-01
-1.03760362e+00 -3.38770598e-02 1.08147490e+00 1.34843373e+00
4.25153077e-01 -1.13627322e-01 1.32621050e-01 5.08778036e-01
1.95950404e-01 4.98472184e-01 3.27255167e-02 -1.17786539e+00
6.75576031e-01 4.13869768e-01 -1.22218058e-01 -7.95691192e-01
-4.63900387e-01 -5.59667408e-01 -1.09435308e+00 -3.74454349e-01
3.72667670e-01 -6.67699039e-01 -4.44197059e-01 1.77894354e+00
4.31329429e-01 4.81951088e-01 -1.18289702e-01 9.91025984e-01
3.15352917e-01 4.41228032e-01 5.97795360e-02 -3.90565842e-01
1.29660594e+00 -9.92904902e-01 -6.34232700e-01 -2.45112911e-01
5.27833402e-01 -4.40660417e-01 3.68869781e-01 1.57327771e-01
-1.31865311e+00 2.48634681e-01 -7.60549247e-01 -1.13417938e-01
-8.09319690e-02 1.34804145e-01 6.05665505e-01 6.20375812e-01
-1.39039004e+00 1.19142301e-01 -1.10652065e+00 -2.05105603e-01
5.59564173e-01 7.90331006e-01 2.13461980e-01 -3.28594536e-01
-8.24416995e-01 3.39703858e-01 8.56273249e-02 2.51864940e-01
-8.15431714e-01 -8.32077920e-01 -2.57850021e-01 4.87904042e-01
9.29981828e-01 -9.28519130e-01 1.36918461e+00 -6.07643604e-01
-1.50388467e+00 4.91673023e-01 -2.15552688e-01 -2.27916628e-01
6.45701826e-01 3.24154586e-01 -3.62082839e-01 2.49650523e-01
5.14188558e-02 3.95141184e-01 2.66881913e-01 -7.18910694e-01
-1.01308024e+00 -5.61960876e-01 3.87363791e-01 3.52713406e-01
-6.14409745e-01 -1.27611279e-01 -1.16865063e+00 -2.22121313e-01
3.62326875e-02 -1.11950910e+00 -3.94851148e-01 1.39194325e-01
-4.58357006e-01 -2.98136532e-01 7.43328094e-01 -2.51176327e-01
1.35185266e+00 -2.07449651e+00 1.09056659e-01 2.91038394e-01
7.36146271e-01 2.12644339e-01 2.28468657e-01 2.32899133e-02
7.20147610e-01 -8.78898874e-02 3.89641047e-01 -5.49570203e-01
3.11836060e-02 6.70661628e-01 4.87096086e-02 1.47928402e-01
-6.09529614e-01 7.81751812e-01 -7.62473047e-01 -5.16399205e-01
-1.94611967e-01 3.29234272e-01 -8.17662716e-01 -1.93618625e-01
-2.42572129e-01 -1.78234652e-02 -5.54450035e-01 7.22918510e-01
8.46490085e-01 -5.95178187e-01 8.60276401e-01 -1.83115065e-01
8.24599788e-02 9.76633355e-02 -1.18064976e+00 1.39424777e+00
-5.25752187e-01 6.44606113e-01 8.22192192e-01 -1.01984215e+00
3.77799839e-01 2.05181971e-01 6.86904252e-01 -6.43562913e-01
3.19879711e-01 4.66562718e-01 -6.95509091e-02 -4.75307733e-01
4.56970751e-01 1.27278119e-01 4.64976504e-02 3.70766699e-01
-8.93388838e-02 7.99414456e-01 2.14239135e-01 2.13112101e-01
1.37814546e+00 -6.99319661e-01 -2.44714737e-01 -5.04412174e-01
8.86779875e-02 -3.23838532e-01 1.12129056e+00 6.22669041e-01
-4.67447639e-01 -1.94350496e-01 9.38138962e-01 -3.74489218e-01
-8.43882978e-01 -1.02824521e+00 2.06706002e-01 1.04129028e+00
4.91421938e-01 -1.67000532e-01 -1.03909469e+00 -4.87135351e-01
-2.14225203e-01 3.09090227e-01 -7.01001808e-02 4.42315303e-02
-4.26342666e-01 -4.67640549e-01 3.98120582e-01 7.02850163e-01
5.68025172e-01 -6.97757065e-01 -8.81208599e-01 2.98736870e-01
-4.24330801e-01 -1.76044774e+00 -8.20464075e-01 8.81904438e-02
-1.04717803e+00 -8.95850658e-01 -5.14184773e-01 -6.94170177e-01
8.28409553e-01 5.26528060e-01 1.07184207e+00 9.35334489e-02
-6.09649830e-02 1.48667336e-01 6.11425377e-02 -2.27231711e-01
2.58579433e-01 5.27583838e-01 3.84045541e-01 -1.75694406e-01
3.48753631e-01 -8.76286387e-01 -9.86491442e-01 3.69678617e-01
-1.00105655e+00 2.25881428e-01 5.05860925e-01 2.86895066e-01
8.45053077e-01 5.71995854e-01 5.67175210e-01 -7.08882332e-01
5.29557824e-01 -7.06275880e-01 -9.42396879e-01 3.31059396e-01
-5.95842302e-01 -4.93801050e-02 9.09107625e-01 -3.52280855e-01
-7.47255027e-01 -5.46536446e-02 8.65966752e-02 -7.86133468e-01
3.26930314e-01 4.77992952e-01 -6.77975357e-01 1.57072857e-01
-1.28096879e-01 -5.79484887e-02 -2.82724798e-01 -2.88652718e-01
8.03413689e-02 6.96123540e-01 5.82689524e-01 -6.66238546e-01
1.05527453e-01 4.82058406e-01 3.39163333e-01 -6.24602020e-01
-2.96792030e-01 -1.07052572e-01 -6.57358393e-02 -5.44129074e-01
7.03439176e-01 -9.77295935e-01 -1.46346509e+00 4.27380800e-01
-1.16948986e+00 -5.15533388e-01 8.11582431e-02 4.28775102e-01
-1.93045437e-01 -1.25465930e-01 -7.88044691e-01 -8.65439892e-01
-4.13251936e-01 -1.41233325e+00 6.01899147e-01 5.95796824e-01
3.57645601e-01 -8.14858973e-01 -5.40265679e-01 4.17265594e-01
5.99462986e-01 -1.31099015e-01 8.35163653e-01 -3.01256537e-01
-1.13292229e+00 1.36519030e-01 -5.75884402e-01 -5.95926978e-02
-2.36610293e-01 -1.70972452e-01 -4.12302375e-01 -2.80912071e-01
-2.59392232e-01 2.31460348e-01 3.28729838e-01 6.63955033e-01
1.47608066e+00 -4.35817540e-01 -7.80727923e-01 8.47691238e-01
1.63201952e+00 4.73238409e-01 5.07104874e-01 1.55234501e-01
7.34812856e-01 7.88439140e-02 -3.73005494e-02 6.82666123e-01
8.42235386e-01 6.00461066e-01 7.74154127e-01 2.76558757e-01
1.83754548e-01 -1.30803078e-01 3.80037613e-02 1.07253683e+00
-1.32314518e-01 -7.76674032e-01 -8.69934857e-01 6.18729293e-01
-2.15547395e+00 -4.49029237e-01 2.99876899e-01 1.92367733e+00
3.93306941e-01 2.79719889e-01 2.06294224e-01 1.00630401e-02
7.24677503e-01 -2.57386059e-01 -1.23540115e+00 -1.45612568e-01
2.34386325e-01 -5.78076653e-02 8.88160884e-01 5.69004305e-02
-3.93259525e-01 6.31875336e-01 5.49235487e+00 9.34353232e-01
-1.03254747e+00 3.27355623e-01 6.70874953e-01 -6.76701427e-01
-2.48799875e-01 -5.04374504e-01 -9.31046426e-01 1.01221776e+00
1.14470375e+00 -3.85119826e-01 9.23315048e-01 1.05878866e+00
1.38046235e-01 4.11528908e-02 -8.63921881e-01 1.29247689e+00
-2.60928720e-01 -1.50234330e+00 -2.24137828e-01 6.63859725e-01
6.72750473e-01 4.80093658e-01 -2.55082488e-01 -2.78237332e-02
3.20213109e-01 -3.57678831e-01 7.41281807e-01 3.78718823e-01
1.02506471e+00 -1.17870212e+00 6.54144943e-01 5.39140463e-01
-1.37940633e+00 -3.18113744e-01 -3.28644246e-01 1.91716682e-02
3.28665555e-01 9.59327579e-01 -4.12542880e-01 3.03695887e-01
8.34953785e-01 2.07846195e-01 3.06581020e-01 8.81990850e-01
2.07328215e-01 1.23119742e-01 -7.84544051e-01 -3.44731122e-01
-5.70604689e-02 -4.28393096e-01 4.75876987e-01 7.74478316e-01
5.73435068e-01 4.13056761e-01 -5.92106767e-02 6.96224689e-01
-9.44601774e-01 -3.56424332e-01 -1.96957722e-01 -8.15459713e-02
1.12951052e+00 1.32220328e+00 -1.34545147e+00 -2.45890781e-01
-4.19756591e-01 9.76607025e-01 3.86704236e-01 3.66888076e-01
-9.12966967e-01 -3.66673201e-01 1.24993491e+00 1.30581558e-01
5.65470994e-01 -2.43221655e-01 -4.63706642e-01 -1.11868238e+00
4.37897354e-01 -3.69162172e-01 2.55607247e-01 -4.84195262e-01
-9.38744962e-01 6.40243173e-01 -4.32238251e-01 -8.03651035e-01
7.03690425e-02 -5.18967211e-01 -4.65413511e-01 4.53638673e-01
-1.34386480e+00 -5.58238506e-01 -2.97762156e-01 7.13296175e-01
3.30378175e-01 -1.27634704e-02 3.35539937e-01 1.15205586e+00
-1.17547417e+00 8.70460510e-01 2.79879391e-01 -6.54534996e-02
-1.24438867e-01 -7.93844104e-01 1.26758352e-01 1.05863357e+00
-2.71838576e-01 2.11179703e-01 3.96356225e-01 -4.05838072e-01
-1.90597641e+00 -8.70665133e-01 8.50620806e-01 1.13923073e-01
4.22105610e-01 -4.99724478e-01 -2.23009467e-01 6.00784063e-01
-3.16644073e-01 3.04713130e-01 7.41652548e-01 -8.29016119e-02
2.28413939e-01 -5.12483358e-01 -1.12008095e+00 9.63883102e-01
1.64376295e+00 -3.69894117e-01 6.46183670e-01 1.32934511e-01
8.34248543e-01 -6.43596709e-01 -5.33376753e-01 1.86985180e-01
5.93782663e-01 -7.43141055e-01 6.88970864e-01 -4.19659853e-01
3.06712538e-01 -1.20575666e-01 -2.59345055e-01 -8.86338711e-01
-4.50875685e-02 -7.39558220e-01 -6.75357878e-01 1.05233169e+00
3.07237834e-01 -5.77906489e-01 1.31949627e+00 1.14797795e+00
-1.36115327e-01 -1.11646914e+00 -1.33136439e+00 -7.05724597e-01
-5.18002629e-01 -6.25487924e-01 8.90171587e-01 5.79974711e-01
-2.04406023e-01 4.00934756e-01 -1.41291693e-01 2.89050460e-01
6.21282876e-01 -1.59519047e-01 4.03737068e-01 -1.30177486e+00
-2.46114135e-01 -6.11039519e-01 -3.09325665e-01 -1.57451725e+00
1.02225259e-01 -6.78024471e-01 -1.49874642e-01 -1.69541430e+00
9.20994207e-02 -8.22229505e-01 -1.67476550e-01 3.40852976e-01
3.41732025e-01 -5.49186617e-02 3.62338215e-01 2.59430677e-01
-1.10676301e+00 2.58495331e-01 1.03700769e+00 2.76594937e-01
-1.92974061e-01 1.92416728e-01 -8.65677953e-01 6.26830041e-01
6.68556809e-01 -3.72302562e-01 -8.11085284e-01 -1.00519288e+00
6.43203259e-01 3.89270842e-01 -4.94151842e-03 -8.85998189e-01
9.54986691e-01 2.93053966e-03 3.17055471e-02 -5.69762647e-01
2.01959297e-01 -1.35119998e+00 3.31931621e-01 5.34847438e-01
2.88096517e-01 3.60870808e-01 4.85306941e-02 7.41855443e-01
3.48714620e-01 2.74637695e-02 3.24854046e-01 2.23845184e-01
-4.51076627e-01 8.72651160e-01 -5.59701920e-01 1.00946270e-01
1.09400046e+00 -1.62096500e-01 -3.74386847e-01 -2.36784413e-01
-4.97023404e-01 7.04710662e-01 2.32981101e-01 1.47104442e-01
2.18491644e-01 -1.17231345e+00 -4.53684479e-02 3.96804251e-02
-5.16840577e-01 4.32999790e-01 6.19204819e-01 9.41947818e-01
-7.17982292e-01 4.03271914e-01 -5.25590479e-02 -3.19001645e-01
-9.53047097e-01 4.16925013e-01 3.95244688e-01 -4.90471750e-01
-4.80297476e-01 7.73406565e-01 -8.62799436e-02 5.51667772e-02
5.41302264e-01 -3.08816105e-01 3.34001064e-01 -6.39098436e-02
3.22365195e-01 9.10503805e-01 2.32472122e-01 -1.41189277e-01
-5.04652202e-01 5.09983450e-02 -3.74551937e-02 3.96653712e-02
1.31036353e+00 -5.74740469e-01 -2.44401962e-01 -2.38234133e-01
9.82234657e-01 -3.78747910e-01 -1.25730097e+00 -4.17251855e-01
-2.00374350e-01 -8.44956934e-02 5.04183888e-01 -5.52986622e-01
-1.94722915e+00 3.95703286e-01 2.82305092e-01 3.12702358e-01
1.55926132e+00 7.75224417e-02 1.49680316e+00 2.41424561e-01
5.78823745e-01 -1.30922472e+00 -3.35499108e-01 3.56967300e-01
-1.62147895e-01 -6.10410631e-01 -4.72970188e-01 -4.79159564e-01
-1.86658069e-01 1.02692878e+00 8.59214306e-01 3.85283232e-01
1.10329497e+00 7.35839486e-01 -2.83249140e-01 -2.76920319e-01
-8.19061399e-01 1.48891509e-01 -4.88485366e-01 1.19897872e-01
-3.27357620e-01 4.46660876e-01 -2.30018988e-01 1.17052174e+00
-7.32157305e-02 4.41085637e-01 3.70031387e-01 7.45658994e-01
-7.53276423e-02 -9.45597529e-01 1.94201574e-01 7.53888011e-01
-6.27174854e-01 1.25911180e-02 1.67794302e-01 3.61715466e-01
3.64268512e-01 9.27973092e-01 6.36260033e-01 -4.79389429e-01
3.08275551e-01 -3.65112633e-01 1.86248228e-01 -5.76282516e-02
3.58669385e-02 4.90129031e-02 -1.19631253e-02 -5.01599014e-01
4.36359532e-02 -4.15944457e-01 -1.28284872e+00 -9.61695075e-01
-1.97929189e-01 -7.66939148e-02 8.56888175e-01 1.06499648e+00
9.58304763e-01 8.35781157e-01 4.79250550e-01 -7.52651274e-01
-2.04473332e-01 -3.55050147e-01 -8.49712849e-01 -3.90733957e-01
1.23360135e-01 -5.46412230e-01 -1.17461607e-01 -3.97636861e-01] | [8.123985290527344, 2.8489725589752197] |
e4bec2ec-0ce4-4d3e-a438-f4ccd4b0db58 | compositional-exemplars-for-in-context | 2302.05698 | null | https://arxiv.org/abs/2302.05698v3 | https://arxiv.org/pdf/2302.05698v3.pdf | Compositional Exemplars for In-context Learning | Large pretrained language models (LMs) have shown impressive In-Context Learning (ICL) ability, where the model learns to do an unseen task via a prompt consisting of input-output examples as the demonstration, without any parameter updates. The performance of ICL is highly dominated by the quality of the selected in-context examples. However, previous selection methods are mostly based on simple heuristics, leading to sub-optimal performance. In this work, we formulate in-context example selection as a subset selection problem. We propose CEIL (Compositional Exemplars for In-context Learning), which is instantiated by Determinantal Point Processes (DPPs) to model the interaction between the given input and in-context examples, and optimized through a carefully-designed contrastive learning objective to obtain preference from LMs. We validate CEIL on 12 classification and generation datasets from 7 distinct NLP tasks, including sentiment analysis, paraphrase detection, natural language inference, commonsense reasoning, open-domain question answering, code generation, and semantic parsing. Extensive experiments demonstrate not only the state-of-the-art performance but also the transferability and compositionality of CEIL, shedding new light on effective and efficient in-context learning. Our code is released at https://github.com/HKUNLP/icl-ceil. | ['Lingpeng Kong', 'Tao Yu', 'Jiangtao Feng', 'Zhiyong Wu', 'Jiacheng Ye'] | 2023-02-11 | null | null | null | null | ['point-processes', 'semantic-parsing', 'open-domain-question-answering'] | ['methodology', 'natural-language-processing', 'natural-language-processing'] | [ 4.88283306e-01 1.49838567e-01 -1.98609605e-01 -5.28473020e-01
-1.23835742e+00 -9.34172392e-01 7.44411945e-01 2.20338166e-01
-4.20175493e-01 6.42841160e-01 2.11801142e-01 -5.69240749e-01
-7.38814622e-02 -6.00936651e-01 -1.06547856e+00 -3.17450017e-01
2.18013421e-01 5.70943296e-01 -1.98897451e-01 -2.62331545e-01
3.00876617e-01 2.17124205e-02 -1.49989343e+00 9.94301319e-01
1.12476468e+00 9.03893173e-01 3.66652548e-01 7.40308166e-01
-5.58579683e-01 1.13766241e+00 -6.25390172e-01 -7.29417920e-01
-9.85367820e-02 -5.83715916e-01 -1.00344121e+00 -2.78558850e-01
4.42688853e-01 1.46187350e-01 2.96710104e-01 9.11157787e-01
4.63006765e-01 6.99012652e-02 5.16393244e-01 -1.29402256e+00
-9.92430329e-01 1.11171162e+00 3.10417097e-02 3.67195494e-02
7.75955141e-01 3.72482181e-01 1.63008785e+00 -1.18920493e+00
6.79298043e-01 1.31829262e+00 5.61737299e-01 8.47092509e-01
-1.33583808e+00 -5.59235632e-01 3.18155974e-01 3.35410774e-01
-8.67593527e-01 -4.19850886e-01 8.89873922e-01 -3.59150201e-01
1.19553769e+00 2.53429264e-01 4.17171061e-01 1.50764155e+00
-6.37793168e-02 1.31790626e+00 1.12718511e+00 -7.16971755e-01
4.79322523e-01 3.07440668e-01 1.77482024e-01 6.90246105e-01
-4.25100252e-02 8.80554318e-02 -6.14793420e-01 -3.81936371e-01
1.99506640e-01 -2.07010597e-01 -2.69963443e-01 -1.57898977e-01
-1.09340310e+00 9.43670750e-01 3.57933015e-01 1.96018338e-01
2.51908728e-04 1.48722067e-01 3.66330147e-01 6.52791381e-01
2.35013813e-01 8.71984184e-01 -8.52345943e-01 -1.73784658e-01
-6.69401407e-01 3.62015873e-01 1.04827774e+00 1.07416320e+00
6.67769492e-01 -2.85024732e-01 -4.08237755e-01 9.40910876e-01
4.80610989e-02 4.41556901e-01 7.39777625e-01 -1.01814425e+00
6.73332810e-01 7.74459004e-01 -8.99814814e-02 -5.39331555e-01
-2.44710356e-01 -3.27777863e-01 -3.35206002e-01 -1.97325855e-01
4.69668418e-01 -2.86800146e-01 -5.46726406e-01 2.12585592e+00
1.76447719e-01 9.08081010e-02 2.80378461e-01 5.74009895e-01
8.71762097e-01 7.94638813e-01 2.19417721e-01 9.26280767e-02
1.28108776e+00 -1.17874241e+00 -2.62511194e-01 -6.69744790e-01
8.17626536e-01 -6.90233052e-01 1.95116830e+00 4.13507640e-01
-1.01540804e+00 -4.29230928e-01 -7.53900409e-01 -3.82274181e-01
-4.40686315e-01 2.27470264e-01 4.53169346e-01 1.74976915e-01
-8.04766238e-01 5.22739232e-01 -3.83153290e-01 -5.79010360e-02
4.17740911e-01 8.82206336e-02 -5.22149866e-03 -2.23973006e-01
-1.31556141e+00 7.08643138e-01 4.94748980e-01 -7.15820342e-02
-8.03801715e-01 -9.89819586e-01 -9.30699706e-01 7.41559416e-02
6.36035740e-01 -8.47015798e-01 1.54335546e+00 -1.25439870e+00
-1.51233709e+00 1.15527964e+00 -2.25199297e-01 -4.84667093e-01
4.42045033e-01 -4.36681509e-01 -2.94380724e-01 9.48867109e-03
1.42855689e-01 7.68199146e-01 6.34963036e-01 -1.18967164e+00
-5.31532049e-01 -5.32967560e-02 4.87493664e-01 1.40765950e-01
-6.13724031e-02 -2.91438540e-03 -3.07596266e-01 -6.02950394e-01
-3.09827209e-01 -9.31641281e-01 -4.30411324e-02 -2.46130005e-01
-5.44295073e-01 -5.24781823e-01 4.03423846e-01 -5.92045605e-01
1.21338093e+00 -2.09710693e+00 1.86175749e-01 -1.95143014e-01
-7.07896277e-02 1.12946883e-01 -3.75278234e-01 4.67183620e-01
2.11966969e-02 1.78112909e-01 -4.91638511e-01 -4.68832672e-01
3.83330584e-01 1.93566620e-01 -6.63754225e-01 -2.58923918e-01
4.98016566e-01 1.20719683e+00 -1.23868549e+00 -4.30424601e-01
-1.19721875e-01 2.31182277e-02 -8.53921652e-01 4.61704671e-01
-8.48909259e-01 1.19508445e-01 -3.06824386e-01 7.13784933e-01
-5.63509725e-02 -6.20036721e-01 1.31569773e-01 2.03974321e-02
3.57737750e-01 7.00818658e-01 -7.80268788e-01 1.79594815e+00
-9.61803734e-01 5.05661488e-01 -1.54626340e-01 -7.72018731e-01
6.14705086e-01 4.38284650e-02 -2.58885235e-01 -6.08395755e-01
-1.08873233e-01 4.92277175e-01 4.49035279e-02 -7.53854156e-01
4.18735594e-01 -1.36740804e-01 -4.15864527e-01 5.48751473e-01
2.76930273e-01 -2.95151919e-01 4.00827467e-01 4.52219099e-01
9.53970373e-01 4.06955957e-01 4.41592127e-01 -1.92324042e-01
6.15900755e-01 7.22836480e-02 3.56430888e-01 1.01396370e+00
4.69790364e-04 4.33927327e-01 9.26179051e-01 -1.47828639e-01
-8.59992027e-01 -9.87119377e-01 -2.92385407e-02 1.49621665e+00
-5.89633733e-02 -4.84505951e-01 -8.68210375e-01 -1.11309898e+00
3.56910303e-02 1.33411491e+00 -5.62534034e-01 -1.35389969e-01
-7.45024443e-01 -6.56729937e-01 5.04527271e-01 4.80747074e-01
2.63707995e-01 -1.65611923e+00 -5.05977333e-01 2.16986299e-01
-2.90631026e-01 -1.27237833e+00 -4.80435073e-01 2.87823439e-01
-7.31059015e-01 -1.14706326e+00 -8.76661018e-02 -9.29913104e-01
6.56836033e-01 -3.53977263e-01 1.59210849e+00 1.90724716e-01
-2.32099012e-01 4.34798479e-01 -3.69901240e-01 -2.57334203e-01
-6.42938912e-01 1.92270875e-01 -3.32711130e-01 -1.90975636e-01
4.46560651e-01 -5.24441302e-01 -4.00999337e-01 -3.54038998e-02
-7.80840695e-01 2.59086639e-01 6.01832509e-01 1.22760224e+00
7.35497296e-01 -4.43486780e-01 7.83516407e-01 -1.36996758e+00
9.75196421e-01 -6.77728057e-01 -4.39837158e-01 6.13329232e-01
-5.62863767e-01 3.10722142e-01 1.08415174e+00 -4.28257674e-01
-1.04089928e+00 -6.13859817e-02 -1.13223292e-01 -1.57823250e-01
-2.93208688e-01 6.35869384e-01 -2.62497604e-01 3.86969656e-01
8.70324135e-01 2.62827128e-01 -2.93557793e-01 -2.73059905e-01
6.43688858e-01 4.94716346e-01 4.18081552e-01 -1.33896279e+00
4.84381318e-01 4.12661135e-02 -4.08961952e-01 -4.79632467e-01
-1.35134161e+00 -5.16149364e-02 -2.33329415e-01 1.61028817e-01
6.02096677e-01 -7.76184261e-01 -4.32010591e-01 2.11582959e-01
-1.10857999e+00 -9.16261315e-01 -4.59694624e-01 -4.82746065e-02
-6.06390595e-01 1.08073212e-01 -7.50556231e-01 -6.11130476e-01
-4.85342860e-01 -1.12304235e+00 1.08097446e+00 1.31826058e-01
-4.36428010e-01 -1.15021241e+00 -1.08141996e-01 5.33103585e-01
2.33945817e-01 9.29601118e-02 1.40596163e+00 -1.02647328e+00
-5.10018885e-01 3.51944380e-02 -5.50491996e-02 4.57696229e-01
-1.86505184e-01 -1.08202212e-01 -1.03989816e+00 -1.24000264e-02
-9.73144099e-02 -8.89255702e-01 8.14832926e-01 2.40832213e-02
1.42880535e+00 -6.05240941e-01 -6.96985424e-02 6.72358036e-01
1.41591287e+00 -4.75327633e-02 2.80837536e-01 3.57879519e-01
5.20165145e-01 7.42584109e-01 5.39232492e-01 1.79862902e-01
4.29148018e-01 2.84360737e-01 1.49907768e-01 3.63164067e-01
-1.09734625e-01 -5.87865233e-01 5.36815405e-01 5.76665103e-01
4.48447257e-01 -2.03170523e-01 -1.15684795e+00 7.25157559e-01
-1.81103957e+00 -8.38758171e-01 2.06514224e-01 1.87490857e+00
1.31765509e+00 2.81045794e-01 -9.67793465e-02 -2.01871052e-01
4.88646895e-01 4.37628999e-02 -7.18323171e-01 -4.69864488e-01
-1.87118888e-01 4.20309663e-01 -2.09212959e-01 7.60155737e-01
-9.05692518e-01 1.13398445e+00 5.30265808e+00 9.54803348e-01
-9.81419563e-01 1.75035939e-01 8.09202433e-01 -2.81651348e-01
-7.13573337e-01 6.32377788e-02 -8.58447433e-01 5.76407373e-01
8.39815021e-01 -2.41810411e-01 6.08142495e-01 1.20174587e+00
-1.98443174e-01 3.93605512e-03 -1.52801836e+00 9.10249114e-01
1.47249922e-01 -1.31896985e+00 2.76478827e-01 -5.19689620e-01
7.78156638e-01 7.68811777e-02 1.46535486e-01 8.45635176e-01
2.87440240e-01 -9.64965820e-01 7.39612281e-01 1.62355348e-01
7.15765715e-01 -5.75468600e-01 4.18110818e-01 4.68339175e-01
-7.78111041e-01 -4.93209273e-01 -2.01136559e-01 -5.25963232e-02
4.60858569e-02 5.72194993e-01 -7.99916983e-01 2.11524129e-01
4.47168320e-01 4.84746248e-01 -6.83423042e-01 5.64961851e-01
-9.03521419e-01 8.98143291e-01 -1.85260728e-01 -5.13186932e-01
3.22912812e-01 -2.08277162e-03 4.84061331e-01 1.55039334e+00
7.42430985e-02 1.01702370e-01 5.96867912e-02 1.36487460e+00
-4.05987114e-01 2.21553758e-01 -2.79930413e-01 -6.61526471e-02
6.36297643e-01 1.17390788e+00 -2.98603415e-01 -5.26157200e-01
-1.79116935e-01 7.86484063e-01 7.17757285e-01 4.24214810e-01
-6.79391086e-01 -4.91921008e-01 4.63412315e-01 -7.37068430e-02
2.52852947e-01 1.06792562e-01 -3.25860828e-01 -1.34660721e+00
3.01185131e-01 -1.22356033e+00 5.55988371e-01 -8.25101852e-01
-1.59091640e+00 6.15672290e-01 9.12005678e-02 -8.28823805e-01
-4.77350742e-01 -8.30227137e-01 -8.64066839e-01 7.16532648e-01
-1.69214594e+00 -1.07743192e+00 -6.21688999e-02 4.04322773e-01
8.94129753e-01 -1.54500365e-01 7.47016370e-01 2.24175602e-02
-5.49720764e-01 7.81812608e-01 -1.46171883e-01 2.23432481e-02
6.59137249e-01 -1.65344179e+00 4.51365590e-01 7.85513699e-01
2.38303527e-01 7.24897921e-01 5.28688729e-01 -4.75410819e-01
-1.35788929e+00 -1.11752141e+00 1.26062047e+00 -7.25454926e-01
9.50547516e-01 -5.45604110e-01 -8.98742914e-01 7.68854320e-01
7.38766491e-02 -1.08405897e-04 8.80990863e-01 2.00807273e-01
-5.81322491e-01 1.03980303e-02 -9.82098281e-01 7.89916456e-01
1.15624118e+00 -8.14431846e-01 -1.08853984e+00 4.95686412e-01
1.05738509e+00 -5.20821333e-01 -3.64617527e-01 1.76560283e-01
3.52557421e-01 -8.68644595e-01 8.45649183e-01 -8.76280427e-01
1.18377292e+00 1.98238194e-02 -2.67930299e-01 -1.31788242e+00
4.00880817e-03 -6.19163811e-01 -3.66899371e-01 1.21426761e+00
9.40740407e-01 -5.58115602e-01 5.43707967e-01 6.31644070e-01
-2.75850624e-01 -1.24825084e+00 -5.42907596e-01 -6.14896357e-01
2.39303485e-01 -6.26531184e-01 6.46751940e-01 9.59614694e-01
1.15920164e-01 7.20386982e-01 1.11242414e-01 -8.49209428e-02
5.65933228e-01 5.13243377e-01 5.71823597e-01 -7.93820739e-01
-8.64687264e-01 -6.34661376e-01 3.53587806e-01 -1.12237620e+00
5.65286696e-01 -1.32852423e+00 7.64677748e-02 -1.36289334e+00
1.53413445e-01 -5.70357084e-01 -2.43449658e-01 5.91884971e-01
-6.91601336e-01 -2.75953352e-01 2.80122638e-01 2.39636190e-02
-7.92695045e-01 3.94471109e-01 1.01763225e+00 -1.27675366e-02
-2.09675565e-01 -9.29035097e-02 -8.78793418e-01 7.92046249e-01
9.79542375e-01 -3.75528425e-01 -5.61802030e-01 -6.08486772e-01
7.23259032e-01 -7.85263479e-02 4.90000457e-01 -6.90629542e-01
9.37947258e-02 -2.17270762e-01 1.36134595e-01 -2.36007884e-01
1.77090257e-01 -3.75512689e-01 -3.96283001e-01 1.98715404e-01
-1.04077816e+00 2.90895831e-02 1.61294475e-01 4.37612772e-01
-1.82688236e-01 -6.00567043e-01 5.52640378e-01 -3.61265332e-01
-8.52467179e-01 -1.43725621e-02 1.70314386e-01 8.11800957e-01
5.59498191e-01 2.79531538e-01 -5.89269996e-01 -1.68791249e-01
-6.70025170e-01 3.57703120e-01 2.92219192e-01 3.97089332e-01
5.31880975e-01 -1.02995574e+00 -7.36995518e-01 6.69742934e-03
3.25908214e-01 1.74801826e-01 1.35621294e-01 5.04143417e-01
-2.57279932e-01 3.56523544e-01 3.56821179e-01 -4.11230683e-01
-9.02749300e-01 5.85859954e-01 2.98209876e-01 -6.25375271e-01
-3.48114759e-01 1.18837619e+00 1.51617795e-01 -9.81017411e-01
2.38605812e-01 -4.61949468e-01 4.83145379e-02 -1.18501142e-01
4.91107941e-01 -2.16011517e-02 7.96845369e-03 3.39073204e-02
-1.62650958e-01 2.50550985e-01 -1.36005625e-01 -4.86803614e-02
1.07659507e+00 1.53844804e-01 -2.25735247e-01 5.54372430e-01
1.16781497e+00 2.32501533e-02 -1.14808464e+00 -3.48492593e-01
2.87166506e-01 -5.85420653e-02 -4.38631803e-01 -1.31854844e+00
-4.98765647e-01 8.29349339e-01 -9.26219895e-02 6.05784319e-02
9.22349095e-01 1.83524877e-01 9.00521100e-01 8.21029723e-01
2.19503477e-01 -1.04498398e+00 4.24333543e-01 7.17827618e-01
1.14788520e+00 -1.32566345e+00 -3.32650155e-01 -2.27025583e-01
-7.25224495e-01 1.00146949e+00 9.28548455e-01 -1.29865468e-01
3.62916410e-01 1.99249566e-01 -3.17683481e-02 -8.13187379e-03
-1.32663894e+00 3.08379643e-02 1.81244001e-01 2.79400140e-01
6.06746852e-01 7.59474263e-02 -1.14246264e-01 1.05350816e+00
-6.07735515e-01 -1.58043385e-01 2.78266162e-01 9.88514066e-01
-1.96285352e-01 -1.20628881e+00 -8.70143995e-02 4.90141928e-01
-4.20286924e-01 -5.07409453e-01 -5.58171034e-01 6.72522962e-01
1.46443546e-01 8.03433955e-01 -2.54760087e-01 -9.86832604e-02
3.38543653e-01 5.98041594e-01 4.78117347e-01 -8.62638295e-01
-9.02422905e-01 -4.68617320e-01 2.86374211e-01 -6.15978837e-01
-8.98790210e-02 -5.51829040e-01 -1.32051730e+00 1.43702611e-01
-1.40916049e-01 2.38907665e-01 5.82666636e-01 1.00294840e+00
5.95203817e-01 3.91872704e-01 4.82482970e-01 -4.46248382e-01
-9.81665254e-01 -7.75727212e-01 1.22050317e-02 6.81861818e-01
3.47242594e-01 -1.71230212e-01 -8.29245448e-01 1.06225699e-01] | [10.797913551330566, 8.374439239501953] |
3dd9f375-ac8e-4ac0-b864-7eb7951c05b1 | airiva-a-deep-generative-model-of-adaptive | 2304.13737 | null | https://arxiv.org/abs/2304.13737v1 | https://arxiv.org/pdf/2304.13737v1.pdf | AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires | Recent advances in immunomics have shown that T-cell receptor (TCR) signatures can accurately predict active or recent infection by leveraging the high specificity of TCR binding to disease antigens. However, the extreme diversity of the adaptive immune repertoire presents challenges in reliably identifying disease-specific TCRs. Population genetics and sequencing depth can also have strong systematic effects on repertoires, which requires careful consideration when developing diagnostic models. We present an Adaptive Immune Repertoire-Invariant Variational Autoencoder (AIRIVA), a generative model that learns a low-dimensional, interpretable, and compositional representation of TCR repertoires to disentangle such systematic effects in repertoires. We apply AIRIVA to two infectious disease case-studies: COVID-19 (natural infection and vaccination) and the Herpes Simplex Virus (HSV-1 and HSV-2), and empirically show that we can disentangle the individual disease signals. We further demonstrate AIRIVA's capability to: learn from unlabelled samples; generate in-silico TCR repertoires by intervening on the latent factors; and identify disease-associated TCRs validated using TCR annotations from external assay data. | ['Edward Meeds', 'Julia Greissl', 'Javier Gonzalez', 'Javier Zazo', 'Rebecca Elyanow', 'Steven Woodhouse', 'Max Ilse', 'Sahra Ghalebikesabi', 'Paidamoyo Chapfuwa', 'Niranjani Prasad', 'Melanie F. Pradier'] | 2023-04-26 | null | null | null | null | ['specificity'] | ['natural-language-processing'] | [ 8.93487334e-01 -6.09073102e-01 -3.81831437e-01 -4.88533705e-01
-7.73082495e-01 -6.91409528e-01 5.02361238e-01 7.95440823e-02
-3.54734898e-01 9.62970078e-01 2.59630650e-01 -4.65977460e-01
-3.01497400e-01 -5.29209197e-01 -7.64253318e-01 -1.05758643e+00
-2.50623584e-01 1.46345472e+00 -4.23900813e-01 3.53545300e-03
-3.00508410e-01 3.96601945e-01 -1.20082819e+00 4.30049032e-01
6.66028798e-01 3.00174087e-01 5.38987368e-02 1.19346273e+00
-5.92624396e-02 1.24397427e-01 -4.30761456e-01 1.22037344e-01
-1.66999191e-01 -4.37035173e-01 -1.37280613e-01 -2.26461843e-01
-9.59426984e-02 -3.32812637e-01 -9.92370620e-02 5.16605079e-01
6.53568923e-01 -5.23277938e-01 1.33534503e+00 -1.14304221e+00
-4.82308477e-01 2.63061613e-01 -5.34778357e-01 1.55532315e-01
7.39027746e-03 4.34098691e-01 1.02721405e+00 -3.77806604e-01
1.32078671e+00 1.42425847e+00 9.42314923e-01 6.45498216e-01
-2.24686742e+00 -5.54428041e-01 -2.11519986e-01 -2.34887168e-01
-1.17353582e+00 -5.53864278e-02 5.80877662e-01 -1.02970111e+00
1.24873590e+00 3.99468005e-01 9.05259848e-01 1.86123109e+00
5.91618717e-01 7.00310469e-01 1.35575545e+00 -1.31369367e-01
1.80128500e-01 -3.90078217e-01 3.68299067e-01 4.92284507e-01
6.17515519e-02 6.08706295e-01 -1.86159790e-01 -1.08623648e+00
8.61509442e-01 3.90007645e-01 -1.76503807e-01 -3.98811579e-01
-1.04502702e+00 1.30663943e+00 -2.71326780e-01 9.95056480e-02
-6.24775171e-01 1.65513128e-01 6.21428370e-01 1.45800292e-01
2.71437347e-01 2.29758099e-01 -6.57785296e-01 9.10224393e-02
-5.76809287e-01 1.14836939e-01 5.68268359e-01 2.22419903e-01
6.80891037e-01 1.17888071e-01 -3.50409299e-02 9.95199919e-01
2.14636594e-01 8.23104441e-01 1.66807920e-01 -3.53684068e-01
-5.07635057e-01 3.56084287e-01 -2.90129006e-01 -5.19586802e-01
-6.18853509e-01 -3.61826926e-01 -8.30557764e-01 -2.08578229e-01
1.85322136e-01 -3.23941171e-01 -1.11589766e+00 2.14759278e+00
4.76137757e-01 1.55640841e-01 -9.21877548e-02 7.29732692e-01
2.74439275e-01 3.81631702e-01 4.87652123e-01 -4.92112458e-01
1.55589759e+00 5.99078164e-02 -5.78665435e-01 -5.65922782e-02
3.17317516e-01 -5.26654840e-01 6.13864660e-01 2.84347177e-01
-3.15326780e-01 2.51997565e-03 -7.68637776e-01 2.17134133e-01
-1.95930347e-01 -3.91249478e-01 1.13013685e+00 4.36155558e-01
-8.32096696e-01 2.71563679e-01 -9.63092566e-01 -4.64192480e-01
2.49870136e-01 5.10481656e-01 -2.23180547e-01 1.77601278e-02
-1.33367813e+00 6.38946474e-01 2.65701950e-01 -1.46025106e-01
-1.19512606e+00 -9.95020330e-01 -4.60444957e-01 -4.62467343e-01
5.84332012e-02 -1.33900070e+00 6.91340566e-01 -9.95115519e-01
-1.13755322e+00 9.23138022e-01 -5.12277931e-02 -1.75512433e-01
5.97460940e-02 2.96128184e-01 -5.63260436e-01 -1.98205970e-02
-2.19402552e-01 5.23705721e-01 8.35555255e-01 -9.95347619e-01
-1.85441762e-01 -7.05995739e-01 -7.42999613e-01 -2.97456980e-01
5.21910310e-01 -1.58921316e-01 8.81718323e-02 -7.30875611e-01
-4.93056774e-01 -1.13766897e+00 -3.08650017e-01 -2.94665277e-01
-4.92183983e-01 -6.67025298e-02 1.86863616e-01 -5.62159061e-01
6.62644625e-01 -1.73582101e+00 5.79920888e-01 2.10046619e-01
3.91222805e-01 6.50842264e-02 -4.12841469e-01 6.47887111e-01
9.04291123e-02 2.10032035e-02 -2.95214593e-01 2.74025738e-01
9.50550213e-02 6.89758956e-01 -3.28869820e-01 7.52310336e-01
4.04208153e-01 1.13333166e+00 -7.29932249e-01 -2.45499328e-01
3.55698131e-02 1.21977961e+00 -7.55044639e-01 2.64961272e-01
-7.48889923e-01 5.31753838e-01 -3.45255077e-01 6.50910974e-01
4.55403358e-01 -3.98378104e-01 1.08064461e+00 -9.37375873e-02
2.73790210e-01 -1.67522684e-01 -4.80508983e-01 9.20889974e-01
-1.91398323e-01 5.39668977e-01 2.12244540e-01 -7.02526927e-01
4.17246997e-01 -3.62277552e-02 2.37473205e-01 -4.98824060e-01
3.66708338e-01 1.50228009e-01 1.92601353e-01 -2.52271742e-01
-2.82786340e-01 -6.71380103e-01 -1.81962758e-01 6.89586997e-01
2.00089589e-01 3.30432475e-01 -3.66028130e-01 -1.63955688e-01
1.03271031e+00 -3.05831909e-01 1.00271173e-01 -9.00247097e-02
-4.19566408e-02 2.60587245e-01 9.12129104e-01 9.80474234e-01
-7.95912072e-02 4.37793046e-01 6.83895051e-01 -6.75719678e-01
-1.39731669e+00 -1.39770532e+00 -5.44765353e-01 1.17090118e+00
-6.45017087e-01 3.90341908e-01 -3.09541523e-01 -3.09654772e-01
5.19819856e-01 5.16803145e-01 -1.00548530e+00 -1.02810055e-01
-3.49877834e-01 -1.29903686e+00 1.15226877e+00 4.79384631e-01
-7.25195885e-01 -6.42594874e-01 -7.74349421e-02 2.41410881e-01
2.72732005e-02 -5.34515798e-01 -4.00651693e-01 5.68042815e-01
-5.60098290e-01 -1.47207439e+00 -6.77739978e-01 -5.32121658e-01
6.82948470e-01 -3.72291863e-01 1.01225495e+00 -1.06953964e-01
-1.09061551e+00 5.68073809e-01 2.74735540e-01 -4.08140749e-01
-8.14910114e-01 -2.23400131e-01 5.77015460e-01 -1.07676230e-01
4.79703009e-01 -4.52973425e-01 -6.80079937e-01 6.04624115e-02
-1.04551399e+00 -4.25803512e-02 7.17991173e-01 1.49832797e+00
1.13263929e+00 -3.49429071e-01 6.55799806e-01 -1.15676725e+00
6.59210980e-01 -8.14689934e-01 -5.91547549e-01 4.35514897e-01
-5.01609564e-01 2.77438879e-01 2.60794729e-01 -8.40730667e-01
-9.68754411e-01 -1.48716196e-01 -4.10665393e-01 -3.37901890e-01
-3.41103554e-01 4.47218210e-01 2.11332381e-01 4.26730961e-01
3.46662968e-01 6.44664526e-01 4.09456998e-01 -2.46175617e-01
2.81981617e-01 6.68157697e-01 2.93098748e-01 -5.36087990e-01
1.38932973e-01 5.92459977e-01 3.56852189e-02 -1.08471382e+00
-2.87178129e-01 -2.93966144e-01 -2.04875126e-01 1.42601401e-01
1.06249726e+00 -8.76561284e-01 -1.18438840e+00 5.40185213e-01
-7.69803524e-01 -7.22681582e-01 2.14349002e-01 6.01138651e-01
-6.70457304e-01 7.35906810e-02 -1.12229204e+00 -7.23065257e-01
-5.44809163e-01 -1.34778416e+00 1.36987746e+00 -2.96514720e-01
-5.87208271e-01 -1.33504999e+00 1.12252653e+00 2.50108957e-01
4.41179097e-01 5.67018926e-01 1.74073470e+00 -1.04251182e+00
-3.26455534e-01 4.23600003e-02 1.88179333e-02 -1.38235256e-01
4.77660485e-02 3.61825198e-01 -8.50076199e-01 -4.77698505e-01
-3.76253247e-01 -5.60777664e-01 9.93285239e-01 7.32979476e-01
3.60692561e-01 -1.69149011e-01 -5.36354601e-01 8.40767205e-01
1.47498488e+00 2.73032486e-01 1.34631068e-01 -1.54097408e-01
4.11256850e-01 6.43947959e-01 4.58254628e-02 2.86498636e-01
5.38320504e-02 7.01423407e-01 -2.39160091e-01 -5.38797583e-03
2.92493343e-01 -4.91163552e-01 2.56487489e-01 8.34769547e-01
3.80236149e-01 -3.68596166e-01 -8.73583913e-01 3.27307850e-01
-1.51866758e+00 -7.24341750e-01 -3.10466792e-02 1.86696696e+00
1.03616822e+00 -1.51017368e-01 3.35831940e-01 -5.90598822e-01
7.77258992e-01 -7.05384016e-02 -9.79270518e-01 -6.29224062e-01
-6.67022645e-01 3.10853124e-01 2.83275247e-01 6.66731656e-01
-5.08705735e-01 3.70553702e-01 8.04525089e+00 8.58722210e-01
-1.24766660e+00 -3.41414250e-02 6.42112911e-01 -1.55563727e-01
-1.01931584e+00 -2.22178683e-01 -6.06699407e-01 2.87047535e-01
9.90899444e-01 1.55875221e-01 5.87493777e-01 3.77000213e-01
-2.84933776e-01 2.49807969e-01 -1.21034122e+00 7.41529167e-01
-1.07265070e-01 -1.39682496e+00 1.67311773e-01 2.61162192e-01
4.71452981e-01 4.18341011e-01 4.22119528e-01 3.77065003e-01
7.45155931e-01 -1.08447933e+00 -2.41464719e-01 6.01010442e-01
1.12796509e+00 -1.06144083e+00 7.74595141e-01 2.40545675e-01
-3.94870371e-01 3.15394461e-01 -1.60015419e-01 3.71591240e-01
1.83672339e-01 6.89027011e-01 -1.47360563e+00 -1.42519727e-01
5.05775623e-02 2.74319630e-02 2.66151018e-02 7.67416805e-02
7.96160325e-02 6.45459950e-01 -3.76711577e-01 -1.51717439e-01
-1.38017014e-01 -3.04866135e-02 6.60641193e-01 1.28151298e+00
-2.22286910e-01 2.82915801e-01 1.07771028e-02 9.09631729e-01
3.43211263e-01 -2.36894250e-01 -5.26826680e-01 -7.15607822e-01
2.90727645e-01 1.02661312e+00 -4.99162138e-01 -1.48168743e-01
1.18983686e-01 7.91828811e-01 2.61031151e-01 4.45143580e-01
-5.45689940e-01 -2.67789029e-02 1.40699017e+00 -1.60002768e-01
4.44499254e-01 1.99294463e-01 4.45348710e-01 -9.94884670e-01
-9.02748585e-01 -1.17295957e+00 5.86178124e-01 -4.96752650e-01
-1.79163289e+00 4.34467643e-01 -1.88703507e-01 -2.42559060e-01
-7.20732033e-01 -7.48593152e-01 4.47888765e-03 9.07223761e-01
-8.84774208e-01 -1.14068878e+00 4.63668883e-01 2.93151528e-01
2.93589503e-01 -5.83055057e-02 1.05935085e+00 4.37181965e-02
-8.25202763e-01 6.68025374e-01 5.81809342e-01 -1.12781398e-01
6.10528827e-01 -1.04963028e+00 3.08069348e-01 -1.90098397e-02
-2.13998526e-01 1.04133749e+00 1.00025034e+00 -1.13868248e+00
-2.00639677e+00 -8.95121455e-01 5.07363379e-01 -6.99697971e-01
8.39986920e-01 -6.93776250e-01 -9.18894291e-01 9.07275558e-01
-2.85992417e-02 -4.41321254e-01 1.47786212e+00 4.01215971e-01
-8.41282606e-01 3.05080920e-01 -1.30496764e+00 7.00566590e-01
8.11174273e-01 -9.51869667e-01 -5.81816077e-01 2.68605471e-01
8.90771031e-01 6.42575789e-03 -1.04178834e+00 3.16660881e-01
1.15994501e+00 -7.53500581e-01 1.17098069e+00 -1.20967090e+00
5.05980961e-02 -7.42749721e-02 -3.01790953e-01 -1.36823726e+00
-4.06584352e-01 -4.18541312e-01 1.86174288e-01 7.79866636e-01
1.41111597e-01 -9.81062591e-01 4.51323926e-01 1.90421343e-01
3.65099102e-01 -6.84393346e-01 -1.03288770e+00 -2.93443829e-01
-3.76683697e-02 -2.77730078e-01 5.62311649e-01 1.06953979e+00
-3.70090902e-01 4.09469128e-01 -3.80522519e-01 -2.69221235e-02
9.83065367e-01 3.24506789e-01 6.37543619e-01 -1.19259787e+00
-8.35193098e-01 -3.66943240e-01 -3.09360266e-01 -3.76067191e-01
3.20928097e-01 -8.95526826e-01 -4.47129793e-02 -8.67416441e-01
8.49167943e-01 -4.91382450e-01 -4.03539509e-01 1.25696838e-01
-2.24961564e-01 8.43400788e-03 -4.94034827e-01 2.28422489e-02
-3.37948531e-01 2.97371596e-01 8.45781028e-01 -2.68618971e-01
-6.79311007e-02 -4.89349574e-01 -5.78318119e-01 4.88979936e-01
4.98612940e-01 -5.27431846e-01 -3.37222159e-01 -3.04237276e-01
3.58926952e-01 4.92836297e-01 2.06950814e-01 9.91196632e-02
-2.26182461e-01 -5.96046269e-01 8.57119858e-01 -8.73569250e-01
2.37542629e-01 -3.90718639e-01 1.01109684e+00 9.60219979e-01
-5.15809953e-01 1.07774191e-01 3.55970889e-01 9.93924737e-01
3.58525634e-01 5.73496461e-01 4.69626874e-01 1.05737381e-01
-2.38460213e-01 2.83079267e-01 -1.13555241e+00 1.98852628e-01
6.02133870e-01 4.86926325e-02 -5.27344406e-01 1.69038530e-02
-6.22763991e-01 -1.53246634e-02 7.60904968e-01 4.49213952e-01
5.83523273e-01 -1.11045492e+00 -8.89089465e-01 5.43064833e-01
2.12683499e-01 -6.49886370e-01 8.86351347e-01 7.75457859e-01
-6.22328341e-01 6.35123968e-01 -3.82916927e-01 -1.06794477e+00
-1.24726892e+00 8.87073815e-01 2.61377722e-01 -3.91490966e-01
-1.60717398e-01 8.01067233e-01 6.62120521e-01 -9.03889358e-01
-1.73965693e-01 2.41961017e-01 2.09333122e-01 3.59803915e-01
3.55010509e-01 1.87369674e-01 -4.16836470e-01 -5.71691811e-01
-6.22243106e-01 5.35421669e-01 -3.19961280e-01 2.97668073e-02
1.51596892e+00 2.62704313e-01 -2.46187299e-01 5.94351828e-01
1.29610550e+00 -1.97991535e-01 -9.07049596e-01 -1.15349874e-01
-2.94720799e-01 -4.27116491e-02 -2.23109037e-01 -8.42062116e-01
-5.51345468e-01 6.52414441e-01 8.39846134e-01 -3.59032243e-01
8.51869047e-01 -8.93331971e-03 8.20084274e-01 3.38026099e-02
5.25020778e-01 -7.11298764e-01 -2.30140716e-01 9.24918279e-02
5.54859042e-01 -8.92389596e-01 -1.76659852e-01 7.85417631e-02
-5.19373178e-01 5.94999433e-01 3.21206786e-02 1.45716071e-01
1.67166427e-01 5.45146465e-01 3.10840696e-01 -3.40584993e-01
-1.51630700e+00 4.86249924e-02 3.19819629e-01 1.00222790e+00
2.68644869e-01 5.90428650e-01 -1.06239505e-01 5.10828018e-01
3.51612151e-01 -1.74609959e-01 3.18926387e-02 5.24133325e-01
-1.50323972e-01 -1.35611212e+00 -3.30258012e-01 6.68036640e-01
-5.71403086e-01 -1.17031555e-03 -6.83715045e-01 7.65452445e-01
-1.00785203e-03 2.76513368e-01 5.55473685e-01 -3.30555469e-01
3.57641317e-02 3.51388186e-01 6.91939831e-01 -2.83033758e-01
-5.41295946e-01 5.71678221e-01 1.86109290e-01 -2.06970915e-01
3.74454856e-02 -8.04466963e-01 -9.46839511e-01 -5.29844105e-01
-2.12824553e-01 -4.08976376e-02 4.88943249e-01 5.13898849e-01
6.92336679e-01 6.04542732e-01 3.59699577e-01 -3.67936254e-01
-5.23800135e-01 -5.19360781e-01 -5.75644255e-01 3.46946597e-01
7.34796703e-01 -6.28873825e-01 -6.20531023e-01 -3.55703443e-01] | [5.007588863372803, 5.467929363250732] |
baf4ad9a-f0c7-48b8-a31a-c1aadf6ca3dd | explicit-visual-prompting-for-low-level | 2303.10883 | null | https://arxiv.org/abs/2303.10883v2 | https://arxiv.org/pdf/2303.10883v2.pdf | Explicit Visual Prompting for Low-Level Structure Segmentations | We consider the generic problem of detecting low-level structures in images, which includes segmenting the manipulated parts, identifying out-of-focus pixels, separating shadow regions, and detecting concealed objects. Whereas each such topic has been typically addressed with a domain-specific solution, we show that a unified approach performs well across all of them. We take inspiration from the widely-used pre-training and then prompt tuning protocols in NLP and propose a new visual prompting model, named Explicit Visual Prompting (EVP). Different from the previous visual prompting which is typically a dataset-level implicit embedding, our key insight is to enforce the tunable parameters focusing on the explicit visual content from each individual image, i.e., the features from frozen patch embeddings and the input's high-frequency components. The proposed EVP significantly outperforms other parameter-efficient tuning protocols under the same amount of tunable parameters (5.7% extra trainable parameters of each task). EVP also achieves state-of-the-art performances on diverse low-level structure segmentation tasks compared to task-specific solutions. Our code is available at: https://github.com/NiFangBaAGe/Explicit-Visual-Prompt. | ['Xiaodong Cun', 'Chi-Man Pun', 'Xi Shen', 'Weihuang Liu'] | 2023-03-20 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Liu_Explicit_Visual_Prompting_for_Low-Level_Structure_Segmentations_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Liu_Explicit_Visual_Prompting_for_Low-Level_Structure_Segmentations_CVPR_2023_paper.pdf | cvpr-2023-1 | ['image-manipulation-detection', 'defocus-blur-detection', 'visual-prompting', 'camouflaged-object-segmentation', 'foreground-segmentation', 'shadow-detection'] | ['computer-vision', 'computer-vision', 'computer-vision', 'computer-vision', 'computer-vision', 'computer-vision'] | [ 3.58408034e-01 2.17143402e-01 -2.73879647e-01 -4.09143388e-01
-1.12621307e+00 -8.06420326e-01 4.30613041e-01 6.09384477e-02
-2.92796493e-01 1.77948728e-01 -5.38582392e-02 -3.18394184e-01
1.75756857e-01 -4.20756936e-01 -1.05805218e+00 -9.10595059e-01
1.30261898e-01 1.09301887e-01 7.64703691e-01 1.81681603e-01
4.33495462e-01 3.38509321e-01 -1.37480235e+00 4.48437750e-01
7.11655319e-01 9.83484089e-01 5.40689349e-01 7.72548199e-01
-2.59969473e-01 5.50826132e-01 -4.84101087e-01 -2.12294102e-01
2.14921564e-01 7.12419348e-03 -8.95661950e-01 2.54242927e-01
7.65807986e-01 -5.23504496e-01 -1.52382687e-01 9.47622359e-01
5.48373103e-01 -3.73146199e-02 5.66989124e-01 -1.33041322e+00
-8.03151011e-01 3.17212582e-01 -9.25474167e-01 2.54749328e-01
9.87891033e-02 4.71367806e-01 1.14401770e+00 -9.87577856e-01
6.38060331e-01 1.14664161e+00 4.86283213e-01 7.44682968e-01
-1.43485475e+00 -5.42468548e-01 6.46632254e-01 2.16563269e-01
-1.14316344e+00 -3.64005774e-01 9.81356502e-01 -6.52583897e-01
7.11016774e-01 9.89277214e-02 3.52332801e-01 1.16340804e+00
-1.43838108e-01 1.21218204e+00 1.06926692e+00 -3.28682899e-01
1.35745049e-01 1.38361856e-01 4.99233097e-01 9.42988217e-01
1.61199659e-01 5.10437228e-02 -5.09405673e-01 -1.04213387e-01
6.95928156e-01 -1.85512528e-01 -4.11116719e-01 -4.40188646e-01
-1.06321168e+00 6.13082349e-01 4.40909028e-01 7.06901774e-02
-6.39958456e-02 3.75023901e-01 2.54910886e-01 -2.19794661e-01
4.28968459e-01 1.65219247e-01 -6.84997857e-01 1.91840395e-01
-9.28447962e-01 1.94097742e-01 5.16919017e-01 1.01293981e+00
1.04688370e+00 -7.40329549e-02 -5.21844327e-01 6.45717323e-01
3.58382851e-01 3.56226146e-01 -1.46837803e-02 -1.01402044e+00
4.11168158e-01 6.11274838e-01 1.31876737e-01 -8.77055109e-01
-2.74227202e-01 -3.31615776e-01 -4.33364123e-01 2.38248721e-01
6.16268873e-01 -1.68203369e-01 -1.39071393e+00 1.69223368e+00
6.05488539e-01 5.01132667e-01 -3.87059033e-01 9.70662177e-01
1.18280852e+00 9.38010931e-01 2.39543676e-01 1.82627961e-01
1.69346416e+00 -1.30173075e+00 -4.85035270e-01 -6.00189447e-01
2.00915053e-01 -7.86310494e-01 1.44624102e+00 2.18355954e-01
-9.62849498e-01 -5.73607445e-01 -9.57090795e-01 -6.70875132e-01
-3.43331546e-01 3.55397940e-01 5.83483696e-01 3.90349597e-01
-1.01868129e+00 1.70660123e-01 -6.30681574e-01 -1.60227567e-01
5.52575648e-01 2.03530565e-01 -1.41777009e-01 3.44768092e-02
-6.88361228e-01 3.29434663e-01 1.94207028e-01 1.76325679e-01
-1.09532726e+00 -1.12123609e+00 -8.31718206e-01 7.76018277e-02
7.37879097e-01 -6.07675850e-01 1.29385972e+00 -8.17334533e-01
-1.31465459e+00 1.24826062e+00 -3.26601326e-01 -1.34382054e-01
4.77007508e-01 -4.14760977e-01 2.81860977e-01 3.70178491e-01
9.34800804e-02 1.05084050e+00 1.12249696e+00 -1.61321855e+00
-4.82195050e-01 -7.45210126e-02 1.94721699e-01 -5.10035222e-03
-1.69569090e-01 9.84991044e-02 -1.11099172e+00 -5.74749112e-01
-1.75438255e-01 -7.44136274e-01 -1.22966386e-01 5.54874361e-01
-7.13993609e-01 -2.10654631e-01 9.80263352e-01 -6.66712523e-01
9.08011794e-01 -2.52527547e+00 -3.80536020e-02 -1.93737417e-01
4.44466799e-01 3.21734220e-01 -3.78322184e-01 8.51028934e-02
1.85178101e-01 1.10626109e-01 -4.76854771e-01 -6.05319679e-01
1.54883608e-01 2.77471066e-01 -4.28354651e-01 4.74919468e-01
3.28598142e-01 1.15898085e+00 -7.75513291e-01 -8.82298410e-01
3.94386172e-01 5.99977136e-01 -4.53341573e-01 3.81682009e-01
-5.96329629e-01 3.85228038e-01 -5.58965504e-01 8.35200608e-01
9.29465175e-01 -6.35916770e-01 6.30189851e-02 -4.09930050e-01
-8.64359289e-02 9.95635688e-02 -9.43269610e-01 1.66421938e+00
-1.93510011e-01 6.88797176e-01 4.68713224e-01 -8.86537969e-01
6.41852677e-01 4.85552549e-02 2.95842141e-01 -7.46190608e-01
1.14022948e-01 -9.68887750e-03 -4.00588334e-01 -6.18788421e-01
3.93036872e-01 4.96157259e-01 -6.31548688e-02 3.02619427e-01
1.38526529e-01 -6.77978620e-02 3.09750400e-02 4.04575318e-01
9.75997567e-01 2.75801092e-01 3.42265487e-01 -1.87052727e-01
3.54250461e-01 -5.41149378e-02 6.44641757e-01 7.94104993e-01
-4.92940605e-01 7.81203508e-01 7.11170435e-01 -2.93722957e-01
-7.92059958e-01 -1.12904811e+00 -1.42560139e-01 1.49082148e+00
5.59822023e-01 -4.92510080e-01 -9.17810500e-01 -8.93589795e-01
1.62490636e-01 3.40658784e-01 -9.16019678e-01 4.00933206e-01
-6.83758080e-01 -3.87080312e-01 1.98719457e-01 5.31591117e-01
4.41716582e-01 -1.16813171e+00 -8.16073358e-01 -1.07559212e-01
-2.17292398e-01 -1.50136256e+00 -7.11608171e-01 4.10019547e-01
-5.54418623e-01 -1.16317153e+00 -7.76219070e-01 -8.71857524e-01
7.70393789e-01 4.71930951e-01 1.17848408e+00 2.80116975e-01
-5.25482774e-01 6.11264169e-01 -2.40470678e-01 -3.25347245e-01
1.59800202e-01 1.40557751e-01 -7.17541575e-01 1.05783358e-01
-5.56579791e-03 -3.72305155e-01 -9.07411933e-01 2.59003043e-01
-8.48385990e-01 2.55838990e-01 6.87031031e-01 6.53766870e-01
8.88503253e-01 -4.04126704e-01 2.18874607e-02 -1.18337834e+00
2.55411506e-01 -2.51607418e-01 -7.16693997e-01 3.56491804e-01
-2.17047051e-01 6.02569990e-02 4.33268070e-01 -6.80124521e-01
-1.04270875e+00 1.63315311e-01 -3.91062908e-02 -5.03636062e-01
-3.65533412e-01 -1.61675230e-01 -2.32910782e-01 -2.07147002e-01
4.43095237e-01 2.22415596e-01 -4.79408890e-01 -5.73019147e-01
6.09057188e-01 3.19270611e-01 7.17501998e-01 -8.15614402e-01
9.28381681e-01 6.12516046e-01 -2.52063334e-01 -7.86045730e-01
-1.14873087e+00 -7.59702682e-01 -4.81158644e-01 -1.65094435e-01
9.75370526e-01 -6.93892956e-01 -7.70306826e-01 4.82085258e-01
-1.48070514e+00 -8.32300305e-01 -1.56560481e-01 -2.31460184e-01
-5.53909123e-01 4.76365656e-01 -6.03338122e-01 -6.83827519e-01
-4.24878329e-01 -1.33247197e+00 1.61086476e+00 1.93143919e-01
1.10593833e-01 -7.76988685e-01 -1.19854920e-01 4.04201388e-01
1.69094458e-01 3.13230664e-01 9.48943734e-01 -3.12839180e-01
-1.10047364e+00 3.99704397e-01 -6.61285281e-01 3.36087853e-01
-1.40486434e-01 1.59969315e-01 -1.26502252e+00 -1.48784116e-01
-1.69031382e-01 -3.53030533e-01 1.06093693e+00 6.24170184e-01
1.50971544e+00 -2.35314041e-01 -5.43685794e-01 9.56869006e-01
1.52166748e+00 -9.96102765e-02 5.45824230e-01 2.82751024e-01
8.26692700e-01 6.63803637e-01 6.47496581e-01 2.00960800e-01
4.09656584e-01 7.74440467e-01 6.11217260e-01 -3.90751243e-01
-2.88272768e-01 -1.50179267e-01 3.22624564e-01 2.34582856e-01
2.47500315e-01 -2.55721569e-01 -7.27338791e-01 6.75664365e-01
-1.91693807e+00 -6.47817969e-01 -2.14254990e-01 1.74952376e+00
9.65470433e-01 8.78450200e-02 1.13462269e-01 -7.76523128e-02
6.07895315e-01 6.77766383e-01 -7.44761586e-01 -3.82958829e-01
1.26311071e-02 1.79328546e-01 5.77011526e-01 6.59376800e-01
-1.26013875e+00 1.10740888e+00 5.91729689e+00 9.62762713e-01
-1.09590340e+00 3.08861762e-01 7.15571225e-01 -3.07507329e-02
-3.74764115e-01 2.15412583e-02 -1.00906825e+00 6.71864986e-01
2.98608720e-01 1.99633807e-01 2.85040200e-01 9.20194983e-01
5.01340404e-02 -2.21380353e-01 -1.07861543e+00 9.06419098e-01
1.46328714e-02 -1.31120765e+00 -1.75403908e-01 -8.36875662e-02
6.06207132e-01 -2.52367859e-03 3.36185664e-01 3.60913984e-02
6.08296059e-02 -8.02512169e-01 1.04592192e+00 1.20701388e-01
8.97351980e-01 -2.63006389e-01 2.09122002e-01 2.01009586e-01
-1.33035827e+00 -4.16403599e-02 -2.23487258e-01 4.08189893e-01
1.59806177e-01 7.56276071e-01 -5.74153304e-01 2.25784868e-01
9.17858601e-01 5.88938713e-01 -6.47765338e-01 1.00887585e+00
-6.28824711e-01 8.51907730e-01 -2.63337433e-01 2.64304340e-01
2.87900329e-01 1.48283124e-01 3.74897927e-01 1.51590490e+00
-1.33381620e-01 6.78950921e-02 1.66336790e-01 1.05635512e+00
-3.32076922e-02 -9.69208255e-02 -1.97020009e-01 2.36034438e-01
3.82978350e-01 1.54224193e+00 -8.14829826e-01 -2.68438309e-01
-4.46943432e-01 1.04636014e+00 4.12774354e-01 6.22715592e-01
-1.06705904e+00 -3.41565996e-01 6.35962248e-01 2.09227264e-01
7.71758616e-01 -2.04006821e-01 -3.81647527e-01 -9.43056345e-01
3.20760012e-01 -6.38161778e-01 2.74601281e-01 -8.78094435e-01
-1.14311779e+00 3.69548619e-01 1.19855106e-01 -9.05014157e-01
2.13979065e-01 -8.40881050e-01 -7.20595419e-01 6.71605647e-01
-1.98402977e+00 -1.37020826e+00 -5.53854346e-01 6.47941351e-01
6.63761795e-01 5.13378680e-01 3.99538487e-01 2.04811186e-01
-5.97826004e-01 6.84235632e-01 -2.82000512e-01 1.48201793e-01
8.62413406e-01 -1.37214649e+00 4.59955513e-01 9.23760593e-01
1.16402179e-01 4.81317282e-01 6.47998810e-01 -4.05984908e-01
-1.29687071e+00 -1.03588295e+00 6.13034427e-01 -4.82207507e-01
5.48314095e-01 -8.47216368e-01 -1.10185611e+00 7.36113429e-01
4.13239419e-01 3.97899091e-01 2.58163571e-01 -9.99318436e-02
-6.67751253e-01 -5.41629717e-02 -9.58949566e-01 5.47356546e-01
1.23716819e+00 -4.71103787e-01 -4.05808091e-01 3.48722428e-01
9.86066878e-01 -6.52822971e-01 -3.37465972e-01 3.15747708e-01
3.78760427e-01 -9.69359994e-01 1.26200247e+00 -1.84823245e-01
3.81981164e-01 -4.13162202e-01 -7.29641169e-02 -7.21339643e-01
-4.11225557e-01 -7.20691204e-01 -2.52156138e-01 1.31591940e+00
3.25935394e-01 -4.89954650e-01 9.24538016e-01 4.87446785e-01
-1.63398951e-01 -1.04281902e+00 -6.09432280e-01 -5.19969106e-01
-1.01514205e-01 -3.35239589e-01 3.54225010e-01 6.00781679e-01
-6.77944720e-01 2.56628186e-01 -2.99225032e-01 4.87692118e-01
8.26531231e-01 4.47212130e-01 9.31558847e-01 -9.45578575e-01
-4.48718578e-01 -3.12778652e-01 -4.42335680e-02 -1.43742228e+00
1.39614627e-01 -6.48084819e-01 2.98659563e-01 -1.67226160e+00
4.07160938e-01 -4.70846295e-01 -2.85226017e-01 8.22652042e-01
-4.23014939e-01 2.07561061e-01 3.62028837e-01 2.21996307e-02
-8.18291306e-01 2.13626727e-01 1.37738955e+00 -2.72421628e-01
-8.94328281e-02 -1.98325694e-01 -7.84808218e-01 6.94622278e-01
7.12518394e-01 -5.29185951e-01 -4.60413963e-01 -7.59427786e-01
-3.49424556e-02 -3.29420745e-01 8.01775157e-01 -6.50342226e-01
2.72754848e-01 -3.25825930e-01 2.67038018e-01 -7.52244890e-01
4.10330892e-01 -7.11440027e-01 -2.54052877e-01 8.32344964e-02
-2.42430672e-01 -3.13035101e-01 3.62060189e-01 6.66830897e-01
2.35029906e-02 -2.00451091e-01 9.02721822e-01 -4.36883271e-02
-1.10993874e+00 3.71858090e-01 -1.85588524e-01 2.48045221e-01
1.13901186e+00 -4.36175913e-01 -8.14501524e-01 4.73488905e-02
-5.64495802e-01 2.68457204e-01 4.95750129e-01 2.52832323e-01
7.03893483e-01 -7.73875237e-01 -4.40881133e-01 8.79610851e-02
2.69219995e-01 3.66292626e-01 5.26302397e-01 8.25100780e-01
-3.01986277e-01 2.32205048e-01 5.14267683e-02 -8.91548514e-01
-1.41779447e+00 5.72473645e-01 2.26052091e-01 -2.56752342e-01
-8.65790665e-01 1.13286233e+00 8.98547947e-01 -1.71170428e-01
5.14198065e-01 -5.72916090e-01 1.61183596e-01 -9.61346924e-02
3.43066037e-01 5.87745458e-02 -1.54327959e-01 -2.55614281e-01
-5.61636209e-01 9.72908616e-01 -2.11892501e-01 4.16844040e-02
1.22708750e+00 -3.43428068e-02 6.70906454e-02 2.79484481e-01
1.28666067e+00 1.58224195e-01 -1.82366943e+00 -3.64207894e-01
-2.90111393e-01 -4.53098238e-01 8.79625008e-02 -8.60597730e-01
-1.23705375e+00 1.09349358e+00 4.35263425e-01 -1.33342519e-02
1.30738759e+00 3.71130228e-01 7.20171809e-01 8.54872316e-02
2.99019277e-01 -8.54456961e-01 3.63589883e-01 1.84400141e-01
8.40080023e-01 -1.29166782e+00 6.18053786e-02 -8.60381842e-01
-6.48035109e-01 7.10015178e-01 7.14738309e-01 -1.41107738e-01
5.76743841e-01 5.82110703e-01 1.15941137e-01 -2.34709755e-01
-8.05577099e-01 -3.32016259e-01 4.71168727e-01 6.98800206e-01
1.54531240e-01 -4.92376229e-03 4.95386831e-02 5.80592096e-01
3.13950539e-01 -2.22807929e-01 1.14526846e-01 9.23265398e-01
-4.47003275e-01 -1.04721272e+00 -2.36221403e-01 2.26682737e-01
-4.24127400e-01 -1.70302495e-01 -5.04759789e-01 8.71371627e-01
2.39004210e-01 7.64470577e-01 -8.15425888e-02 -5.09406589e-02
1.66551307e-01 -2.52132952e-01 5.64472198e-01 -6.71833634e-01
-7.38157034e-01 6.40191957e-02 -1.45476162e-01 -9.78035092e-01
-4.32543695e-01 -4.41602439e-01 -1.24498975e+00 -1.18942492e-01
-9.32849050e-02 -1.95626006e-01 5.74583828e-01 6.25179112e-01
4.91599977e-01 5.11576056e-01 3.13921034e-01 -1.14182734e+00
-2.12068528e-01 -5.73677897e-01 -2.55974293e-01 3.85094196e-01
6.46805763e-01 -7.14260578e-01 -4.01386529e-01 2.54908890e-01] | [9.592723846435547, 0.3347044587135315] |
44f78ff4-8f80-47cb-806e-38f1049df899 | concurrent-subsidiary-supervision-for | 2207.13247 | null | https://arxiv.org/abs/2207.13247v1 | https://arxiv.org/pdf/2207.13247v1.pdf | Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation | The prime challenge in unsupervised domain adaptation (DA) is to mitigate the domain shift between the source and target domains. Prior DA works show that pretext tasks could be used to mitigate this domain shift by learning domain invariant representations. However, in practice, we find that most existing pretext tasks are ineffective against other established techniques. Thus, we theoretically analyze how and when a subsidiary pretext task could be leveraged to assist the goal task of a given DA problem and develop objective subsidiary task suitability criteria. Based on this criteria, we devise a novel process of sticker intervention and cast sticker classification as a supervised subsidiary DA problem concurrent to the goal task unsupervised DA. Our approach not only improves goal task adaptation performance, but also facilitates privacy-oriented source-free DA i.e. without concurrent source-target access. Experiments on the standard Office-31, Office-Home, DomainNet, and VisDA benchmarks demonstrate our superiority for both single-source and multi-source source-free DA. Our approach also complements existing non-source-free works, achieving leading performance. | ['R. Venkatesh Babu', 'Varun Jampani', 'Hiran Sarkar', 'Akshay Kulkarni', 'Suvaansh Bhambri', 'Jogendra Nath Kundu'] | 2022-07-27 | null | null | null | null | ['source-free-domain-adaptation'] | ['computer-vision'] | [ 3.24955374e-01 -8.55638459e-02 -4.23125625e-01 -5.63255668e-01
-9.23533380e-01 -7.82542288e-01 6.72351301e-01 -3.80071588e-02
-4.80311096e-01 1.02846980e+00 2.62194872e-01 -2.58674145e-01
-2.35399976e-01 -5.44230163e-01 -4.65215713e-01 -4.84734505e-01
3.98760825e-01 6.80907130e-01 2.49214858e-01 -5.57646036e-01
-7.12985396e-02 2.26093158e-01 -1.11211681e+00 2.73295581e-01
1.22011960e+00 8.77910018e-01 1.61318019e-01 1.39017433e-01
-1.05968779e-02 6.74916983e-01 -7.86008716e-01 -3.05746108e-01
7.90475070e-01 -2.28298232e-01 -9.89620686e-01 1.07722804e-02
5.42752028e-01 -3.46794724e-01 -1.39463581e-02 9.25637901e-01
7.59840250e-01 3.85464013e-01 7.30992138e-01 -1.69837928e+00
-9.71562207e-01 3.36008966e-01 -3.79903495e-01 4.81492095e-02
2.25210324e-01 1.77969426e-01 9.86334801e-01 -7.16416597e-01
6.96989179e-01 8.49570632e-01 5.10172546e-01 7.10821807e-01
-1.45733476e+00 -1.06290889e+00 3.56689215e-01 -1.46589592e-01
-1.23869944e+00 -6.68555975e-01 9.38558459e-01 -5.54864228e-01
9.02081728e-01 -5.38927801e-02 -1.37420483e-02 1.59287941e+00
-1.89845785e-01 5.82922101e-01 1.23266006e+00 -5.04660606e-01
4.33146626e-01 4.69842881e-01 4.05158043e-01 3.56905848e-01
3.59984875e-01 2.96527222e-02 -6.33847773e-01 -6.29219890e-01
8.16711426e-01 -1.24850320e-02 -1.00262232e-01 -1.08359003e+00
-1.21934891e+00 8.28927338e-01 2.97672331e-01 1.46524563e-01
-4.29920554e-01 -3.22976351e-01 6.08294010e-01 7.70672321e-01
5.02826512e-01 7.79229045e-01 -7.89117157e-01 2.75402963e-02
-8.13262641e-01 4.95076299e-01 7.47185707e-01 1.46011829e+00
7.96936214e-01 -1.32824764e-01 -2.18803808e-01 9.95398343e-01
-5.52789262e-03 4.16327447e-01 7.13449597e-01 -9.31037366e-01
7.70994723e-01 5.84593534e-01 4.31001633e-01 -5.23042142e-01
-2.95418590e-01 -4.98077989e-01 -7.00525999e-01 2.97858000e-01
7.36328304e-01 -3.11440438e-01 -9.62249637e-01 1.96146178e+00
2.31733501e-01 -1.16484538e-01 2.79698282e-01 8.54454577e-01
3.87937039e-01 1.57495484e-01 3.69488358e-01 1.22509943e-02
1.29928088e+00 -1.10940444e+00 -6.66971684e-01 -5.23932457e-01
7.14571118e-01 -5.11002779e-01 1.47646022e+00 3.47837657e-01
-7.62372792e-01 -4.98086154e-01 -1.16082788e+00 -1.79071724e-01
-6.69475138e-01 -9.84602198e-02 5.63568592e-01 8.36362123e-01
-8.48901391e-01 1.98486194e-01 -4.89568502e-01 -6.38846695e-01
7.73215175e-01 3.78970742e-01 -5.18844545e-01 -8.22633207e-02
-1.27287757e+00 8.26585889e-01 3.11343312e-01 -7.70460963e-01
-8.86943519e-01 -1.10964000e+00 -6.19687617e-01 6.16560802e-02
6.02778375e-01 -9.60904539e-01 1.43288815e+00 -1.36180282e+00
-1.41457927e+00 1.02229953e+00 -8.24406594e-02 -8.26363206e-01
5.96875131e-01 -3.20843428e-01 -7.32513130e-01 -6.20336160e-02
4.11425024e-01 5.88215947e-01 1.24230766e+00 -1.18193877e+00
-8.31620932e-01 -3.50188971e-01 1.63781434e-01 4.41056550e-01
-7.54559457e-01 -1.49678856e-01 -3.07467654e-02 -7.17740476e-01
-3.84689540e-01 -7.72825837e-01 -2.28854612e-01 4.90650423e-02
-2.19851717e-01 -1.40206262e-01 8.37020874e-01 -4.78017449e-01
1.10807395e+00 -2.49696636e+00 -1.68212146e-01 3.73279184e-01
5.98906040e-01 3.03506345e-01 -1.90094993e-01 2.18897298e-01
-2.15750694e-01 -7.77882710e-02 -3.86338234e-01 -2.17751086e-01
1.78197175e-01 1.77336499e-01 -5.71915984e-01 2.34856904e-01
-3.12496666e-02 5.58292210e-01 -9.53828514e-01 -1.53139070e-01
-8.65693837e-02 3.12282648e-02 -8.22156429e-01 2.64959484e-01
-2.67471164e-01 4.91639882e-01 -5.41860163e-01 7.55379677e-01
6.65343821e-01 -3.88809651e-01 1.98048264e-01 1.87185436e-01
2.60691941e-01 5.14184833e-01 -9.83746231e-01 2.04359889e+00
-5.67779720e-01 4.38858956e-01 1.90867305e-01 -1.07572281e+00
1.12180936e+00 1.48208663e-01 6.64078653e-01 -7.06658781e-01
-2.97089845e-01 4.02267069e-01 -2.06164971e-01 7.02626631e-02
6.47042871e-01 8.07030499e-02 -2.59900600e-01 4.17159617e-01
1.89433664e-01 1.51630431e-01 -2.86708683e-01 1.49604425e-01
1.17114329e+00 1.51594028e-01 7.02445209e-01 -5.84428251e-01
4.35904801e-01 3.43802691e-01 5.60644507e-01 9.08119798e-01
-8.37776124e-01 5.91219842e-01 2.40119934e-01 -4.02108222e-01
-8.31722558e-01 -1.14457250e+00 1.37289539e-01 1.69696450e+00
2.61568874e-01 -3.69039387e-01 -6.35577798e-01 -1.38381147e+00
2.31362507e-01 7.63311982e-01 -3.45132411e-01 -3.46133143e-01
-3.81605238e-01 -4.60062534e-01 6.32345557e-01 5.34401596e-01
8.66303921e-01 -8.17469835e-01 -4.51198846e-01 3.28831971e-01
-3.70251328e-01 -9.62596655e-01 -7.25736439e-01 5.18755555e-01
-7.56217062e-01 -7.88753688e-01 -9.06623542e-01 -7.58418918e-01
5.48168540e-01 5.52545965e-01 1.21052492e+00 -4.32259798e-01
2.11463735e-01 6.05507672e-01 -8.56013671e-02 -4.72205818e-01
-2.85238475e-01 6.71555877e-01 3.15565884e-01 -7.71343559e-02
1.00226259e+00 -8.66223097e-01 -6.24269009e-01 6.24836266e-01
-7.46178508e-01 -2.99726099e-01 5.65778255e-01 9.28333044e-01
5.42108536e-01 -2.17609033e-01 1.21058202e+00 -1.26225448e+00
1.09759140e+00 -7.73302555e-01 -5.02106369e-01 2.37535626e-01
-1.28213787e+00 -2.68791411e-02 7.62189507e-01 -6.95452809e-01
-1.26868010e+00 3.45844686e-01 2.39960656e-01 -4.35782194e-01
-4.29121852e-01 2.38956258e-01 -3.96114796e-01 9.24985185e-02
1.52017438e+00 2.74917781e-01 5.48720472e-02 -5.39917290e-01
5.38959920e-01 8.89131606e-01 5.71743727e-01 -9.81007874e-01
1.06666648e+00 4.26217854e-01 -5.93231559e-01 -4.68454391e-01
-6.67636037e-01 -7.43917525e-01 -8.24239910e-01 4.32124734e-01
6.70434237e-01 -1.31911957e+00 -1.27767399e-01 1.90248013e-01
-7.98782706e-01 -6.28809154e-01 -5.10825038e-01 1.14408553e-01
-7.72619784e-01 3.12586576e-01 2.37555459e-01 -3.26501906e-01
-3.80026549e-01 -9.19008136e-01 7.14270890e-01 9.48440060e-02
-5.25157332e-01 -1.03144896e+00 -5.16837724e-02 4.78368133e-01
7.49851346e-01 -4.55081649e-02 9.10905242e-01 -1.23472190e+00
-2.44757876e-01 7.41967410e-02 -2.75457650e-01 4.14988279e-01
4.89372402e-01 -9.01795924e-01 -1.09882832e+00 -5.16576588e-01
-1.14706784e-01 -2.93503076e-01 5.39378345e-01 1.86020747e-01
9.76477027e-01 -4.14477408e-01 -2.41165876e-01 7.20637798e-01
1.19456077e+00 1.20698802e-01 4.65592712e-01 7.96012998e-01
5.00683248e-01 3.98171782e-01 9.09398437e-01 4.96603936e-01
5.20772278e-01 8.02368283e-01 4.94708158e-02 -2.59395063e-01
-2.62056947e-01 -4.07270432e-01 5.46515167e-01 8.70651975e-02
1.38221174e-01 -6.58617006e-04 -9.44178760e-01 9.57935929e-01
-1.93586850e+00 -6.64959013e-01 3.90258580e-01 2.41860437e+00
1.09595847e+00 1.33556455e-01 6.89948082e-01 -4.23940897e-01
4.89593267e-01 3.12776789e-02 -8.75243545e-01 -1.73590183e-01
2.01050062e-02 2.56543517e-01 8.06984544e-01 7.87797198e-02
-1.28497553e+00 1.07723176e+00 5.97624683e+00 7.82192230e-01
-9.93860662e-01 4.09520060e-01 3.42179298e-01 -1.19972244e-01
-4.88739014e-02 -1.17850669e-01 -9.07088816e-01 3.92132998e-01
8.68312895e-01 -6.51816547e-01 4.97760296e-01 1.60057318e+00
-2.26531684e-01 4.45316702e-01 -1.41744685e+00 1.04894555e+00
-2.42343128e-01 -1.07570159e+00 -5.82627021e-02 2.25364521e-01
7.47156620e-01 8.81213695e-02 1.97013199e-01 7.89487183e-01
7.12876439e-01 -6.71609581e-01 4.94485140e-01 -5.40304221e-02
1.08203781e+00 -5.59390187e-01 3.85931879e-01 3.17870349e-01
-9.56756473e-01 -2.32725188e-01 -3.58079433e-01 -3.05053890e-02
-3.01651001e-01 2.85802007e-01 -9.76612270e-01 6.30527198e-01
6.60015047e-01 6.65666759e-01 -4.80069757e-01 7.00304031e-01
-5.82125559e-02 5.06816447e-01 -2.20153332e-01 3.76399904e-01
1.75452843e-01 2.94447877e-02 6.43194973e-01 1.12749100e+00
1.58074483e-01 -2.94962168e-01 4.44288760e-01 6.58612311e-01
-3.61357898e-01 2.02102318e-01 -1.01246095e+00 9.54198092e-02
8.25233579e-01 7.95843482e-01 -2.81307120e-02 -3.56772453e-01
-4.76957589e-01 1.34118330e+00 3.97040665e-01 6.27041876e-01
-6.86331093e-01 -4.23561484e-01 1.30599201e+00 3.07533026e-01
2.10804850e-01 -2.35620588e-01 -5.78232586e-01 -1.33729279e+00
7.02678710e-02 -1.39447403e+00 9.03566241e-01 -3.15900356e-01
-1.73918211e+00 4.19859856e-01 1.72459632e-01 -1.53636777e+00
-2.73499340e-01 -3.04974556e-01 -3.68297368e-01 1.04390872e+00
-1.97117436e+00 -1.32125401e+00 -1.80537239e-01 1.34924972e+00
6.51929915e-01 -6.22463882e-01 1.13714838e+00 4.02698785e-01
-3.66745800e-01 1.09862518e+00 2.61146367e-01 3.16989571e-02
1.43637395e+00 -1.35142696e+00 3.01619470e-01 8.43308866e-01
-1.12942763e-01 8.25889885e-01 3.86910170e-01 -6.37170792e-01
-9.02157605e-01 -1.32614851e+00 6.88774407e-01 -8.16963613e-01
5.10111988e-01 -6.15771949e-01 -8.51550698e-01 9.23389196e-01
7.74366483e-02 6.61077425e-02 6.98278069e-01 3.67445469e-01
-8.07617307e-01 -2.88835496e-01 -1.58846366e+00 6.71693027e-01
1.36420894e+00 -6.25805259e-01 -7.06520438e-01 5.44356585e-01
8.80380929e-01 -3.97532344e-01 -8.78738999e-01 -1.73967499e-02
3.61376286e-01 -5.30046642e-01 1.39235961e+00 -8.84492993e-01
2.93409437e-01 -1.06446654e-01 -2.00983822e-01 -1.43504953e+00
-4.75703269e-01 -1.03196597e+00 -2.10736051e-01 1.32968354e+00
3.75416815e-01 -1.03003323e+00 6.97354436e-01 1.13425136e+00
-8.92134681e-02 9.75334793e-02 -9.39912379e-01 -1.39853764e+00
4.76952553e-01 -1.19032629e-01 8.78493369e-01 1.51763427e+00
-1.45045400e-01 3.62463236e-01 -5.72010756e-01 2.82029212e-01
6.60178781e-01 -1.20074369e-01 1.16560030e+00 -1.40762544e+00
-1.61362916e-01 -2.77509838e-01 -3.51875909e-02 -1.26149821e+00
9.93260220e-02 -1.05325055e+00 -2.11489663e-01 -1.04593778e+00
-2.84106344e-01 -8.26484084e-01 -7.79235184e-01 9.03831780e-01
-9.98565461e-03 -3.03498477e-01 1.01266190e-01 5.33918619e-01
-5.01765549e-01 2.74162114e-01 8.95931661e-01 -1.41843736e-01
-7.03129768e-01 -9.05157067e-03 -1.35713089e+00 4.55774814e-01
1.04683995e+00 -6.69654250e-01 -8.57058227e-01 -3.84274155e-01
-2.29161307e-01 -5.08837879e-01 2.52936393e-01 -9.55153346e-01
1.87254399e-01 -4.11534518e-01 9.43500623e-02 -5.08567169e-02
9.81320888e-02 -1.19333172e+00 -3.34296107e-01 4.69336435e-02
-5.16646266e-01 -3.85664076e-01 1.38748586e-01 6.83661342e-01
-6.11797981e-02 1.12655878e-01 8.16488743e-01 -1.58547498e-02
-1.01605558e+00 2.67665952e-01 -1.29527003e-01 2.54027724e-01
1.02945018e+00 -1.81731239e-01 -6.02018118e-01 -3.96117508e-01
-6.06006801e-01 2.79293925e-01 4.43359971e-01 4.86354440e-01
2.69802779e-01 -1.32374787e+00 -5.73393703e-01 3.46962899e-01
5.35721183e-01 -4.85015325e-02 -1.98463053e-02 5.97594440e-01
5.20738475e-02 2.56839663e-01 -5.58156371e-01 -3.64727229e-01
-1.04576659e+00 6.33316398e-01 1.56329647e-01 -4.95181888e-01
-6.96365178e-01 7.26640582e-01 5.19684315e-01 -7.07871556e-01
4.07715857e-01 -1.74027234e-01 2.03873869e-02 -1.59185439e-01
3.80414218e-01 2.55189776e-01 1.40614808e-01 -1.14962295e-01
-4.70693916e-01 -9.66417938e-02 -5.33504069e-01 -6.29074574e-02
1.24922955e+00 -3.60397935e-01 5.11838078e-01 -2.45689638e-02
9.13556576e-01 4.53610606e-02 -1.36868656e+00 -8.46217453e-01
1.52683139e-01 -6.43072486e-01 -1.52990818e-01 -1.25822723e+00
-6.09430254e-01 6.30962908e-01 8.59082043e-01 9.54092890e-02
1.48028779e+00 -2.47568861e-01 9.16531086e-01 7.74769008e-01
4.51694012e-01 -1.41551864e+00 2.50003263e-02 4.01419342e-01
8.87381315e-01 -1.45430505e+00 -5.03234453e-02 -3.15670222e-01
-1.09110808e+00 8.01803589e-01 8.99384439e-01 -6.17884994e-02
5.58153808e-01 -1.36711404e-01 1.40943676e-01 -5.57779670e-02
-5.00455618e-01 -2.45046094e-01 1.79742604e-01 1.38338280e+00
1.27758682e-01 1.86294802e-02 4.16421471e-03 1.12268925e+00
-6.46616295e-02 2.32470334e-01 2.55054027e-01 1.08925414e+00
-1.38672441e-01 -1.39467561e+00 -2.79018492e-01 3.41730922e-01
-3.13338548e-01 -1.93712190e-01 -6.92227185e-01 9.10231471e-01
-2.90897619e-02 7.93566346e-01 -2.95085818e-01 -2.94210792e-01
5.06253362e-01 5.14929175e-01 -3.08626983e-02 -7.17288971e-01
-8.23024929e-01 -2.00333416e-01 2.42608324e-01 -5.72597802e-01
-1.22381352e-01 -4.62624639e-01 -9.22462225e-01 -1.92289039e-01
4.38056746e-03 -2.46282399e-01 4.26808476e-01 7.07014561e-01
9.76571321e-01 1.84254348e-01 5.74885786e-01 -1.24633893e-01
-9.53294516e-01 -6.87910438e-01 -3.95705938e-01 7.40118206e-01
3.93700778e-01 -8.81220639e-01 -1.15900151e-01 3.24601769e-01] | [10.3314790725708, 3.1171531677246094] |
55bbf5be-61e3-45fd-a9fb-bc7be628c385 | pulmonary-arteryvein-classification-in-ct | null | null | https://doi.org/10.1109/TMI.2018.2833385 | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6214740/pdf/nihms982442.pdf | Pulmonary Artery–Vein Classification in CT Images Using Deep Learning | Recent studies show that pulmonary vascular diseases may specifically affect arteries or veins through different physiologic mechanisms. To detect changes in the two vascular trees, physicians manually analyze the chest computed tomography (CT) image of the patients in search of abnormalities. This process is time consuming, difficult to standardize, and thus not feasible for large clinical studies or useful in real-world clinical decision making. Therefore, automatic separation of arteries and veins in CT images is becoming of great interest, as it may help physicians to accurately diagnose pathological conditions. In this paper, we present a novel, fully automatic approach to classify vessels from chest CT images into arteries and veins. The algorithm follows three main steps: first, a scale-space particles segmentation to isolate vessels; then a 3-D convolutional neural network (CNN) to obtain a first classification of vessels; finally, graph-cuts' optimization to refine the results. To justify the usage of the proposed CNN architecture, we compared different 2-D and 3-D CNNs that may use local information from bronchus- and vessel-enhanced images provided to the network with different strategies. We also compared the proposed CNN approach with a random forests (RFs) classifier. The methodology was trained and evaluated on the superior and inferior lobes of the right lung of 18 clinical cases with noncontrast chest CT scans, in comparison with manual classification. The proposed algorithm achieves an overall accuracy of 94%, which is higher than the accuracy obtained using other CNN architectures and RF. Our method was also validated with contrast-enhanced CT scans of patients with chronic thromboembolic pulmonary hypertension to demonstrate that our model generalizes well to contrast-enhanced modalities. The proposed method outperforms state-of-the-art methods, paving the way for future use of 3-D CNN for artery/vein classification in CT images. | ['Raúl San José Estépar', 'Maria J. Ledesma-Carbayo', 'David Bermejo-Pelaez', 'Daniel Jimenez-Carretero', 'Pietro Nardelli', 'Farbod N. Rahaghi', 'George R. Washko'] | 2018-05-04 | null | null | null | ieee-transactions-on-medical-imaging-volume | ['pulmonary-arteryvein-classification', 'pulmorary-vessel-segmentation', '3d-medical-imaging-segmentation'] | ['computer-vision', 'computer-vision', 'medical'] | [ 1.53992236e-01 -1.86338052e-02 -8.43564942e-02 -1.43661290e-01
-2.76684612e-01 -4.47016120e-01 2.63054013e-01 2.29388759e-01
-5.87446332e-01 7.20523119e-01 -1.12709492e-01 -9.37496483e-01
-1.96062148e-01 -1.13998151e+00 -5.37844449e-02 -7.08502948e-01
-3.08755010e-01 1.06060779e+00 5.75945020e-01 1.77638978e-01
-6.15805760e-02 1.36061192e+00 -1.03493273e+00 2.81581104e-01
5.31818867e-01 1.11772227e+00 -2.60149445e-02 1.10995376e+00
-4.47042942e-01 7.27728188e-01 -3.42848152e-01 -7.68441036e-02
3.65738958e-01 -5.98833203e-01 -9.50179756e-01 1.91869617e-01
3.93571079e-01 -2.72390872e-01 -4.78819758e-03 6.09601140e-01
6.33676648e-01 -1.59694180e-01 8.16001773e-01 -5.55731714e-01
-2.19857935e-02 1.64640650e-01 -4.16842997e-01 7.31418550e-01
-3.49298626e-01 1.05170161e-01 7.45067179e-01 -5.85985065e-01
5.25932610e-01 7.15828478e-01 6.90334141e-01 4.24153626e-01
-1.08634818e+00 -5.09070992e-01 -2.89976031e-01 1.41449824e-01
-1.04310668e+00 1.84345111e-01 4.54488337e-01 -8.09852421e-01
7.61697710e-01 3.54034603e-01 1.09462440e+00 5.08771122e-01
3.86521935e-01 1.51642621e-01 1.39183855e+00 -3.65680546e-01
5.74096777e-02 1.37558579e-01 -3.02563310e-02 1.08447301e+00
4.13172424e-01 3.20828825e-01 2.85007060e-01 -2.26223961e-01
1.12010372e+00 1.11511484e-01 -3.48725349e-01 -5.24626255e-01
-1.01595747e+00 8.73536646e-01 7.93513894e-01 8.53367567e-01
-6.78786874e-01 1.04949707e-02 2.62388378e-01 -1.03207551e-01
2.80160278e-01 3.17328602e-01 -2.75168419e-01 1.64954692e-01
-1.07610011e+00 -6.31311387e-02 7.91663945e-01 3.10281605e-01
2.17939034e-01 -3.54387239e-02 -1.10722519e-01 7.08020687e-01
2.62437284e-01 7.19372779e-02 6.51810884e-01 -5.45247793e-01
2.98487663e-01 5.77776611e-01 -2.72518516e-01 -6.93076134e-01
-7.59715021e-01 -9.15172815e-01 -1.26907051e+00 5.41855633e-01
9.10088956e-01 -3.75228934e-02 -1.15848887e+00 8.23920786e-01
4.49148804e-01 -4.95951734e-02 -2.81163394e-01 1.07679689e+00
8.75124753e-01 5.97506054e-02 2.07979843e-01 -1.21467613e-01
1.54822040e+00 -1.01419473e+00 -3.19205821e-01 2.38598868e-01
5.75973988e-01 -7.50311553e-01 7.67146170e-01 3.77634615e-01
-9.34033394e-01 -5.52161574e-01 -8.72509420e-01 3.28294784e-01
-1.96376368e-01 3.01095694e-01 3.35688740e-01 9.05734539e-01
-8.09884608e-01 9.00849640e-01 -1.04498327e+00 -4.06499296e-01
8.62325907e-01 3.84362251e-01 -3.10007811e-01 2.76894838e-01
-8.07935059e-01 9.82836604e-01 -1.68023836e-02 1.22957148e-01
-6.50523245e-01 -5.34020364e-01 -2.91871965e-01 2.15847075e-01
3.06412965e-01 -1.08931303e+00 1.18806148e+00 -6.49446905e-01
-1.32830095e+00 1.02854645e+00 -5.86731732e-02 -6.09245598e-01
7.65287638e-01 1.97535262e-01 -1.27277642e-01 6.22615933e-01
-1.15561202e-01 1.57455012e-01 6.82401061e-01 -9.10994709e-01
-8.25572073e-01 -4.65804011e-01 -3.14423233e-01 -1.54418483e-01
1.93631381e-01 -2.15088099e-01 -1.18226133e-01 -5.55095494e-01
4.03335273e-01 -8.57041180e-01 -6.16187751e-01 3.73955846e-01
-4.62945342e-01 4.82195616e-02 5.36922812e-01 -8.02098513e-01
1.04676449e+00 -1.65544152e+00 -1.23351216e-01 6.70598924e-01
8.09279025e-01 3.97351354e-01 4.14750278e-01 -1.49154976e-01
-2.82325506e-01 4.32226062e-01 -4.23921257e-01 9.79848355e-02
-6.36903286e-01 2.09207863e-01 3.49192947e-01 4.73611087e-01
3.67790312e-02 7.28654504e-01 -3.76408398e-01 -9.34168637e-01
4.39260751e-01 3.83888394e-01 -1.90315977e-01 3.08873564e-01
1.65324867e-01 8.50614190e-01 -5.48350632e-01 5.77872157e-01
5.83319426e-01 -5.05551100e-01 2.96868593e-01 -5.74355051e-02
-1.01417184e-01 1.93130612e-01 -9.22568798e-01 9.76927519e-01
-7.74530113e-01 4.57398534e-01 1.37105808e-01 -1.22125125e+00
8.53567183e-01 6.01770997e-01 7.05859900e-01 -4.93379265e-01
3.86799335e-01 4.76865709e-01 5.18205881e-01 -6.91390336e-01
-3.60056162e-01 -6.04455948e-01 7.30924428e-01 3.75388443e-01
-1.00461863e-01 -2.82902807e-01 1.97436392e-01 -2.62019128e-01
9.67042625e-01 -2.50759274e-01 6.09863937e-01 -2.09824324e-01
9.86387968e-01 2.36980408e-01 1.47257552e-01 6.33746982e-01
-3.49991083e-01 6.65873766e-01 5.69060624e-01 -8.74962986e-01
-9.61280704e-01 -1.12553430e+00 -4.35798198e-01 2.07733661e-01
-3.07785988e-01 2.35622749e-01 -5.73168755e-01 -1.07049799e+00
-6.63337260e-02 2.71244675e-01 -5.37676275e-01 5.75199604e-01
-9.40069139e-01 -7.92249203e-01 4.16353673e-01 5.04257262e-01
6.73067689e-01 -9.80182469e-01 -9.67915893e-01 4.67762321e-01
-7.19030723e-02 -9.29111600e-01 7.51465708e-02 4.04138774e-01
-1.51316619e+00 -1.57765341e+00 -9.55787659e-01 -7.48761296e-01
6.07459903e-01 6.93127587e-02 1.18580186e+00 4.76002067e-01
-7.19758809e-01 -3.39663774e-03 -1.96899056e-01 -1.58981308e-01
-6.12724245e-01 3.24077606e-01 -6.38494611e-01 -1.93875283e-01
-1.08006813e-01 -7.46130288e-01 -8.62128496e-01 3.89175951e-01
-5.59942245e-01 -1.87838748e-01 9.05584812e-01 8.48657966e-01
7.73578942e-01 3.03036511e-01 2.21143603e-01 -1.31333315e+00
4.79359508e-01 -3.49528909e-01 -5.56794107e-01 -1.33397086e-02
-8.17664921e-01 -9.73362550e-02 1.01868415e+00 -6.82387650e-02
-9.68356252e-01 1.82123765e-01 -5.28450847e-01 -3.23678464e-01
-6.23236120e-01 2.69860536e-01 5.13158500e-01 -2.29476839e-01
8.72684836e-01 5.12691028e-02 2.39160195e-01 -4.66929644e-01
1.55478969e-01 6.22060597e-01 3.53460014e-01 -2.08118305e-01
8.31392944e-01 7.40348399e-01 7.05105960e-01 -8.26868236e-01
-4.81314033e-01 -7.10137188e-01 -1.18957365e+00 -2.96966940e-01
1.20884454e+00 -2.65691012e-01 -2.95075953e-01 -4.26972099e-02
-9.98963714e-01 -1.28954038e-01 -5.55903792e-01 7.48763561e-01
-4.41239446e-01 4.51689512e-01 -6.31998599e-01 -3.95018041e-01
-5.26000202e-01 -1.25483108e+00 4.62555170e-01 1.39722720e-01
-1.73001766e-01 -1.29263079e+00 1.45476624e-01 4.98381823e-01
7.39501595e-01 3.51393402e-01 1.39135003e+00 -8.34596395e-01
-6.01920545e-01 -2.97861516e-01 -3.25497299e-01 5.94026506e-01
6.76999837e-02 1.20526329e-01 -7.48539507e-01 1.26048014e-01
5.59857823e-02 2.00826317e-01 7.99305856e-01 7.52146244e-01
1.37320590e+00 1.00500444e-02 -4.23623502e-01 6.84098899e-01
1.44406056e+00 5.23038745e-01 4.29570079e-01 3.97535503e-01
4.69823211e-01 6.32306457e-01 2.16204002e-01 2.42554903e-01
-2.57126510e-01 3.58132988e-01 5.97405255e-01 -7.17401564e-01
-5.46007454e-01 1.83088645e-01 -5.47849894e-01 5.72980344e-01
-6.93717539e-01 -2.47937869e-02 -9.44293976e-01 4.74824667e-01
-1.20660019e+00 -7.28228927e-01 -7.25583613e-01 2.06336212e+00
3.52868646e-01 2.58857608e-01 3.37995082e-01 1.12226196e-01
6.68559730e-01 -9.35993120e-02 -1.78716138e-01 -5.64642549e-01
4.12875712e-01 1.19373071e+00 5.56999624e-01 3.29376906e-01
-1.13378215e+00 3.27272862e-01 5.80118942e+00 4.83091176e-01
-1.58870196e+00 1.79848358e-01 7.23525107e-01 3.68237227e-01
9.74833369e-02 -1.07411399e-01 -3.09031636e-01 1.96599755e-02
6.14131451e-01 2.14699462e-01 -3.34099829e-02 8.17883492e-01
3.73754203e-01 -1.75958186e-01 -6.61043644e-01 5.10933340e-01
-4.90888864e-01 -1.42639458e+00 -2.80066431e-01 2.03166679e-01
2.63737500e-01 4.56180722e-02 -2.66153783e-01 -1.11052968e-01
-4.60921265e-02 -1.12641335e+00 8.34207907e-02 3.62367988e-01
7.45615184e-01 -3.86888355e-01 1.07799971e+00 3.15490335e-01
-1.23852801e+00 1.60885647e-01 -1.03167340e-01 2.25712106e-01
9.67327580e-02 5.79225242e-01 -1.69766247e+00 4.91394550e-01
7.08235979e-01 2.97058851e-01 -5.95348060e-01 1.29146159e+00
-2.98623770e-01 8.88670623e-01 -2.51383036e-01 -2.29429275e-01
2.72328675e-01 -2.41531521e-01 4.93362725e-01 1.23492646e+00
4.03248399e-01 3.68809439e-02 -1.85722187e-01 8.18229795e-01
1.87047750e-01 6.22802079e-01 -4.75968122e-01 2.75805295e-01
-6.00835085e-02 1.54295659e+00 -1.36385298e+00 -5.72886825e-01
-5.33883989e-01 5.07085443e-01 -1.20968819e-02 9.55350474e-02
-7.04894602e-01 -1.90828666e-01 -2.30340939e-02 7.99940467e-01
3.71142745e-01 -3.92450877e-02 -4.67335373e-01 -8.38601649e-01
-3.14344227e-01 -4.65192854e-01 5.71959019e-01 -5.05211055e-01
-1.20704865e+00 1.07613111e+00 -9.20264497e-02 -1.37354004e+00
-1.42042011e-01 -8.14808190e-01 -7.37756491e-01 1.11987484e+00
-1.64744389e+00 -8.03489208e-01 -7.29937017e-01 4.13010031e-01
4.10213023e-01 -1.30450964e-01 7.81591654e-01 2.46167406e-01
-2.62789130e-01 -5.31252250e-02 -1.28093451e-01 1.83152333e-01
4.73212540e-01 -1.58181369e+00 4.54226919e-02 6.56664550e-01
-1.00758322e-01 3.68860692e-01 1.85222030e-01 -5.19045889e-01
-3.36077392e-01 -1.18165350e+00 8.62387955e-01 9.53082964e-02
3.91676217e-01 3.63409877e-01 -7.72497118e-01 4.13191408e-01
1.48263931e-01 4.47931409e-01 8.57572138e-01 -2.68504828e-01
6.03525229e-02 -2.40742043e-02 -1.25944090e+00 2.31558815e-01
6.38673723e-01 -1.19440653e-03 -5.37430584e-01 4.56865996e-01
-5.15348986e-02 -3.97639394e-01 -1.16864979e+00 4.52171057e-01
6.21006370e-01 -1.30063951e+00 1.04972482e+00 -6.31873727e-01
5.24740279e-01 -1.94646865e-01 3.12898487e-01 -1.13969111e+00
-4.33290660e-01 9.35464799e-02 3.36769879e-01 4.04028952e-01
5.20598054e-01 -8.38826537e-01 1.15929770e+00 7.88019523e-02
-1.72167778e-01 -1.16558433e+00 -9.30540085e-01 -4.12578523e-01
3.59878331e-01 -3.28672767e-01 2.65882045e-01 6.63016558e-01
-6.89886928e-01 2.24565834e-01 2.19838813e-01 -5.71284033e-02
4.79240805e-01 3.79278809e-01 6.99897230e-01 -1.42678964e+00
-4.54817981e-01 -7.78683186e-01 -3.72883469e-01 -7.41906226e-01
-3.03751767e-01 -1.03652239e+00 -3.82725120e-01 -1.84851956e+00
1.24964779e-02 -7.62380123e-01 -8.18966478e-02 1.53795987e-01
1.14892513e-01 2.69457102e-01 1.78856030e-02 4.75274086e-01
2.72421420e-01 -1.22246772e-01 1.97412407e+00 8.06182548e-02
-9.93011072e-02 8.73901129e-01 -3.06186557e-01 8.27142894e-01
1.03980207e+00 -5.91883600e-01 -1.47609130e-01 3.27376992e-01
-3.66496623e-01 5.18176675e-01 4.67750192e-01 -1.05586970e+00
-9.58940480e-03 5.35934977e-02 7.41618395e-01 -8.17263186e-01
-2.74196994e-02 -1.19577122e+00 7.39465356e-02 1.16006649e+00
-1.93567857e-01 -1.49696751e-03 -9.24636871e-02 2.65941203e-01
-3.76818359e-01 -4.80356216e-01 1.24300718e+00 -7.84323812e-01
-8.19751769e-02 3.71683210e-01 -9.04536664e-01 -2.23932907e-01
1.05829680e+00 -4.05348808e-01 -4.64833342e-02 -2.70366400e-01
-1.37152636e+00 -2.88581610e-01 -5.85137047e-02 -4.07926977e-01
6.00309968e-01 -7.66118884e-01 -6.66472912e-01 2.89632201e-01
-2.10934609e-01 3.53841752e-01 2.42822453e-01 1.43552709e+00
-1.46961665e+00 6.10161543e-01 -3.47137779e-01 -8.85561585e-01
-1.57016265e+00 3.52178216e-01 1.00929821e+00 -8.34874988e-01
-6.30367041e-01 5.88916659e-01 1.33307993e-01 -2.93248385e-01
-4.80341651e-02 -7.82719195e-01 -5.27730107e-01 -1.42844722e-01
-1.77109390e-01 4.85438019e-01 5.15696824e-01 -5.57389081e-01
-2.61083692e-01 7.84150422e-01 1.72990456e-01 8.17156434e-02
1.00668252e+00 1.55161649e-01 -1.59665018e-01 -6.83603808e-02
1.16410482e+00 1.16846621e-01 -5.00679255e-01 -1.57109320e-01
-1.99121892e-01 -5.28522670e-01 1.83905140e-01 -8.22729826e-01
-1.46435201e+00 1.37878633e+00 8.89717996e-01 4.92504478e-01
1.25334156e+00 -3.95994335e-02 7.22761452e-01 1.62714608e-02
-5.05852997e-02 -5.82116425e-01 2.81629954e-02 -4.20124978e-02
6.72974646e-01 -1.05660045e+00 2.04061136e-01 -8.70587587e-01
-4.36006606e-01 1.80322886e+00 4.99661386e-01 -9.45121273e-02
1.03562868e+00 1.30064577e-01 3.65285784e-01 -3.44575047e-01
-3.74443233e-01 -4.99855518e-01 4.14099693e-01 5.59023559e-01
7.64755607e-01 1.93321645e-01 -5.16850293e-01 1.97648600e-01
-1.22303106e-01 2.82228906e-02 4.56955492e-01 8.86374950e-01
-5.40464640e-01 -1.12693477e+00 -4.24631417e-01 8.24549437e-01
-8.19412708e-01 1.24642968e-01 -3.45142573e-01 1.41583097e+00
4.25699323e-01 5.84730268e-01 -6.68156566e-03 2.23589200e-03
5.47887444e-01 9.53382552e-02 4.58029717e-01 -6.30228937e-01
-9.62739646e-01 4.45513964e-01 1.84518307e-01 -3.06074947e-01
-4.77304965e-01 -5.82813442e-01 -1.18185198e+00 -2.51154024e-02
-3.71712118e-01 1.00646764e-01 6.35819852e-01 7.57748961e-01
-1.32424712e-01 9.64969277e-01 6.92515612e-01 -3.56311619e-01
-3.68756473e-01 -9.22793388e-01 -6.86433196e-01 2.89635360e-01
2.71832705e-01 -6.44984961e-01 -5.71487129e-01 3.86529043e-02] | [15.150286674499512, -2.1813182830810547] |
3f13ddca-0d77-4d92-9d90-326480464c98 | efficient-federated-learning-with-spike | 2205.14315 | null | https://arxiv.org/abs/2205.14315v1 | https://arxiv.org/pdf/2205.14315v1.pdf | Efficient Federated Learning with Spike Neural Networks for Traffic Sign Recognition | With the gradual popularization of self-driving, it is becoming increasingly important for vehicles to smartly make the right driving decisions and autonomously obey traffic rules by correctly recognizing traffic signs. However, for machine learning-based traffic sign recognition on the Internet of Vehicles (IoV), a large amount of traffic sign data from distributed vehicles is needed to be gathered in a centralized server for model training, which brings serious privacy leakage risk because of traffic sign data containing lots of location privacy information. To address this issue, we first exploit privacy-preserving federated learning to perform collaborative training for accurate recognition models without sharing raw traffic sign data. Nevertheless, due to the limited computing and energy resources of most devices, it is hard for vehicles to continuously undertake complex artificial intelligence tasks. Therefore, we introduce powerful Spike Neural Networks (SNNs) into traffic sign recognition for energy-efficient and fast model training, which is the next generation of neural networks and is practical and well-fitted to IoV scenarios. Furthermore, we design a novel encoding scheme for SNNs based on neuron receptive fields to extract information from the pixel and spatial dimensions of traffic signs to achieve high-accuracy training. Numerical results indicate that the proposed federated SNN outperforms traditional federated convolutional neural networks in terms of accuracy, noise immunity, and energy efficiency as well. | ['Yi Wu', 'Shengli Xie', 'Dusit Niyato', 'Jiawen Kang', 'Bo Li', 'Zhe Zhang', 'Kan Xie'] | 2022-05-28 | null | null | null | null | ['traffic-sign-recognition'] | ['computer-vision'] | [ 1.60693944e-01 -4.11511302e-01 -4.58138824e-01 -6.77842259e-01
-1.81875572e-01 -4.71366346e-01 3.07481587e-01 -4.36940730e-01
-5.62805116e-01 6.79247677e-01 -4.43914443e-01 -6.87497735e-01
-1.64461672e-01 -9.23630774e-01 -7.05873549e-01 -9.62418020e-01
2.98627079e-01 1.23051591e-01 3.52857083e-01 1.88017651e-01
1.69418857e-01 5.97277343e-01 -1.67908072e+00 -8.46663192e-02
1.09705925e+00 1.61139786e+00 -6.96724094e-03 1.41194612e-02
-3.97284746e-01 5.70911050e-01 -5.31506725e-02 -6.81514204e-01
3.91453058e-01 -2.74402291e-01 5.43748843e-04 -4.81948674e-01
3.45097393e-01 -3.97639781e-01 -9.00206447e-01 1.36770880e+00
3.28915060e-01 -1.05856797e-02 2.10643098e-01 -1.85834885e+00
-6.16970122e-01 -5.55299446e-02 -2.97837844e-03 -2.16479734e-01
-6.24497294e-01 5.39689898e-01 3.36972773e-01 -3.69528711e-01
4.90816027e-01 4.60845768e-01 4.56211686e-01 9.89159524e-01
-6.11409307e-01 -1.29189777e+00 -7.95654207e-02 7.89218485e-01
-1.16582370e+00 -8.24455678e-01 8.26857388e-01 -1.68921258e-02
4.86790448e-01 5.46056986e-01 6.46157742e-01 8.21087480e-01
1.08559676e-01 9.00449276e-01 9.82236803e-01 2.44011641e-01
6.45805418e-01 1.14890508e-01 2.02195749e-01 6.59177601e-01
9.06808496e-01 2.14660227e-01 -6.05502427e-01 -3.50638032e-02
3.71479064e-01 4.91493642e-01 -5.94259277e-02 -5.83859682e-01
-9.77254689e-01 4.03252661e-01 5.61211526e-01 3.60245444e-02
-4.40951556e-01 6.76536679e-01 6.29921556e-01 1.51081383e-01
-4.00448777e-02 -3.45197260e-01 -4.26246613e-01 -3.08358520e-01
-7.93354154e-01 -2.58265231e-02 5.46745420e-01 8.51546943e-01
8.03281069e-01 2.84392238e-01 -1.19732276e-01 3.33534092e-01
2.76396334e-01 1.25084233e+00 3.64260048e-01 -1.01000881e+00
4.95998085e-01 7.44894624e-01 -2.53179502e-02 -1.09852731e+00
1.27829671e-01 -1.56304240e-01 -1.23717654e+00 1.60796776e-01
3.35852265e-01 -1.13118276e-01 -9.87917781e-01 1.59938693e+00
2.85253108e-01 4.73590463e-01 1.67044476e-01 9.85209048e-01
7.20876753e-01 3.89866680e-01 5.71675748e-02 1.41529283e-02
1.27606320e+00 -5.76613724e-01 -8.75253081e-01 -3.00995827e-01
6.01271152e-01 8.41464326e-02 3.40538234e-01 -2.35156007e-02
-6.71008050e-01 -1.58751130e-01 -1.08078170e+00 3.18752937e-02
-6.53884232e-01 1.75247014e-01 9.61899459e-01 9.55824614e-01
-7.74011493e-01 1.04222275e-01 -8.99923623e-01 -2.32556555e-02
1.31088996e+00 7.34879732e-01 -4.10130680e-01 -5.37647545e-01
-1.08328533e+00 5.01103282e-01 5.31112887e-02 3.86241853e-01
-4.36789572e-01 -3.66719693e-01 -6.20100737e-01 4.21230821e-03
1.23862207e-01 -4.99337763e-01 9.33236659e-01 -6.64066732e-01
-1.26374865e+00 4.97599870e-01 -4.51059908e-01 -7.04910576e-01
4.40211296e-01 6.17392004e-01 -6.43839955e-01 -1.34697840e-01
-2.10818395e-01 4.33614850e-01 7.10532784e-01 -9.28408444e-01
-6.25313520e-01 -6.85136497e-01 -4.67243224e-01 -3.82992655e-01
-6.40201986e-01 -4.88961376e-02 -4.09516335e-01 -6.07479028e-02
1.96878493e-01 -8.02896678e-01 -1.19255818e-01 6.00360632e-01
-9.51734092e-03 -2.07488164e-01 1.69988978e+00 -5.55640042e-01
8.85682166e-01 -2.32866120e+00 -6.80804431e-01 4.98535156e-01
4.38725263e-01 7.94931889e-01 -1.67016879e-01 -2.88572252e-01
5.49109042e-01 -9.79245529e-02 -1.67564824e-01 -1.46831065e-01
2.41543457e-01 6.33656144e-01 -2.93433279e-01 4.77585703e-01
-1.12732023e-01 1.44863689e+00 -6.54546142e-01 -4.28375363e-01
2.69059569e-01 4.01462406e-01 -2.82393306e-01 -2.06916690e-01
1.16973659e-02 2.91250587e-01 -9.40974474e-01 8.23814809e-01
1.10838521e+00 -1.25634536e-01 -1.03022888e-01 -1.49861291e-01
-7.74816573e-02 4.91103530e-03 -7.65597165e-01 1.15203536e+00
-3.31378847e-01 7.46064603e-01 4.65031028e-01 -1.09484446e+00
1.13314712e+00 2.26969481e-01 5.58937073e-01 -1.34110367e+00
4.46404517e-01 6.21455014e-01 -2.27354765e-01 -5.25223434e-01
7.03598037e-02 3.21013778e-01 -1.40506357e-01 4.43364233e-01
-3.42723548e-01 4.50143188e-01 -1.58244267e-01 -6.06851690e-02
1.28831112e+00 -4.40332234e-01 -4.59031343e-01 2.35843420e-01
5.43614745e-01 -5.41307516e-02 1.07298553e+00 2.72095859e-01
-7.48685598e-01 -2.60021799e-04 -4.94710691e-02 -6.57661259e-01
-7.93327808e-01 -7.20133901e-01 -3.53111140e-02 3.60512197e-01
4.50999737e-01 1.01551585e-01 -5.76754332e-01 -6.85296357e-01
3.09985220e-01 6.36329353e-01 -1.96384326e-01 -5.86361408e-01
-6.71233416e-01 -2.42924839e-01 8.12205195e-01 5.22033215e-01
1.35254073e+00 -9.22079504e-01 -7.02669561e-01 -6.32467121e-02
-1.17240034e-01 -1.18125379e+00 -3.70723099e-01 8.71725082e-02
-6.63677752e-01 -1.00833714e+00 -5.29733479e-01 -8.08172226e-01
8.05440307e-01 5.81929266e-01 1.61780998e-01 1.39742494e-01
-9.50699151e-02 6.61329553e-03 -3.03882249e-02 -5.54791510e-01
-8.68989974e-02 -2.03872159e-01 1.87148511e-01 6.28451705e-01
9.15644825e-01 -4.62949246e-01 -8.58414829e-01 4.54299569e-01
-8.16681623e-01 9.00780335e-02 5.44627309e-01 6.16349339e-01
5.59371650e-01 7.33333156e-02 5.82101285e-01 -2.63934106e-01
2.04238117e-01 -3.87919694e-01 -1.01523411e+00 4.02022302e-01
-5.54899871e-01 -1.25816837e-03 8.22867513e-01 -1.91285416e-01
-8.70404124e-01 3.56684089e-01 1.26846656e-01 -6.04696751e-01
-8.26393962e-02 -1.26299858e-01 -5.46213806e-01 -7.55602300e-01
6.75939247e-02 6.73870444e-01 3.77806365e-01 -1.58503801e-01
1.36984468e-01 1.15221393e+00 6.68968499e-01 7.52272606e-02
8.25056851e-01 5.70629179e-01 3.80063802e-01 -4.69033569e-01
2.22364366e-01 -1.46889344e-01 7.78030381e-02 -3.52794886e-01
7.02324927e-01 -7.29672730e-01 -1.40227222e+00 7.94983268e-01
-1.19568491e+00 4.34372649e-02 -1.61714092e-01 5.92702091e-01
-3.02176207e-01 2.47989550e-01 -9.70418155e-02 -8.72161448e-01
-5.23245633e-01 -1.01813984e+00 5.98718882e-01 4.83947635e-01
5.06376922e-01 -4.78457570e-01 -3.57619137e-01 6.21107221e-01
1.04120517e+00 -4.94881757e-02 7.59513259e-01 -5.85102916e-01
-1.39906895e+00 -7.44964957e-01 -5.95562518e-01 3.19434792e-01
1.34128317e-01 -3.98250282e-01 -1.00962210e+00 -8.95572305e-02
-2.45228149e-02 -2.26245061e-01 1.00040805e+00 2.57128358e-01
1.41592824e+00 -5.54908633e-01 -6.46228671e-01 9.76451159e-01
1.18923783e+00 4.54991430e-01 7.21709311e-01 8.25627819e-02
6.38490498e-01 3.67653549e-01 2.96558738e-01 1.49130031e-01
5.08598864e-01 3.03809971e-01 5.97233832e-01 1.96128994e-01
-2.93443464e-02 -3.87655139e-01 9.93852541e-02 7.70193815e-01
2.30139136e-01 -2.19511509e-01 -6.22192919e-01 4.98800159e-01
-2.00317049e+00 -1.07119036e+00 -6.98665231e-02 2.34368849e+00
1.61819130e-01 -3.27921450e-01 -3.89758945e-01 6.53378619e-03
7.14956224e-01 2.48006321e-02 -1.23051190e+00 -2.44146347e-01
-2.15334803e-01 -3.59228998e-02 1.17050827e+00 -2.94248939e-01
-7.76067138e-01 6.41334951e-01 5.12718201e+00 1.07633781e+00
-1.48068869e+00 2.62931168e-01 7.14239657e-01 -4.58711805e-03
-5.69897413e-01 1.02574192e-02 -6.43724740e-01 9.50896323e-01
9.37346697e-01 -1.64728507e-01 6.04205489e-01 9.41194117e-01
2.47508243e-01 1.14839643e-01 -6.81258559e-01 1.42362380e+00
-3.05885822e-01 -1.71911991e+00 -1.91535890e-01 3.05918515e-01
6.82010353e-01 4.47973013e-01 7.74778798e-02 8.42287168e-02
3.05505157e-01 -8.97314608e-01 2.52236813e-01 6.08761132e-01
1.02097094e+00 -6.94080830e-01 5.98585367e-01 5.39169431e-01
-1.28131437e+00 -3.99575979e-01 -4.39688712e-01 2.63921320e-01
1.68111131e-01 5.42624950e-01 -1.37684286e-01 3.87907565e-01
6.78365290e-01 5.53078592e-01 -3.65019619e-01 1.30345428e+00
1.88295692e-01 6.39488339e-01 -7.50824153e-01 -5.42723596e-01
1.44386888e-01 -3.06631058e-01 1.85301140e-01 4.67136413e-01
5.28189540e-01 1.76102772e-01 -2.94991046e-01 7.82850623e-01
-5.05083621e-01 -1.25044912e-01 -9.38408434e-01 -6.47167489e-02
8.05308104e-01 1.12382758e+00 -5.48678160e-01 -1.76062047e-01
-4.49974149e-01 7.98823416e-01 -1.07332982e-01 3.48177224e-01
-7.65322447e-01 -5.82008183e-01 1.01414168e+00 -1.71664193e-01
4.82044816e-01 -3.31811935e-01 -6.13615215e-01 -1.04475105e+00
4.67685103e-01 -4.22716856e-01 -5.26484847e-03 -4.94324803e-01
-1.06430137e+00 3.18549067e-01 -5.59897959e-01 -1.38372326e+00
1.10871255e-01 -5.66317499e-01 -8.20601225e-01 4.72780943e-01
-1.66720521e+00 -1.09526432e+00 -4.99357820e-01 7.62797177e-01
-1.44774035e-01 -3.73126954e-01 4.85946298e-01 5.75488806e-01
-6.58451200e-01 9.41731513e-01 6.36218727e-01 2.90516824e-01
2.34056994e-01 -8.53981823e-02 5.61927199e-01 8.30713272e-01
-6.21608905e-02 2.20207617e-01 -1.09143816e-01 -6.55946672e-01
-2.09985995e+00 -1.48283660e+00 1.04738140e+00 -7.77766630e-02
2.56824732e-01 -3.28498811e-01 -7.60736108e-01 3.41034919e-01
-2.25635260e-01 7.20898390e-01 4.57473934e-01 -7.69101143e-01
-3.01818699e-01 -8.77734125e-01 -1.47680843e+00 4.79943275e-01
1.17664242e+00 -5.76583683e-01 3.67161967e-02 2.02804044e-01
4.78151977e-01 1.66079074e-01 -1.07330419e-01 4.09509391e-01
4.80996281e-01 -6.07491195e-01 5.33050537e-01 -3.63557458e-01
-4.69902456e-01 -5.96652687e-01 -2.07761601e-01 -7.13724196e-01
1.62056848e-01 -6.15922689e-01 -1.57322630e-01 1.10999703e+00
1.06393486e-01 -1.34142888e+00 1.43776953e+00 1.31534779e+00
8.44006762e-02 -5.75994790e-01 -1.67000115e+00 -8.23932707e-01
-3.27982336e-01 -7.28316128e-01 1.12749970e+00 6.14539564e-01
-2.09893659e-01 -4.34518754e-01 -3.07817966e-01 1.42031508e-02
9.83549058e-01 1.35623038e-01 7.77236521e-01 -1.05715227e+00
4.15868402e-01 -4.02091444e-01 -1.01028430e+00 -1.12371767e+00
2.36314207e-01 -1.02002466e+00 7.41517097e-02 -1.42873812e+00
-9.21991989e-02 -8.40137959e-01 -6.21856093e-01 7.68714607e-01
4.99117732e-01 3.05508882e-01 1.29991621e-01 1.56190425e-01
-8.64384711e-01 8.39965999e-01 1.15081966e+00 -4.28884596e-01
2.12456629e-01 2.36364871e-01 -4.04727250e-01 2.29241043e-01
7.93629467e-01 -4.58948731e-01 -3.40826541e-01 -5.95006108e-01
-6.64665997e-02 -7.38430396e-02 6.80113137e-01 -1.09379768e+00
1.03985894e+00 -2.88088739e-01 2.80899018e-01 -7.15957701e-01
3.37071508e-01 -1.37027359e+00 3.63970578e-01 7.33861804e-01
1.17880635e-01 -4.51516151e-01 4.73285988e-02 7.58029103e-01
-2.63211012e-01 3.36258769e-01 3.31334293e-01 3.26588213e-01
-9.81243908e-01 8.42818558e-01 -3.60136658e-01 -4.54260439e-01
1.38207400e+00 -7.38541663e-01 -4.12780315e-01 -2.20970973e-01
1.78140655e-01 6.24725819e-01 5.40392697e-01 4.15853709e-01
8.32372069e-01 -1.56387746e+00 -2.64797330e-01 8.82250845e-01
2.34641030e-01 -7.28909671e-02 6.50849104e-01 7.16568291e-01
-2.90876091e-01 7.79754877e-01 -3.10745925e-01 -4.28340733e-01
-1.04823256e+00 4.60171759e-01 1.68198407e-01 5.09297192e-01
-3.66536289e-01 5.12244761e-01 -2.61199117e-01 -4.18896735e-01
3.29151869e-01 -2.46411100e-01 3.83503377e-01 -5.06227672e-01
4.75001991e-01 5.07007957e-01 2.16689482e-01 -7.26389050e-01
-6.68820739e-01 5.40203273e-01 2.33643040e-01 3.86033386e-01
1.02563751e+00 -6.14218786e-03 -2.12906711e-02 -4.63515788e-01
1.46841991e+00 -5.07475555e-01 -1.49425757e+00 -3.03204060e-01
-2.60929912e-01 -6.75291955e-01 3.77543330e-01 -5.65189302e-01
-1.69434953e+00 7.77511239e-01 8.02325785e-01 -4.83108580e-01
1.11018956e+00 -4.29418743e-01 1.64449918e+00 8.10811877e-01
8.45254481e-01 -1.18160772e+00 -5.68611622e-01 2.19821855e-01
6.04234189e-02 -1.29377341e+00 -4.55484778e-01 -1.00966103e-01
-4.48788464e-01 9.59385693e-01 5.86173236e-01 1.40980572e-01
8.39823067e-01 2.51959771e-01 9.17198732e-02 -9.88553390e-02
-5.89918494e-01 6.02004081e-02 6.46031722e-02 6.97279274e-01
-7.79998004e-01 1.29940644e-01 -1.55373588e-01 7.23139822e-01
2.57504553e-01 5.99683225e-01 -2.41293803e-01 1.07308590e+00
-4.32316482e-01 -1.03190708e+00 -5.63818142e-02 8.13214779e-01
6.10723160e-02 2.43086249e-01 -2.55614549e-01 1.46506518e-01
2.74879783e-01 9.07402217e-01 1.22394562e-01 -7.11619616e-01
1.69550657e-01 2.23345891e-01 -4.36695758e-03 3.69650334e-01
-1.54387534e-01 -8.38540614e-01 -1.56168193e-01 -6.61066771e-01
-1.05883673e-01 -4.93539006e-01 -1.39515984e+00 -7.34672427e-01
-2.62108803e-01 7.37093836e-02 1.32340443e+00 9.69588041e-01
8.83707404e-01 -8.76524597e-02 9.31926131e-01 -4.92299169e-01
-4.85649019e-01 -1.52173743e-01 -3.54642868e-01 1.67605519e-01
2.68888056e-01 -3.16570282e-01 -2.28651956e-01 -4.11811680e-01] | [7.918078422546387, -0.6112276911735535] |
fc6163f2-69cc-4818-b371-7ad08fb01ffa | bopr-body-aware-part-regressor-for-human | 2303.11675 | null | https://arxiv.org/abs/2303.11675v2 | https://arxiv.org/pdf/2303.11675v2.pdf | BoPR: Body-aware Part Regressor for Human Shape and Pose Estimation | This paper presents a novel approach for estimating human body shape and pose from monocular images that effectively addresses the challenges of occlusions and depth ambiguity. Our proposed method BoPR, the Body-aware Part Regressor, first extracts features of both the body and part regions using an attention-guided mechanism. We then utilize these features to encode extra part-body dependency for per-part regression, with part features as queries and body feature as a reference. This allows our network to infer the spatial relationship of occluded parts with the body by leveraging visible parts and body reference information. Our method outperforms existing state-of-the-art methods on two benchmark datasets, and our experiments show that it significantly surpasses existing methods in terms of depth ambiguity and occlusion handling. These results provide strong evidence of the effectiveness of our approach.The code and data are available for research purposes at https://github.com/cyk990422/BoPR. | ['Ying Shan', 'Jifeng Ning', 'Shaoli Huang', 'Yongkang Cheng'] | 2023-03-21 | null | null | null | null | ['occlusion-handling'] | ['computer-vision'] | [-1.55166954e-01 1.59942359e-01 -5.75454116e-01 -3.46501797e-01
-4.10778791e-01 -2.51176506e-01 3.08510482e-01 -3.21576327e-01
-1.14766791e-01 5.42194545e-01 6.39351726e-01 4.13119346e-01
1.91358313e-01 -3.84437054e-01 -7.69767284e-01 -4.18026388e-01
5.13307303e-02 4.09794241e-01 2.45413288e-01 -1.12837784e-01
-1.88953981e-01 4.35622364e-01 -1.56496191e+00 -5.76390289e-02
4.63435650e-01 1.13706219e+00 -3.31632227e-01 4.13285404e-01
4.65194941e-01 4.03087467e-01 -2.83626676e-01 -5.48110843e-01
6.06048763e-01 -1.98159069e-01 -7.59324074e-01 3.48216355e-01
9.36234236e-01 -6.06784761e-01 -6.95167363e-01 5.07270813e-01
8.21217060e-01 9.02501419e-02 2.79138744e-01 -1.09187663e+00
-2.84457356e-01 1.91615209e-01 -9.95257497e-01 1.32591531e-01
6.59693480e-01 1.98543787e-01 8.69371712e-01 -9.37955737e-01
7.03894794e-01 1.47820735e+00 6.63189888e-01 6.90096319e-01
-1.10430586e+00 -6.59572780e-01 5.45974970e-01 -5.28055541e-02
-1.47265255e+00 -7.17035115e-01 9.19190526e-01 -4.36857969e-01
6.39781535e-01 2.24224478e-01 1.08257079e+00 9.62254167e-01
1.72029436e-01 1.19380844e+00 6.86647713e-01 -2.90775537e-01
-2.26665437e-01 -3.60308826e-01 1.51272416e-01 9.39680696e-01
4.73373652e-01 1.59266412e-01 -8.15979600e-01 -1.58742860e-01
1.06862700e+00 1.67737007e-01 -4.23976660e-01 -9.43768740e-01
-8.69121313e-01 5.92023909e-01 6.79684401e-01 -1.98310390e-01
-5.04266679e-01 4.41603959e-01 2.18726739e-01 -1.82203561e-01
6.05360627e-01 -2.41788208e-01 -5.68887293e-01 2.11992577e-01
-6.93696797e-01 4.99190509e-01 7.05670178e-01 1.05648243e+00
4.54903156e-01 -2.91978687e-01 -3.04303944e-01 8.29647005e-01
6.76043868e-01 5.52275658e-01 2.00583249e-01 -9.34536278e-01
4.75599021e-01 7.53944576e-01 1.11449599e-01 -8.76101851e-01
-5.42467237e-01 -4.11989242e-01 -5.35180032e-01 1.02781586e-01
4.35245275e-01 -1.54867128e-01 -1.00687242e+00 1.71559739e+00
1.09121239e+00 -2.34246507e-01 -5.05231559e-01 1.37186694e+00
1.19322193e+00 8.18299316e-03 1.82473421e-01 2.79082179e-01
1.65998852e+00 -1.28850913e+00 -5.58343470e-01 -6.04067802e-01
2.20622331e-01 -5.24774134e-01 7.53331482e-01 1.77346662e-01
-1.31054747e+00 -5.72819710e-01 -9.19584870e-01 -4.95892763e-01
-6.68078288e-03 4.42062467e-01 8.63907099e-01 4.35052902e-01
-7.33967066e-01 4.15115058e-01 -1.04806077e+00 -4.16723549e-01
5.67147911e-01 6.03500783e-01 -6.04761183e-01 -1.77847415e-01
-7.79937923e-01 6.47760034e-01 5.56571744e-02 3.73536170e-01
-5.91337621e-01 -3.75875205e-01 -1.40087700e+00 -1.67903796e-01
4.77509946e-01 -1.29107380e+00 1.18967986e+00 -7.47722924e-01
-1.40792298e+00 1.10584116e+00 -2.60996610e-01 -2.54426867e-01
6.46899164e-01 -9.35866296e-01 5.87627105e-03 3.11574429e-01
-2.35044304e-02 9.51708734e-01 9.15250361e-01 -9.72216070e-01
-3.24092716e-01 -7.96853662e-01 5.98710217e-02 5.55433989e-01
1.60082042e-01 -5.44754639e-02 -1.12231505e+00 -6.15118563e-01
5.32789111e-01 -1.03880203e+00 -8.75470787e-02 7.10761070e-01
-4.81181711e-01 -1.46024927e-01 3.91903788e-01 -9.02187765e-01
1.12410378e+00 -1.99083948e+00 3.50811541e-01 6.25415593e-02
4.57416147e-01 1.36591438e-02 1.33446619e-01 2.54469305e-01
1.50409415e-02 -3.63361210e-01 -8.61008242e-02 -6.92920625e-01
2.55015772e-02 1.26581401e-01 1.54889494e-01 9.58772302e-01
1.49951980e-01 1.17599344e+00 -5.61377406e-01 -7.31542289e-01
3.48764181e-01 7.11583674e-01 -5.39921343e-01 1.42905802e-01
2.70591322e-02 6.39617860e-01 -4.70529765e-01 1.06311285e+00
7.23995447e-01 -2.96111017e-01 1.11181706e-01 -3.22737545e-01
3.16219240e-01 2.67625928e-01 -1.11660850e+00 1.97048783e+00
5.08500356e-03 1.95051461e-01 2.02773079e-01 -4.69733298e-01
5.75378358e-01 2.53627062e-01 6.04261816e-01 -5.85936487e-01
3.20057899e-01 -1.51209086e-01 -1.35694101e-01 -3.51817191e-01
1.47063360e-01 1.14701428e-01 2.67986394e-02 -4.99835014e-02
1.10503606e-01 1.81275353e-01 1.13918856e-01 -2.13549826e-02
7.98914611e-01 8.25034380e-01 5.75827301e-01 -3.14294510e-02
3.95657837e-01 -2.98820406e-01 7.30472267e-01 3.38498980e-01
-3.36279809e-01 7.97556221e-01 1.72571421e-01 -6.03235126e-01
-5.62843919e-01 -1.05458188e+00 -5.76401204e-02 1.16751564e+00
3.73008579e-01 -5.51618278e-01 -4.96980429e-01 -6.41266704e-01
4.84690219e-01 -6.04342930e-02 -9.49834526e-01 1.22305833e-01
-7.39571095e-01 -2.47224346e-01 1.32015780e-01 9.68101263e-01
3.76501113e-01 -9.80656743e-01 -8.34466457e-01 -7.47604445e-02
-3.52084100e-01 -1.06464148e+00 -6.76945269e-01 -2.61269987e-01
-1.02974737e+00 -1.30362868e+00 -1.02931631e+00 -4.16173667e-01
7.90328681e-01 1.71116069e-01 1.18601668e+00 3.09696674e-01
-6.16462111e-01 5.32230854e-01 -1.33243073e-02 -3.48087847e-01
3.31622541e-01 3.68028171e-02 -4.24061194e-02 -1.45314425e-01
2.23322034e-01 -6.21561885e-01 -1.21032596e+00 4.62724954e-01
-3.44456822e-01 2.21699327e-01 6.36260152e-01 5.57293653e-01
7.52288997e-01 -6.95672035e-01 -1.05202042e-01 -5.94081461e-01
-8.60880911e-02 -3.33797604e-01 -5.77769876e-01 -1.16324969e-01
-1.62870094e-01 -9.17577371e-02 -1.34451747e-01 -3.62024963e-01
-8.46041560e-01 4.38590854e-01 -3.31390910e-02 -5.98704994e-01
-1.92998290e-01 1.73146248e-01 -3.15356046e-01 -8.84419084e-02
4.48908329e-01 -4.01503071e-02 5.01167178e-02 -7.96960175e-01
3.41139972e-01 1.82704419e-01 7.52125621e-01 -6.31672859e-01
6.87367797e-01 8.42283428e-01 1.53433934e-01 -5.34931183e-01
-1.03775418e+00 -8.77064466e-01 -1.05101478e+00 -2.60211170e-01
8.27968299e-01 -1.36722767e+00 -7.13470995e-01 3.71079266e-01
-9.35826361e-01 -1.24456212e-01 -2.38018498e-01 5.34851491e-01
-5.22383213e-01 4.40138578e-01 -7.74756908e-01 -8.48653495e-01
-5.54869413e-01 -6.83276117e-01 1.62962282e+00 2.63898730e-01
-4.23521698e-01 -6.16359890e-01 5.80742396e-02 5.90901256e-01
-1.24377623e-01 6.12483144e-01 2.22083107e-01 -2.25362822e-01
-6.36664867e-01 -3.45131576e-01 -1.21316269e-01 -9.07639563e-02
-1.68384500e-02 -3.22404712e-01 -8.54890645e-01 -5.53940535e-01
-3.66432101e-01 -3.98208708e-01 8.09851825e-01 7.32100844e-01
9.64984119e-01 -3.09292823e-01 -6.12352729e-01 8.40191722e-01
1.09478056e+00 -4.70057428e-01 5.86084545e-01 1.74853697e-01
9.48834956e-01 6.34843886e-01 7.76384413e-01 6.33881092e-01
6.24953508e-01 9.82686520e-01 5.49868226e-01 -3.73069733e-01
-4.47608829e-01 -4.67489123e-01 1.23235293e-01 3.92964780e-01
-3.18587452e-01 -3.15543376e-02 -7.43343413e-01 6.30013287e-01
-1.95868015e+00 -6.49987996e-01 -9.43649039e-02 2.15330982e+00
6.27327502e-01 -1.31710932e-01 5.61540484e-01 -9.55167338e-02
4.98594671e-01 1.12346083e-01 -6.38540745e-01 7.86971152e-02
2.50640392e-01 1.31690472e-01 5.20057261e-01 2.89196551e-01
-1.50462377e+00 8.62556159e-01 6.11855745e+00 1.95425868e-01
-7.37325847e-01 2.68255007e-02 2.73951322e-01 -4.27828968e-01
2.86960572e-01 -2.86050826e-01 -1.02956760e+00 2.60939240e-01
2.71460623e-01 3.31035525e-01 1.04164280e-01 8.93732250e-01
-6.12290539e-02 -1.80656672e-01 -1.14804375e+00 1.09181380e+00
3.77289534e-01 -6.81134284e-01 -3.62069964e-01 2.95593470e-01
4.19675857e-01 1.14657074e-01 -1.90514386e-01 -6.73345150e-03
1.93307519e-01 -8.28757465e-01 8.86436939e-01 5.90672553e-01
5.44629395e-01 -3.54189843e-01 6.06289387e-01 1.33465409e-01
-1.45797420e+00 -3.36178206e-02 -2.91803002e-01 -3.56886655e-01
1.81411356e-01 2.84887046e-01 -4.18352723e-01 5.71926832e-01
9.05977547e-01 7.07217336e-01 -6.21754885e-01 1.23547423e+00
-5.97544909e-01 3.34427357e-01 -5.70330083e-01 4.88420010e-01
-4.10108209e-01 1.35115191e-01 4.16642636e-01 8.21175933e-01
-7.41193220e-02 2.75198162e-01 3.14410478e-01 6.90799177e-01
-1.07779734e-01 1.43659487e-01 -3.66282791e-01 3.80264670e-01
1.75211892e-01 1.12652588e+00 -5.47902942e-01 -3.15696329e-01
-5.04368544e-01 1.03333032e+00 4.49033469e-01 1.46070302e-01
-9.71928835e-01 8.64290223e-02 7.18870997e-01 3.69750440e-01
6.10024154e-01 -5.30675948e-02 -1.83067530e-01 -1.34333158e+00
5.30991077e-01 -7.78726220e-01 6.55518830e-01 -7.97053456e-01
-1.04769862e+00 2.78369159e-01 2.21726239e-01 -1.17171180e+00
-1.58635437e-01 -5.02050459e-01 -1.94318622e-01 7.21328437e-01
-1.17529440e+00 -1.63283932e+00 -5.84208369e-01 6.07014537e-01
5.12153208e-01 4.93968427e-01 5.88955522e-01 2.80614406e-01
-6.39135718e-01 6.17012978e-01 -6.06887877e-01 3.24170977e-01
6.18386090e-01 -9.55252647e-01 6.37227416e-01 7.66036689e-01
1.01743415e-01 7.14358449e-01 5.27535677e-01 -8.83956432e-01
-1.36382961e+00 -8.10617566e-01 6.83824480e-01 -8.18469584e-01
5.24261743e-02 -4.41921145e-01 -4.84463513e-01 9.19311047e-01
-1.69077680e-01 4.79101598e-01 6.14660621e-01 3.00404072e-01
-3.56875211e-01 3.07485238e-02 -9.58786190e-01 5.65284729e-01
1.59157169e+00 -6.07842728e-02 -6.83457255e-01 1.74927652e-01
4.39112693e-01 -1.04645514e+00 -8.61630082e-01 6.24491155e-01
1.14142442e+00 -8.82201076e-01 1.33314824e+00 -4.48889524e-01
4.86075729e-01 -2.95268476e-01 -7.44688362e-02 -7.18156755e-01
-4.00979728e-01 -4.14245814e-01 -7.44057953e-01 8.36575568e-01
-4.69783880e-03 -4.66174036e-01 8.85665655e-01 7.51584947e-01
4.32983190e-02 -1.02129197e+00 -8.31555426e-01 -6.11726165e-01
-1.89712211e-01 1.05328187e-02 5.19627154e-01 5.23426354e-01
-1.53594196e-01 1.54950574e-01 -6.03680134e-01 2.88092941e-01
6.02954924e-01 4.43874836e-01 1.22362828e+00 -1.17368174e+00
-5.17844439e-01 -1.37845635e-01 -6.68051064e-01 -1.34298182e+00
-6.89785257e-02 -4.51878369e-01 -4.97621037e-02 -1.62157655e+00
2.94703513e-01 1.13313645e-01 -9.74894464e-02 9.24640477e-01
-2.44487718e-01 7.10664570e-01 3.25615287e-01 1.62636518e-01
-6.16556644e-01 5.73520660e-01 1.34555018e+00 1.57954115e-02
-1.11797646e-01 1.85967878e-01 -6.45893872e-01 9.07097876e-01
6.45982087e-01 -3.85049075e-01 -1.97886959e-01 -4.08738613e-01
-1.12662919e-01 4.88113388e-02 7.24158645e-01 -1.11947441e+00
3.92439961e-02 8.67866203e-02 1.04669297e+00 -8.61041605e-01
8.36245954e-01 -7.77849615e-01 2.33522803e-01 5.83619356e-01
7.97917787e-03 -2.35798992e-02 3.14314127e-01 4.98415738e-01
1.26574218e-01 3.54681611e-01 5.22196233e-01 -1.84313476e-01
-5.81617534e-01 6.02920175e-01 3.17866415e-01 1.15230486e-01
8.13391566e-01 -3.80063921e-01 -1.30538091e-01 -4.29306954e-01
-8.96253705e-01 5.19517481e-01 6.71873569e-01 6.12182200e-01
5.78379273e-01 -1.29756951e+00 -6.77180231e-01 3.75311404e-01
2.67173827e-01 8.37304518e-02 2.59288132e-01 1.08116829e+00
-4.60676044e-01 4.19676960e-01 -2.62558848e-01 -7.68430591e-01
-1.70069039e+00 4.26274121e-01 3.95693332e-01 -1.03817739e-01
-9.84442174e-01 9.56289351e-01 6.50262535e-01 -3.60806137e-01
3.97783130e-01 -2.71282285e-01 1.09129310e-01 -3.40775013e-01
3.37405950e-01 2.81013578e-01 -2.33299300e-01 -1.00187278e+00
-6.05208039e-01 9.65278447e-01 6.89568222e-02 1.06855318e-01
1.08396697e+00 -3.77263814e-01 1.33376524e-01 1.01232104e-01
9.58836913e-01 1.93248361e-01 -1.45114172e+00 -3.62614691e-01
-4.86526638e-01 -7.56444514e-01 -2.23605484e-01 -9.17756438e-01
-1.26679063e+00 7.97348499e-01 6.06525540e-01 -5.52736104e-01
1.07222307e+00 4.05773073e-01 6.83141112e-01 -1.18352212e-01
4.02371496e-01 -8.15775037e-01 -1.75760418e-01 9.82774496e-02
1.17549813e+00 -1.23068738e+00 5.95907211e-01 -9.39876735e-01
-4.69364017e-01 6.47110939e-01 9.81846452e-01 -1.90275967e-01
6.10338569e-01 -6.26979843e-02 1.22702725e-01 -5.55642903e-01
-4.74270970e-01 -5.03227293e-01 9.23432827e-01 6.38802350e-01
6.03702962e-01 2.64829323e-02 -5.12475669e-01 5.26991308e-01
-3.33074927e-01 4.52274010e-02 -3.55409116e-01 1.06554961e+00
-4.34589386e-02 -1.05496538e+00 -5.51196873e-01 2.80757368e-01
-5.24812698e-01 2.01472864e-01 -5.64814091e-01 1.07143688e+00
1.86746672e-01 5.28019667e-01 -6.13698028e-02 2.83085574e-05
4.19884145e-01 1.74779929e-02 8.56356621e-01 -6.08938396e-01
-3.58449638e-01 3.86053056e-01 1.73644558e-01 -1.16198468e+00
-4.59169000e-01 -6.75281465e-01 -1.02355397e+00 -9.86690223e-02
-4.60852027e-01 -3.97013754e-01 4.41681564e-01 7.47286320e-01
5.72075844e-01 3.48770797e-01 7.08182007e-02 -1.25839174e+00
-4.06885862e-01 -8.70308995e-01 -3.48836750e-01 6.19831383e-01
3.52654159e-01 -1.12028503e+00 2.79737986e-04 -1.26947323e-02] | [7.057725429534912, -0.9316050410270691] |
55b3305c-7d7e-4377-a427-85f7a7a5ea5d | study-of-frequency-domain-exponential | 2201.05501 | null | https://arxiv.org/abs/2201.05501v1 | https://arxiv.org/pdf/2201.05501v1.pdf | Study of Frequency domain exponential functional link network filters | The exponential functional link network (EFLN) filter has attracted tremendous interest due to its enhanced nonlinear modeling capability. However, the computational complexity will dramatically increase with the dimension growth of the EFLN-based filter. To improve the computational efficiency, we propose a novel frequency domain exponential functional link network (FDEFLN) filter in this paper. The idea is to organize the samples in blocks of expanded input data, transform them from time domain to frequency domain, and thus execute the filtering and adaptation procedures in frequency domain with the overlap-save method. A FDEFLN-based nonlinear active noise control (NANC) system has also been developed to form the frequency domain exponential filtered-s least mean-square (FDEFsLMS) algorithm. Moreover, the stability, steady-state performance and computational complexity of algorithms are analyzed. Finally, several numerical experiments corroborate the proposed FDEFLN-based algorithms in nonlinear system identification, acoustic echo cancellation and NANC implementations, which demonstrate much better computational efficiency. | ['Y. Yu', 'R. C. de Lamareb', 'S. Tana', 'T. Yu'] | 2022-01-12 | null | null | null | null | ['acoustic-echo-cancellation', 'acoustic-echo-cancellation'] | ['medical', 'speech'] | [ 1.45572424e-01 -1.99044093e-01 6.42376244e-01 2.28719767e-02
-2.99613059e-01 -3.70631039e-01 -1.69056524e-02 -5.59523463e-01
-5.00677109e-01 8.28252614e-01 1.05152883e-01 -2.69129574e-01
-8.14076066e-01 -2.12920293e-01 -1.28831476e-01 -8.90154898e-01
-2.49903411e-01 -2.81134695e-01 1.07128985e-01 -2.41083264e-01
-1.90849036e-01 4.79525626e-01 -1.30541193e+00 -3.75964075e-01
1.22139907e+00 9.46233869e-01 2.09740400e-01 7.86902368e-01
3.16497415e-01 2.73221403e-01 -6.90268457e-01 5.60332648e-02
3.65336001e-01 -7.42639601e-01 5.39785400e-02 -2.35573560e-01
-4.70779017e-02 -8.75903070e-02 -4.94974047e-01 1.19874752e+00
1.05066919e+00 7.96060205e-01 5.66651046e-01 -7.87563443e-01
-1.07427627e-01 5.44890285e-01 -1.29641563e-01 1.47730723e-01
1.70330599e-01 -3.93451229e-02 2.46303350e-01 -1.29301548e+00
3.10761899e-01 1.27179766e+00 1.08190823e+00 4.16791052e-01
-1.25560975e+00 -1.05036843e+00 -2.14062721e-01 5.17224483e-02
-1.45645821e+00 -6.96749747e-01 7.20178485e-01 -3.17507058e-01
7.24234462e-01 4.29042190e-01 9.01989102e-01 3.37990433e-01
4.89131287e-02 3.26394230e-01 9.02377665e-01 -6.12661183e-01
5.84833547e-02 -1.85997024e-01 3.06093663e-01 6.38081193e-01
2.72438169e-01 5.73338270e-01 -5.70279002e-01 -3.15370351e-01
9.75795507e-01 -3.31285149e-01 -8.27307701e-01 3.45759660e-01
-6.78174078e-01 5.14733076e-01 1.68504670e-01 4.20738757e-01
-2.17895880e-01 1.69579342e-01 2.29841679e-01 5.58435142e-01
6.26880229e-01 4.33608711e-01 -1.51923329e-01 -7.78724253e-03
-1.11587751e+00 3.22579443e-01 1.07661939e+00 8.37378263e-01
4.28665191e-01 1.01878250e+00 2.29620978e-01 8.91458273e-01
5.46082079e-01 1.20196724e+00 3.57860535e-01 -9.73117530e-01
9.74509120e-02 -2.22392497e-03 -3.32491882e-02 -1.24073970e+00
-7.48374164e-01 -1.07952499e+00 -1.21175241e+00 6.76985690e-03
1.83155581e-01 -7.30151951e-01 -4.41218555e-01 1.65833485e+00
2.76896596e-01 4.02643025e-01 2.66385525e-01 9.08688724e-01
5.54037333e-01 1.09839594e+00 -2.18616903e-01 -9.37035799e-01
8.06818783e-01 -5.46687841e-01 -1.47721183e+00 2.41583362e-02
3.90074193e-01 -1.15373266e+00 4.57674682e-01 3.72392088e-01
-1.11398268e+00 -8.14360201e-01 -7.87369013e-01 3.78596663e-01
7.59344548e-02 3.29850376e-01 5.13517484e-02 7.20662355e-01
-1.06071866e+00 4.90460515e-01 -6.14444911e-01 2.35983849e-01
-3.87761086e-01 4.24949080e-01 -9.70010459e-02 5.47847569e-01
-1.52078593e+00 5.97887039e-01 2.74216592e-01 8.14557314e-01
-1.85836002e-01 -9.00266290e-01 -3.89691472e-01 6.33421764e-02
2.68490911e-01 -3.48138809e-01 9.73193109e-01 -8.57243419e-01
-1.67624187e+00 -1.34290904e-01 -2.89858580e-01 -3.87452304e-01
2.30595589e-01 -1.99982330e-01 -1.08201051e+00 1.06794396e-02
-3.10558796e-01 -2.26939425e-01 1.22721124e+00 -9.25171137e-01
-6.12897575e-01 9.71012414e-02 -5.57332158e-01 1.22107416e-01
-3.38882595e-01 -3.04779798e-01 -1.26701295e-02 -9.59690809e-01
5.17267406e-01 -6.45298719e-01 -3.78179312e-01 -1.24568656e-01
-1.96030483e-01 1.89318970e-01 9.57156181e-01 -7.67936647e-01
2.06151271e+00 -2.51059866e+00 2.19852030e-01 6.88772798e-01
1.40599534e-01 8.08953822e-01 6.24176636e-02 6.89831197e-01
1.28836511e-02 -2.24549323e-01 -1.86757207e-01 -3.59433368e-02
-3.13105047e-01 -1.19442031e-01 -1.20656744e-01 5.46319425e-01
-1.38216585e-01 4.11815405e-01 -5.10768890e-01 -2.16091886e-01
6.72190636e-02 4.25829202e-01 -7.58403659e-01 1.03110112e-01
4.84040558e-01 5.70480764e-01 -2.31355622e-01 3.17264050e-01
8.93149912e-01 1.35504156e-01 -2.76659355e-02 -8.45244169e-01
-7.91323960e-01 -2.69746989e-01 -1.65281940e+00 1.03112841e+00
-6.27314150e-01 8.17579746e-01 9.78905797e-01 -1.03734004e+00
1.05014038e+00 7.45134175e-01 4.33912992e-01 -7.39846766e-01
1.35222718e-01 7.67929435e-01 3.47592175e-01 -6.51552260e-01
2.31936172e-01 -2.66781986e-01 3.29903424e-01 4.60931100e-02
1.60584733e-01 -1.12852179e-01 1.81071967e-01 -2.27555763e-02
6.84271812e-01 -4.92538601e-01 4.88044262e-01 -9.58765626e-01
1.15166581e+00 -1.83550715e-01 7.98809886e-01 6.28926992e-01
-1.00528397e-01 -1.06311217e-01 -1.38510063e-01 1.24908485e-01
-8.28198075e-01 -6.09425187e-01 -2.09925368e-01 4.72510278e-01
4.35470156e-02 -2.26650298e-01 -6.41641021e-01 2.90591925e-01
6.91638812e-02 2.53658324e-01 1.55438989e-01 -2.88622320e-01
-1.08462465e+00 -3.00156027e-01 7.95736015e-01 1.71161935e-01
6.22170269e-01 -3.38799864e-01 -1.67000338e-01 7.47977138e-01
-5.27246564e-04 -7.00599551e-01 -6.76434875e-01 7.79868513e-02
-8.28093410e-01 -8.11117113e-01 -7.14645922e-01 -1.20034492e+00
5.44400394e-01 2.29844898e-02 4.14891779e-01 -1.16800494e-01
-8.99201110e-02 5.86437225e-01 -2.00945556e-01 -3.18785071e-01
-1.54187888e-01 -2.34460846e-01 6.68964267e-01 1.98645294e-01
-3.20853472e-01 -6.81996465e-01 -6.17613077e-01 5.64363122e-01
-6.61231101e-01 4.31877822e-02 3.78361672e-01 9.91425455e-01
3.16817790e-01 5.48127294e-01 9.52813983e-01 -6.72840297e-01
1.06960094e+00 6.60617128e-02 -1.10367060e+00 3.23993042e-02
-6.51036143e-01 -3.83885652e-01 1.13514543e+00 -7.98754513e-01
-1.22304273e+00 4.01390949e-03 -4.74666715e-01 -2.74049878e-01
6.90038204e-01 7.99913049e-01 -2.94594356e-04 -5.99328101e-01
5.71212292e-01 4.49559331e-01 3.49725813e-01 -6.34850919e-01
3.27848792e-02 7.14071512e-01 8.93339574e-01 -1.37648240e-01
1.23066986e+00 9.62245557e-03 1.32599190e-01 -1.36057496e+00
-3.80196750e-01 -5.11784256e-01 -6.29752278e-02 -5.34278810e-01
2.83950776e-01 -7.51575351e-01 -1.27884161e+00 8.11595917e-01
-1.15394640e+00 -5.42456023e-02 -2.24825904e-01 1.29804838e+00
-2.57371336e-01 1.64822683e-01 -6.79897666e-01 -1.49045241e+00
-5.78478456e-01 -8.40445518e-01 8.77303705e-02 3.74573857e-01
-2.90062465e-02 -1.13732421e+00 -1.32489964e-01 -4.13561076e-01
9.63229120e-01 1.33086056e-01 6.24789178e-01 -9.72409025e-02
-4.35432523e-01 -1.84972629e-01 6.33164868e-02 5.85433483e-01
-1.48857847e-01 -2.51456290e-01 -5.52248180e-01 -6.08723819e-01
6.86540604e-01 4.31899458e-01 4.98785168e-01 7.47585177e-01
3.47868741e-01 -5.69261432e-01 -1.37744755e-01 7.94300079e-01
1.79238367e+00 7.16892481e-01 2.95289367e-01 -2.78810471e-01
3.07947457e-01 2.84359872e-01 3.26072544e-01 2.76681036e-01
-4.10557330e-01 2.62191027e-01 -2.52279222e-01 -3.90033275e-01
-1.17060028e-01 1.55032828e-01 3.87234718e-01 1.79662633e+00
-2.09774181e-01 -5.28373063e-01 -3.37374389e-01 1.03419356e-01
-1.52760077e+00 -8.27210844e-01 -4.67189997e-01 1.84717834e+00
7.56848395e-01 -1.62814111e-01 -2.72393733e-01 5.89005470e-01
8.27696919e-01 -1.64924353e-01 -5.93311012e-01 -1.35661855e-01
-3.05617481e-01 2.81163514e-01 6.88253760e-01 9.31032360e-01
-8.28269482e-01 2.81731248e-01 6.00576878e+00 1.29443419e+00
-1.20240104e+00 1.95042081e-02 -1.03344284e-01 3.13515186e-01
3.38197835e-02 -1.31015778e-01 -9.01374638e-01 4.04254019e-01
1.04489589e+00 -7.24779248e-01 6.15777552e-01 3.68519306e-01
7.44199097e-01 1.70295313e-02 -3.16262752e-01 1.23315859e+00
-2.14145571e-01 -1.00298429e+00 -5.31047940e-01 -2.62516052e-01
6.48672462e-01 -7.17982411e-01 -4.26097922e-02 1.99102849e-01
-5.48319340e-01 -5.12429595e-01 7.15185404e-01 1.23330927e+00
9.44623053e-01 -7.06020713e-01 5.16517818e-01 6.77345932e-01
-1.69233525e+00 -3.63151819e-01 -4.54243481e-01 -1.68855563e-01
6.52731180e-01 8.92294645e-01 -2.33734697e-01 6.00416362e-01
2.00269207e-01 4.91079986e-01 1.12804823e-01 1.37780941e+00
3.90233219e-01 1.01310432e+00 -6.14095211e-01 -3.76348704e-01
6.17095493e-02 -6.08132482e-01 9.75957036e-01 1.08034790e+00
6.60221040e-01 7.48055041e-01 1.19948210e-02 6.47701979e-01
3.37776721e-01 1.36786640e-01 -3.20141343e-03 -8.94912407e-02
6.57394886e-01 8.84219766e-01 -2.12796405e-01 -1.55338287e-01
-4.78092670e-01 2.93282390e-01 -6.07535958e-01 8.03421855e-01
-6.15162373e-01 -1.09332526e+00 3.85663182e-01 2.89958596e-01
-1.92137361e-01 -4.34366673e-01 7.75298104e-02 -7.75294542e-01
-1.87309533e-01 -7.69227147e-01 -1.48538366e-01 -3.30222696e-01
-1.04472971e+00 7.19730020e-01 -2.25862086e-01 -1.79303157e+00
-2.86506921e-01 -3.87991399e-01 -3.27539086e-01 1.26584601e+00
-1.00850260e+00 -3.68690223e-01 3.04223206e-02 7.32544184e-01
3.36771846e-01 -3.78957480e-01 6.73275948e-01 9.37367260e-01
-3.66373777e-01 6.38781190e-01 1.03803837e+00 -1.13341138e-01
4.43774372e-01 -6.45464540e-01 -1.67284980e-01 1.07092237e+00
-7.97834337e-01 1.00388157e+00 9.09849107e-01 -7.30341196e-01
-1.32576871e+00 -9.61708248e-01 8.12894046e-01 7.39318550e-01
5.75403988e-01 -4.04585242e-01 -9.77704823e-01 -1.17991315e-02
1.30652916e-02 -1.43499836e-01 4.31305677e-01 -4.84067082e-01
3.16241980e-01 -6.81888223e-01 -1.01206815e+00 3.77162308e-01
9.73939478e-01 -5.10015547e-01 -1.69094473e-01 3.76650728e-02
7.86269009e-01 -6.06011927e-01 -9.63847041e-01 6.06721461e-01
6.45896733e-01 -5.90284824e-01 9.76367116e-01 -4.23739664e-02
-3.17941397e-01 -6.67052329e-01 -7.98789188e-02 -1.44890881e+00
-7.43266463e-01 -1.28420913e+00 -1.61970660e-01 1.14254689e+00
4.86897141e-01 -1.18269134e+00 3.15612882e-01 1.29782692e-01
-4.57155585e-01 -6.74742460e-01 -1.00251901e+00 -1.03646779e+00
-4.16964501e-01 -3.09183061e-01 4.97171506e-02 4.59465593e-01
7.29001015e-02 2.65986055e-01 -6.59001231e-01 4.62381274e-01
7.18565762e-01 -3.36832285e-01 2.35768005e-01 -1.27631247e+00
-5.19191325e-01 -9.52238664e-02 -1.26642287e-01 -1.46550727e+00
-1.65169746e-01 -5.76969385e-01 1.70566112e-01 -1.27435029e+00
-7.79169679e-01 -4.84479994e-01 -5.59482537e-02 -3.31507802e-01
-1.20662928e-01 2.53405333e-01 1.56232923e-01 2.34970838e-01
6.60927519e-02 4.55971330e-01 1.35505772e+00 1.60303608e-01
-4.16588843e-01 5.81784308e-01 6.03429489e-02 4.75999743e-01
3.97884130e-01 -1.43834502e-01 -7.02936888e-01 -3.01762849e-01
2.43305434e-02 6.96149230e-01 8.14741664e-03 -1.40557683e+00
9.77313638e-01 3.36716175e-01 3.10257316e-01 -8.51330340e-01
5.11695683e-01 -1.08145845e+00 6.30565047e-01 9.16250467e-01
-2.79125333e-01 -9.33082029e-03 2.44781867e-01 6.55054688e-01
-5.87743580e-01 -1.52790725e-01 1.12824166e+00 3.29455227e-01
-2.92947620e-01 1.00493804e-01 -9.87706363e-01 -3.75094265e-03
4.35178190e-01 -2.50865608e-01 -3.32040004e-02 -6.34497881e-01
-1.00572681e+00 1.75843820e-01 -6.00279689e-01 -3.90645713e-01
6.80158317e-01 -1.37444437e+00 -6.20234370e-01 7.51253605e-01
-6.96087599e-01 -3.71765584e-01 8.04450929e-01 1.16396832e+00
-5.37215650e-01 6.25584126e-01 3.96705002e-01 -4.47710246e-01
-1.25945055e+00 -1.52881183e-02 6.55444384e-01 -8.92368853e-02
-3.62199128e-01 1.00398183e+00 -3.38149294e-02 -2.94406772e-01
2.65012026e-01 -1.29021168e-01 -7.51355439e-02 4.54940014e-02
4.94801670e-01 9.03532863e-01 5.51694147e-02 -4.88048017e-01
-2.86361482e-03 9.84593570e-01 5.09033442e-01 -3.60290080e-01
1.04062831e+00 -4.08041209e-01 -4.20467436e-01 5.72869889e-02
1.41395366e+00 3.95706356e-01 -9.02114689e-01 -5.60680151e-01
-3.36176872e-01 -2.95423120e-01 4.22205180e-02 -5.32301962e-01
-1.15970755e+00 3.48615199e-01 9.48731363e-01 2.72409528e-01
1.73589623e+00 -7.31508613e-01 9.15613949e-01 4.27430451e-01
5.82510084e-02 -1.15087724e+00 -3.50685894e-01 7.16785431e-01
8.14715505e-01 -2.92074651e-01 1.17074633e-02 -7.10701764e-01
2.46371746e-01 1.40078664e+00 3.49990398e-01 -2.27632388e-01
1.29155016e+00 6.81476474e-01 1.53807685e-01 2.99133748e-01
-4.52474147e-01 3.26067917e-02 3.53539228e-01 4.85774904e-01
4.86946404e-01 -2.27184579e-01 -1.18770206e+00 8.31844628e-01
-2.48416513e-01 -8.43422711e-02 3.65120053e-01 5.38324654e-01
-7.44364023e-01 -9.68155742e-01 -6.42385602e-01 5.75475097e-01
-2.78850615e-01 1.97326653e-02 3.52583855e-01 6.57902479e-01
7.24693108e-03 1.12194812e+00 1.27637852e-03 -4.09611374e-01
8.47313941e-01 -4.92498465e-02 1.69446059e-02 6.70391740e-03
-6.67218149e-01 9.05288756e-01 5.81954159e-02 -1.44439325e-01
-3.12899798e-01 -3.50714862e-01 -1.43510246e+00 -3.39581728e-01
-9.97450054e-01 7.36231089e-01 3.97602111e-01 5.51498175e-01
6.91955090e-02 8.01421165e-01 7.51770914e-01 -5.05249679e-01
-5.15671909e-01 -9.34037626e-01 -8.39877248e-01 -7.92203993e-02
5.54333627e-01 -5.40611386e-01 -8.14485967e-01 -1.32427335e-01] | [15.099013328552246, 5.771141529083252] |
b23664f3-ed5a-4dfb-a7ad-b4fe8e533f8d | improved-ccg-parsing-with-semi-supervised | null | null | https://aclanthology.org/Q14-1026 | https://aclanthology.org/Q14-1026.pdf | Improved CCG Parsing with Semi-supervised Supertagging | Current supervised parsers are limited by the size of their labelled training data, making improving them with unlabelled data an important goal. We show how a state-of-the-art CCG parser can be enhanced, by predicting lexical categories using unsupervised vector-space embeddings of words. The use of word embeddings enables our model to better generalize from the labelled data, and allows us to accurately assign lexical categories without depending on a POS-tagger. Our approach leads to substantial improvements in dependency parsing results over the standard supervised CCG parser when evaluated on Wall Street Journal (0.8{\%}), Wikipedia (1.8{\%}) and biomedical (3.4{\%}) text. We compare the performance of two recently proposed approaches for classification using a wide variety of word embeddings. We also give a detailed error analysis demonstrating where using embeddings outperforms traditional feature sets, and showing how including POS features can decrease accuracy. | ['Mike Lewis', 'Mark Steedman'] | 2014-01-01 | null | null | null | tacl-2014-1 | ['ccg-supertagging'] | ['natural-language-processing'] | [ 1.47300661e-01 7.75737524e-01 -2.86976218e-01 -6.55453205e-01
-9.44472253e-01 -7.79730737e-01 4.04003590e-01 7.67894745e-01
-8.36701155e-01 6.52919054e-01 4.58156973e-01 -6.59815192e-01
-1.46839404e-02 -7.77205169e-01 -4.67528343e-01 -4.79827285e-01
-1.37251884e-01 6.60668671e-01 5.14087915e-01 -9.99406800e-02
2.40113407e-01 3.23208660e-01 -1.29992485e+00 9.06136185e-02
5.86829603e-01 6.17905438e-01 4.54810143e-01 8.15798521e-01
-7.33742535e-01 3.36531490e-01 -5.76961517e-01 -5.77661932e-01
-2.62944728e-01 3.01788859e-02 -1.21356332e+00 -3.23371232e-01
2.09727094e-01 1.02972761e-01 1.18643470e-01 8.81789386e-01
4.67290729e-01 5.88084795e-02 7.52341866e-01 -6.04730964e-01
-9.43252504e-01 8.57104123e-01 3.27378660e-02 3.61456811e-01
5.34818292e-01 -4.17254269e-01 1.44757235e+00 -6.13946617e-01
9.36881363e-01 1.09093916e+00 7.40228832e-01 9.33061659e-01
-1.08277500e+00 -3.81782979e-01 2.10326791e-01 8.30445364e-02
-8.38248670e-01 -1.63292602e-01 3.22135538e-01 -3.43586236e-01
1.60019755e+00 7.39730522e-02 2.48001516e-01 1.04767084e+00
1.88871890e-01 3.89529139e-01 1.12817836e+00 -1.08379483e+00
2.31325492e-01 1.01018876e-01 8.48725498e-01 6.16451263e-01
5.86710095e-01 -5.95661998e-02 -2.94739038e-01 -2.16579601e-01
2.97071278e-01 -4.24430877e-01 4.39582951e-02 -2.51241833e-01
-8.61417830e-01 1.18156993e+00 3.78184989e-02 5.61348975e-01
-5.00215329e-02 6.83804750e-02 5.13359010e-01 1.03773504e-01
6.19336486e-01 6.21505201e-01 -1.01552510e+00 -4.63672310e-01
-5.29822409e-01 -1.66089177e-01 1.00303638e+00 1.16161382e+00
6.20747745e-01 -2.77682334e-01 2.91974008e-01 1.18427777e+00
4.68908370e-01 3.96877751e-02 8.59034479e-01 -8.06269050e-01
6.02501929e-01 4.46351826e-01 -9.03854594e-02 -4.14775640e-01
-8.40311944e-01 -4.53198627e-02 -1.86645225e-01 -1.56728327e-01
7.04111576e-01 -2.17093095e-01 -1.17508769e+00 1.62320125e+00
2.57253051e-01 -4.44371819e-01 2.92716712e-01 2.92715311e-01
9.40500855e-01 3.44893783e-01 6.84830427e-01 -1.66755214e-01
1.65725470e+00 -6.03181124e-01 -7.39463210e-01 -4.19452012e-01
1.25049424e+00 -7.18735278e-01 7.44234920e-01 1.35318026e-01
-6.67885840e-01 -4.06650394e-01 -9.32085395e-01 -2.97579557e-01
-7.91287780e-01 -2.50009954e-01 8.74150276e-01 1.10620940e+00
-1.07360828e+00 7.83898771e-01 -1.03837430e+00 -6.89884007e-01
3.50047976e-01 7.49059856e-01 -8.37935865e-01 -2.38333270e-01
-1.15067732e+00 1.14779627e+00 7.28708923e-01 -4.64968204e-01
1.16528049e-01 -4.73420560e-01 -1.30031347e+00 5.77455238e-02
-8.02223384e-02 -1.51859507e-01 1.19650698e+00 -2.08007187e-01
-1.25022137e+00 1.06288135e+00 -1.68758288e-01 -3.43356341e-01
-5.89932352e-02 -1.80818453e-01 -5.77855647e-01 1.89320713e-01
3.18080813e-01 7.11879194e-01 2.47752577e-01 -7.69835174e-01
-8.09159338e-01 -3.22122425e-01 -5.52450940e-02 -1.75207824e-01
-5.02616704e-01 2.03490257e-01 -1.11932330e-01 -4.68240857e-01
3.97678763e-01 -7.87959278e-01 -3.18639904e-01 -6.79392099e-01
-2.66038060e-01 -8.00018311e-01 3.69552165e-01 -8.50495398e-01
1.21445227e+00 -2.08699441e+00 -5.10010310e-02 -1.69618651e-01
1.22238897e-01 3.46507967e-01 -1.75134137e-01 6.30330622e-01
-3.66404951e-01 6.73473835e-01 -1.81069642e-01 -2.50424504e-01
1.41848087e-01 6.61125779e-01 1.66502371e-01 2.89483875e-01
5.30378520e-01 6.73274994e-01 -1.04571784e+00 -6.41328335e-01
1.64792314e-01 2.13216528e-01 -5.23377240e-01 -7.75957853e-03
8.28726590e-02 7.11091012e-02 -5.11095703e-01 4.63261724e-01
4.54902142e-01 2.33605087e-01 6.45196021e-01 2.74119467e-01
-1.48243517e-01 6.22567475e-01 -8.87312949e-01 1.55450237e+00
-6.27299011e-01 5.80704868e-01 -4.21328634e-01 -1.10786676e+00
1.06295228e+00 3.79256189e-01 1.05926119e-01 -3.38322490e-01
1.57953769e-01 3.81786913e-01 2.93282241e-01 -4.20767725e-01
4.53593194e-01 -3.59414101e-01 -6.02204859e-01 2.96173722e-01
7.94837594e-01 -2.47427598e-02 4.09913838e-01 -5.08574545e-02
1.53525412e+00 1.01409733e-01 4.74812865e-01 -6.05333149e-01
2.62534350e-01 2.41732955e-01 6.56043112e-01 6.96393967e-01
-2.69530922e-01 5.71600795e-01 8.44326138e-01 -5.40325046e-01
-8.84680092e-01 -9.61737514e-01 -5.88818014e-01 1.54823565e+00
-2.96029866e-01 -4.82931823e-01 -8.53159845e-01 -1.13067424e+00
-7.37543032e-02 1.01627231e+00 -8.67234945e-01 1.52670056e-01
-7.71920025e-01 -1.07257318e+00 4.88636971e-01 1.01967323e+00
-3.11703652e-01 -1.24604547e+00 -4.58817631e-01 6.04820371e-01
1.54054493e-01 -1.25971770e+00 4.80017848e-02 1.00991094e+00
-1.07627273e+00 -1.17419565e+00 -2.35628232e-01 -1.34847093e+00
5.19542456e-01 -4.14947778e-01 1.26966238e+00 1.88760888e-02
-2.64276773e-01 3.53548437e-01 -1.07138407e+00 -4.64736015e-01
-8.07143509e-01 3.66167456e-01 6.47754669e-02 -8.37273896e-01
1.07121527e+00 -3.00695300e-01 -5.96635696e-03 -1.40895098e-01
-7.20318675e-01 -4.72652376e-01 4.80787605e-01 1.12794864e+00
4.86622483e-01 -4.73973751e-01 6.58696949e-01 -1.61650121e+00
5.11036634e-01 -4.81197774e-01 -2.73141623e-01 2.14566201e-01
-5.72957873e-01 5.81081152e-01 7.44497955e-01 -3.55386198e-01
-8.28612626e-01 1.23573370e-01 -6.52311742e-01 4.58489835e-01
-5.14264107e-01 2.15103343e-01 -2.01684386e-01 2.09452972e-01
5.14964938e-01 -1.49910688e-01 -3.44232976e-01 -8.08595181e-01
6.63649738e-01 1.00126612e+00 3.39863092e-01 -5.08989573e-01
4.13692892e-01 -1.13218874e-01 -2.44747818e-01 -7.75652707e-01
-6.36739016e-01 -7.49178290e-01 -1.15679610e+00 4.83309180e-01
1.16958535e+00 -5.20508766e-01 -1.57995820e-02 -1.87706545e-01
-1.21730900e+00 -1.87255636e-01 -2.58340180e-01 7.06861258e-01
-4.93511617e-01 6.01676345e-01 -7.69590378e-01 -5.12304068e-01
-7.29074255e-02 -8.01986158e-01 8.39151025e-01 -1.07075535e-02
-5.73070884e-01 -1.35239625e+00 2.38422170e-01 2.41983578e-01
1.60458870e-02 -5.23483206e-04 1.27313149e+00 -1.38598955e+00
2.88461626e-01 -4.77784395e-01 -1.12488963e-01 4.03807491e-01
1.41475052e-01 -2.28112593e-01 -1.04146230e+00 8.53891522e-02
-3.35832596e-01 2.29711477e-02 9.23013806e-01 1.34521767e-01
8.59847009e-01 2.26658240e-01 -4.14144367e-01 3.40118021e-01
1.36542380e+00 2.94247538e-01 3.73298198e-01 6.45631671e-01
6.16774559e-01 6.61976397e-01 6.62264347e-01 5.37500232e-02
2.92513490e-01 2.03018665e-01 3.41385275e-01 3.29115689e-01
-1.32592604e-01 -5.00039719e-02 1.30931661e-01 1.21486795e+00
-1.18985377e-01 -2.43025526e-01 -9.63193297e-01 9.00290787e-01
-1.33937383e+00 -5.16214073e-01 -3.79705727e-01 1.94403112e+00
9.14327681e-01 2.87958711e-01 -1.88132077e-01 1.63383886e-01
8.00155163e-01 -2.61490438e-02 6.52211159e-02 -1.32239878e+00
2.39770412e-01 1.03445351e+00 8.74744952e-01 4.33765948e-01
-1.39145434e+00 1.16906762e+00 6.80006838e+00 5.82487404e-01
-5.60023487e-01 4.61819440e-01 2.67152280e-01 5.15604734e-01
-1.67895809e-01 -3.47567089e-02 -1.07565665e+00 4.85596955e-01
1.41813064e+00 6.52369782e-02 -2.29674786e-01 9.02581871e-01
-4.45724607e-01 -3.28793451e-02 -1.16159880e+00 4.97154355e-01
-3.25658545e-02 -1.13012433e+00 -4.29384887e-01 8.78442377e-02
3.05748641e-01 1.34552896e-01 -4.91510510e-01 6.71706617e-01
6.85219944e-01 -9.48867321e-01 3.26678604e-01 -1.29557729e-01
9.01613057e-01 -5.10530949e-01 1.21694601e+00 1.83499783e-01
-1.02845418e+00 4.48403582e-02 -8.19490433e-01 -1.36387020e-01
6.66474551e-02 4.58626300e-01 -8.51579726e-01 5.66736102e-01
7.98627019e-01 3.35719913e-01 -6.96580231e-01 6.59862101e-01
-6.04532659e-01 9.24316466e-01 -3.81609678e-01 -4.63860929e-01
2.35557988e-01 2.00549543e-01 1.21917583e-01 1.74121726e+00
1.13485418e-01 1.21239126e-01 -1.05103210e-01 -2.24881321e-02
-1.07760198e-01 4.26507354e-01 -4.64364529e-01 -1.77000850e-01
4.85136509e-01 1.06003761e+00 -9.81565714e-01 -3.61377060e-01
-6.93572819e-01 7.93927372e-01 8.07508409e-01 -1.86294794e-01
-4.27955896e-01 -8.04520190e-01 5.37869036e-01 -2.48987064e-01
6.88545048e-01 -1.91964164e-01 -2.98852891e-01 -8.31105053e-01
-3.82838808e-02 -1.72672212e-01 6.19418502e-01 -2.83842683e-01
-1.29960752e+00 8.32907259e-01 1.24401212e-01 -8.47422123e-01
-4.42381203e-01 -1.33376646e+00 -3.40032637e-01 8.53089273e-01
-1.47337091e+00 -8.41558099e-01 2.79783458e-01 -2.79199928e-01
4.68455732e-01 -2.02786580e-01 1.53074419e+00 -1.66987684e-02
-3.32594007e-01 7.02314377e-01 3.31611544e-01 4.79958683e-01
7.09119081e-01 -1.84396470e+00 6.75655723e-01 6.38777435e-01
3.33609074e-01 5.77705860e-01 6.10442460e-01 -3.53778273e-01
-1.01664388e+00 -1.02301526e+00 1.69517946e+00 -7.69930243e-01
9.69119608e-01 -4.52807337e-01 -8.84553730e-01 8.14122677e-01
1.42551363e-01 2.82110691e-01 1.19118333e+00 7.01911390e-01
-6.06253326e-01 3.31700265e-01 -1.26772261e+00 2.06319273e-01
1.16987967e+00 -2.41328403e-01 -1.28316236e+00 3.87122035e-01
7.86243796e-01 -1.88896775e-01 -1.19644880e+00 8.95326138e-02
4.89984810e-01 -6.87762797e-01 7.12800503e-01 -8.80139768e-01
3.97393525e-01 3.65227073e-01 -1.33755296e-01 -1.40587699e+00
-6.34194076e-01 -1.37082696e-01 1.47489011e-01 1.25976348e+00
6.16012156e-01 -9.48917925e-01 7.11005986e-01 5.93609929e-01
-4.60016847e-01 -5.12054861e-01 -1.11092091e+00 -8.25831592e-01
6.74911559e-01 -7.07787812e-01 4.54628259e-01 8.86725307e-01
5.02255440e-01 2.11241931e-01 3.09348106e-01 1.33194104e-01
2.94870436e-01 -1.88999236e-01 7.53707960e-02 -1.49667251e+00
-1.86237022e-01 -2.01521486e-01 -1.05718374e+00 -6.16805255e-01
3.08654279e-01 -1.02013886e+00 1.26548633e-01 -1.74766552e+00
-4.30714265e-02 -6.41467214e-01 -5.00923336e-01 7.46375263e-01
-3.76633257e-01 3.09200764e-01 1.60290629e-01 -2.66900361e-01
-4.09316033e-01 -5.16856164e-02 5.87428153e-01 1.55991152e-01
1.24198705e-01 -3.85977030e-01 -8.32602918e-01 7.93910146e-01
1.01177430e+00 -9.41667080e-01 7.47989714e-02 -6.59974754e-01
1.64195169e-02 -2.19402686e-01 -2.58390367e-01 -7.75222123e-01
-1.39981985e-01 1.40583470e-01 3.31498116e-01 -1.28668845e-01
1.40829682e-01 -3.64140570e-01 -5.10172367e-01 2.64227718e-01
-2.63835639e-01 1.22444965e-01 3.32835466e-01 6.53613925e-01
-1.24210499e-01 -1.03758061e+00 5.25941491e-01 -2.24371344e-01
-1.07502556e+00 -1.61451146e-01 -6.10953867e-01 3.41917932e-01
7.99956799e-01 -2.30877221e-01 -2.39281893e-01 2.73827285e-01
-1.24284291e+00 -7.14401761e-03 3.11909020e-01 4.24139440e-01
2.20825538e-01 -8.92197192e-01 -4.72308546e-01 2.39481717e-01
2.94369042e-01 -1.90390036e-01 -9.86920819e-02 2.96290785e-01
-8.65959227e-01 5.55292070e-01 -9.31285694e-02 -1.19024388e-01
-1.37832153e+00 5.08068442e-01 -3.38384211e-01 -5.20649672e-01
-5.20527959e-01 1.04470468e+00 -1.25986442e-01 -8.21631849e-01
3.24808508e-02 -5.92880309e-01 -7.14573979e-01 2.46930569e-01
3.14529270e-01 8.34563076e-02 2.68531591e-01 -6.77326918e-01
-6.82680726e-01 4.59818125e-01 -2.25174308e-01 8.28511268e-02
1.71717715e+00 3.13578278e-01 3.88405994e-02 2.62512356e-01
1.38189840e+00 9.87792164e-02 -5.52141428e-01 1.64320931e-01
6.00265443e-01 -4.98260371e-02 -1.20977275e-01 -7.18695283e-01
-4.35755551e-01 1.05960524e+00 5.58384538e-01 3.84456575e-01
7.63840497e-01 4.20779526e-01 6.56233966e-01 3.81865650e-01
5.33072591e-01 -1.26202464e+00 -5.86522341e-01 6.67594731e-01
9.25113186e-02 -1.26848340e+00 -2.67200265e-02 -9.00755227e-01
-4.11050200e-01 1.56951582e+00 8.12876970e-02 -3.14797759e-01
7.36899257e-01 2.11873263e-01 2.40026757e-01 -1.19137019e-02
-5.61791241e-01 -4.54896212e-01 -1.15325674e-01 1.02478933e+00
7.77175665e-01 3.95079076e-01 -8.99297833e-01 1.04103112e+00
-3.52351606e-01 -4.56639826e-01 7.44413853e-01 1.23174369e+00
-6.30827546e-01 -2.02400470e+00 -1.41181082e-01 6.60097241e-01
-9.53149796e-01 -2.35966578e-01 -9.83898416e-02 1.16535497e+00
2.47795656e-01 1.11566210e+00 1.24914177e-01 -1.52223960e-01
2.17170671e-01 6.74633920e-01 4.64024842e-01 -1.37239003e+00
-5.30611873e-01 -2.21254185e-01 5.75571179e-01 -2.80829668e-01
-4.32602674e-01 -8.04954886e-01 -1.40752983e+00 2.30692178e-01
-4.82288271e-01 4.61055815e-01 7.57768750e-01 9.96222556e-01
7.10774288e-02 5.06111979e-01 2.20029131e-01 -5.04818916e-01
-6.13638580e-01 -1.33204401e+00 -6.82155371e-01 4.95821357e-01
-2.60741502e-01 -7.34142542e-01 -4.99193579e-01 1.45861655e-01] | [10.318443298339844, 9.758899688720703] |
510c9b26-11fb-47c9-bdf7-72e9c985dc47 | functional-segmentation-through-dynamic-mode | 1905.10218 | null | https://arxiv.org/abs/1905.10218v1 | https://arxiv.org/pdf/1905.10218v1.pdf | Functional Segmentation through Dynamic Mode Decomposition: Automatic Quantification of Kidney Function in DCE-MRI Images | Quantification of kidney function in Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) requires careful segmentation of the renal region of interest (ROI). Traditionally, human experts are required to manually delineate the kidney ROI across multiple images in the dynamic sequence. This approach is costly, time-consuming and labour intensive, and therefore acts to limit patient throughout and acts as one of the factors limiting the wider adoption of DCR-MRI in clinical practice. Therefore, to address this issue, we present the first use of Dynamic Mode Decomposition (DMD) as a basis for automatic segmentation of a dynamic sequence, in this case, kidney ROIs in DCE-MRI. Using DMD coupled combined with thresholding and connected component analysis is first validated on synthetically generated data with known ground-truth, and then applied to ten healthy volunteers' DCE-MRI datasets. We find that the segmentation result obtained from our proposed DMD framework is comparable to that of expert observers and very significantly better than that of an a-priori bounding box segmentation. Our result gives a mean Jaccard coefficient of 0.87, compared to mean scores of 0.85, 0.88 and 0.87 produced from three independent manual annotations. This represents the first use of DMD as a robust automatic data-driven segmentation approach without requiring any human intervention. This is a viable, efficient alternative approach to current manual methods of isolation of kidney function in DCE-MRI. | ['Kevin Wells', 'Miroslaw Bober', 'Isky Gorden', 'Santosh Tirunagari', 'Norman Poh', 'David Windridge'] | 2019-05-24 | null | null | null | null | ['kidney-function'] | ['medical'] | [ 4.46518302e-01 1.46488860e-01 3.30732793e-01 -4.15331841e-01
-6.43106639e-01 -6.12371147e-01 3.56412649e-01 1.86209753e-01
-6.87686384e-01 6.39751256e-01 -2.55031642e-02 -3.26380581e-01
-4.21039730e-01 -5.63868821e-01 -2.86914170e-01 -8.89914274e-01
-4.60673004e-01 8.77850175e-01 3.76653731e-01 2.32803687e-01
1.50107518e-01 9.03430462e-01 -9.46134150e-01 -1.53679624e-01
1.05158925e+00 5.29614091e-01 5.31852663e-01 7.61290669e-01
9.62912850e-03 7.84886062e-01 -2.42914870e-01 -2.67329097e-01
4.08032417e-01 -7.18317211e-01 -9.13725436e-01 5.21506488e-01
4.54644442e-01 -4.10898030e-01 -1.06770350e-02 9.31942821e-01
6.19056106e-01 1.87549040e-01 6.91259980e-01 -5.09733796e-01
-3.12606633e-01 6.23516321e-01 -6.27600491e-01 5.31237662e-01
-6.86808601e-02 2.45137423e-01 8.38881135e-02 -5.95842898e-01
9.30225730e-01 5.93210757e-01 7.23005474e-01 5.11116147e-01
-1.63940942e+00 -4.51341152e-01 -4.06379282e-01 -2.00406626e-01
-1.32463109e+00 -3.21343631e-01 4.20230150e-01 -8.66244674e-01
5.77978671e-01 3.55820894e-01 7.46964037e-01 2.10752040e-01
2.62891769e-01 3.03681850e-01 1.71724033e+00 -4.88885283e-01
1.45423949e-01 -1.08488120e-01 -1.52463536e-03 5.63561380e-01
3.86005372e-01 -5.05048633e-02 5.03352046e-01 -2.39321902e-01
1.14939237e+00 -1.49420947e-01 -4.24722612e-01 -7.43056774e-01
-1.51063371e+00 5.60796201e-01 2.91954339e-01 6.93624377e-01
-7.57950187e-01 1.61713332e-01 4.51490492e-01 1.78214088e-02
1.61811203e-01 1.16297387e-01 1.34328857e-01 1.12324901e-01
-1.28303599e+00 1.40501067e-01 5.69840968e-01 4.86501753e-01
1.22996792e-02 -1.99578870e-02 2.73016677e-03 8.35124671e-01
3.48310143e-01 6.12681985e-01 4.85001624e-01 -1.03918016e+00
-1.52140871e-01 3.53927583e-01 -2.66841836e-02 -7.16460407e-01
-4.10610884e-01 -3.23904693e-01 -9.45609391e-01 4.62830216e-01
6.57980919e-01 5.23565076e-02 -1.37736535e+00 1.22569013e+00
5.47397614e-01 -1.00858122e-01 -2.16401011e-01 1.29649711e+00
4.49613094e-01 -1.57831274e-02 4.79935706e-01 -4.91026759e-01
1.32109272e+00 -5.60130179e-01 -7.11427152e-01 2.40494996e-01
5.06102562e-01 -7.61242688e-01 6.07679427e-01 2.87940472e-01
-1.13258469e+00 -9.97353494e-02 -8.74114990e-01 5.63813508e-01
1.00212775e-01 7.32370540e-02 6.15007341e-01 8.99463594e-01
-9.43173528e-01 6.72828376e-01 -1.19393075e+00 -2.60088742e-01
5.39048851e-01 4.63715672e-01 -6.09571278e-01 -2.11091131e-01
-7.29706347e-01 1.34566510e+00 1.34489685e-01 2.88084775e-01
-6.99205816e-01 -8.08759093e-01 -5.05139530e-01 -3.79026800e-01
1.04691915e-01 -4.13929045e-01 1.08371031e+00 -7.06569970e-01
-1.28210270e+00 1.31328511e+00 3.24707180e-02 -5.38007021e-01
1.08648252e+00 2.74378389e-01 -3.96258891e-01 7.25918412e-01
1.57541022e-01 3.83612126e-01 4.38040257e-01 -1.52992511e+00
-6.42245710e-02 -5.55216074e-01 -3.30537230e-01 3.36995125e-02
6.41679406e-01 3.57900530e-01 -2.71042168e-01 -5.39233029e-01
6.01086080e-01 -1.17022514e+00 -7.34849155e-01 1.50252134e-02
-1.11249045e-01 2.99667001e-01 3.37336153e-01 -1.12200224e+00
1.11717284e+00 -1.62858999e+00 -3.14070821e-01 6.88589811e-01
5.13140500e-01 1.97204933e-01 5.00033617e-01 -1.78844139e-01
-2.78009057e-01 1.59370638e-02 -8.82403255e-01 3.70943129e-01
-3.61999661e-01 1.52672976e-01 4.52325910e-01 1.07519686e+00
-2.54255354e-01 7.49254882e-01 -9.69510734e-01 -9.06000972e-01
4.99436766e-01 4.05493915e-01 -1.27632290e-01 -2.51942407e-02
4.72769916e-01 9.01630878e-01 -2.89774418e-01 5.95309436e-01
9.40334439e-01 -1.11001603e-01 5.73954046e-01 -1.54961139e-01
-2.35868126e-01 -3.57209414e-01 -1.22550631e+00 1.46035135e+00
-1.62196949e-01 3.26792449e-01 3.59917819e-01 -1.07428038e+00
8.47563446e-01 6.91778600e-01 1.04437470e+00 -8.63785267e-01
4.64164875e-02 4.70208794e-01 5.26004791e-01 -7.06899405e-01
-1.85220331e-01 -8.06837320e-01 2.68483162e-01 5.83701968e-01
-8.41085762e-02 -2.00594395e-01 4.57413822e-01 1.14310712e-01
9.63929296e-01 1.38908312e-01 2.98873216e-01 -7.41428912e-01
7.86858261e-01 2.97588021e-01 3.64677787e-01 5.82467437e-01
-6.87117994e-01 8.94534528e-01 2.36046880e-01 -3.45221847e-01
-1.18331468e+00 -1.13783038e+00 -7.66258895e-01 2.51212358e-01
-1.40226847e-02 4.43295509e-01 -9.03346896e-01 -5.73808074e-01
1.49571612e-01 3.77251953e-01 -6.06958330e-01 5.24620235e-01
-9.48091328e-01 -1.01736009e+00 5.34608841e-01 4.24670964e-01
2.69801378e-01 -8.76123011e-01 -9.76999104e-01 5.36657333e-01
-2.61867523e-01 -9.42253709e-01 -2.66842395e-01 1.50869980e-01
-1.42293024e+00 -1.22584665e+00 -1.36421204e+00 -6.41595721e-01
9.94309187e-01 -4.37846221e-02 1.17448163e+00 1.94256097e-01
-7.03130662e-01 3.79813313e-01 -6.16141520e-02 3.58816683e-02
-6.28991902e-01 -4.65163708e-01 -1.82455465e-01 -3.44308257e-01
1.01210840e-01 -7.23727822e-01 -1.01649177e+00 4.10052568e-01
-9.42749679e-01 -1.14152171e-01 7.41683722e-01 4.94778186e-01
7.93443084e-01 -2.80027926e-01 4.69607472e-01 -1.14385521e+00
5.20299911e-01 -2.54023254e-01 -6.87791169e-01 3.70275736e-01
-8.06178093e-01 -2.22627625e-01 2.23979905e-01 -3.98728013e-01
-1.12389636e+00 3.67726207e-01 1.30165026e-01 -3.80115092e-01
-2.02672318e-01 2.73759633e-01 4.97416943e-01 -4.67787057e-01
7.71007538e-01 1.68634474e-01 3.61467212e-01 -3.62768769e-01
1.98398158e-01 4.48259622e-01 8.43742251e-01 -5.17221034e-01
4.29411978e-01 7.33874917e-01 3.12652230e-01 -5.82848549e-01
-6.52382448e-02 -6.09896660e-01 -1.08522534e+00 -5.72529554e-01
9.83876705e-01 -5.28087854e-01 -5.38702250e-01 2.70736635e-01
-6.88633800e-01 -2.97328562e-01 -1.97404787e-01 8.69223654e-01
-5.77441037e-01 6.76761150e-01 -7.10732520e-01 -7.83695102e-01
-5.65435529e-01 -1.18504369e+00 4.27359819e-01 1.31348938e-01
-1.58493280e-01 -1.03720737e+00 1.84096530e-01 7.37462640e-01
7.76616514e-01 9.56085742e-01 7.71778762e-01 -5.01973033e-01
-4.31190461e-01 -3.77251506e-01 -2.22296819e-01 3.73429090e-01
2.43349764e-02 -1.76839605e-01 -6.15795672e-01 -5.95790967e-02
2.20241696e-01 1.09257117e-01 4.89513755e-01 8.29008102e-01
8.33174884e-01 1.69288799e-01 -1.07022747e-01 1.72621638e-01
1.85583711e+00 5.41629314e-01 7.20580876e-01 3.15452695e-01
4.32593882e-01 6.42879009e-01 5.30075788e-01 1.82652116e-01
2.39715740e-01 3.31592530e-01 6.59682900e-02 -3.65723640e-01
-1.82857588e-01 3.39258105e-01 -3.08257461e-01 8.29607308e-01
-6.33953154e-01 4.69112486e-01 -1.46119094e+00 8.90980065e-01
-1.41238439e+00 -9.15932715e-01 -6.82419896e-01 2.17043948e+00
7.25952923e-01 -7.44512081e-02 1.56110063e-01 -5.96422255e-02
1.00517583e+00 -2.70174831e-01 -2.33299553e-01 -4.07085270e-01
3.04868877e-01 4.72681671e-01 8.97252083e-01 4.48695958e-01
-1.03810418e+00 2.47267619e-01 6.68323708e+00 2.85761297e-01
-1.13352275e+00 3.37841600e-01 5.65301061e-01 1.68019101e-01
-8.90637655e-03 6.80474341e-02 3.87325175e-02 4.23629016e-01
7.53969431e-01 -3.11025441e-01 3.33869398e-01 5.17978728e-01
5.44401467e-01 -8.20638776e-01 -6.85445309e-01 6.00035012e-01
-1.28470048e-01 -1.05443752e+00 -4.80864197e-01 2.54905462e-01
7.36568332e-01 1.10557731e-02 -5.09292245e-01 -1.00064345e-01
3.83616276e-02 -1.20231771e+00 2.40706474e-01 7.77005076e-01
8.36143672e-01 -4.27008539e-01 7.61591911e-01 1.54872715e-01
-1.03336024e+00 5.34780383e-01 -5.93167543e-03 3.40663731e-01
3.63528132e-01 7.98752964e-01 -9.49245214e-01 3.45296502e-01
4.45368439e-01 -1.65141732e-01 -2.53354967e-01 1.27974558e+00
1.06274605e-01 4.15939927e-01 -2.73018450e-01 4.50845420e-01
5.74678220e-02 -4.99380410e-01 4.88327146e-01 1.47243321e+00
1.03523144e-02 3.44450742e-01 -2.22573150e-02 8.94588888e-01
3.39143187e-01 2.77869314e-01 -3.49125504e-01 9.66282189e-02
8.46808404e-02 1.43103802e+00 -1.38098884e+00 -6.28833950e-01
-3.18258792e-01 7.46071398e-01 -2.15993956e-01 1.45654500e-01
-7.90722370e-01 -1.62907377e-01 -1.97255105e-01 5.26727319e-01
1.33059517e-01 -1.22397974e-01 -4.09952253e-01 -8.55371475e-01
6.69054016e-02 -6.61393940e-01 3.67281556e-01 -5.40758729e-01
-1.12090218e+00 4.76716995e-01 2.74083316e-01 -1.10442412e+00
-7.36623034e-02 -2.24075526e-01 -5.60429990e-01 1.24958503e+00
-1.21805072e+00 -8.06981981e-01 -3.33737910e-01 2.86970884e-01
3.67321372e-02 4.90535080e-01 7.12756574e-01 6.04142010e-01
-1.50243908e-01 -5.97418472e-02 3.03278193e-02 3.08399469e-01
4.29100066e-01 -1.52846682e+00 -1.91349834e-01 9.42692459e-01
-6.70013964e-01 8.59964490e-01 5.66148400e-01 -8.33670139e-01
-1.00827014e+00 -7.20706820e-01 8.06500494e-01 -2.03438058e-01
4.46298271e-01 3.27578008e-01 -9.54124510e-01 4.64140028e-01
2.51722317e-02 5.74203610e-01 7.46033132e-01 -6.04811251e-01
5.33137739e-01 2.04622149e-01 -1.79018533e+00 1.43792346e-01
7.78042257e-01 -1.99976489e-01 -8.70301366e-01 1.49730355e-01
-1.14113398e-01 -7.06069767e-01 -1.73155010e+00 5.29229522e-01
7.87205100e-01 -9.88581955e-01 9.95025396e-01 -1.73227340e-01
3.48476291e-01 -4.83362168e-01 1.49108142e-01 -8.04697812e-01
-1.47894397e-01 -1.91110745e-01 2.56448478e-01 8.64527225e-01
1.84925213e-01 -4.25201356e-01 8.43795300e-01 1.03874600e+00
-4.75252792e-02 -7.19915748e-01 -9.40649450e-01 -6.41673684e-01
2.18750015e-01 -1.55356273e-01 2.69033499e-02 1.33869410e+00
-1.39163181e-01 -4.76502210e-01 1.44015342e-01 3.03592011e-02
1.26488090e+00 2.08335429e-01 4.31314230e-01 -1.28017282e+00
9.36709717e-02 -3.21249038e-01 -5.16093314e-01 -3.92459124e-01
-3.68404746e-01 -1.07377625e+00 2.77863275e-02 -1.91747963e+00
4.42409158e-01 -7.70010173e-01 -1.66317552e-01 6.58598989e-02
1.89264938e-02 5.03882289e-01 1.45219252e-01 5.11804760e-01
-1.64730757e-01 -9.17711928e-02 1.89824820e+00 2.19224617e-01
-3.62370536e-02 -4.47325557e-02 -3.46093893e-01 5.80117404e-01
6.86473906e-01 -6.80198669e-01 -1.28088281e-01 2.43648782e-01
-4.16020304e-01 3.51976722e-01 3.84280115e-01 -9.30914998e-01
2.02659130e-01 -1.23597413e-01 6.56885862e-01 -4.48120385e-01
-3.15864027e-01 -1.04778361e+00 5.95866442e-01 1.01937294e+00
-7.21020028e-02 -2.42652465e-02 -6.58684000e-02 2.08625555e-01
-1.29150927e-01 -4.85040963e-01 1.21306455e+00 -9.12768185e-01
-4.89522159e-01 -2.46671326e-02 -5.41689754e-01 7.73833916e-02
1.11356795e+00 -5.95530927e-01 1.67009458e-01 8.75247642e-02
-1.33251309e+00 2.29813740e-01 4.21112418e-01 -2.68999577e-01
4.11959618e-01 -1.09438550e+00 -7.25034475e-01 -1.64231151e-01
-2.07294598e-01 7.86042213e-02 6.08546317e-01 1.80154049e+00
-1.26742303e+00 3.83599043e-01 -3.44750971e-01 -1.04457200e+00
-1.26924694e+00 3.31566095e-01 8.10342669e-01 -5.11575758e-01
-1.17149282e+00 2.88110346e-01 -2.00044051e-01 -4.64645743e-01
-1.27285659e-01 -3.74188215e-01 -1.06217645e-01 -1.06557153e-01
1.65122434e-01 4.98415411e-01 1.76631331e-01 -8.90350878e-01
-5.44749379e-01 5.83226740e-01 1.25273243e-01 -3.03075522e-01
1.23894536e+00 -2.67635614e-01 -2.87986428e-01 7.26347864e-02
8.83658767e-01 6.87489137e-02 -9.52815175e-01 2.52385158e-02
2.92096555e-01 -5.25045276e-01 2.67951995e-01 -9.99214411e-01
-1.08160937e+00 4.77130860e-01 1.08192849e+00 1.78689823e-01
1.01406121e+00 -2.33120427e-01 4.99213874e-01 -1.95850208e-01
2.73649544e-01 -1.09808350e+00 -5.67134202e-01 -1.56078398e-01
7.69692838e-01 -1.16963398e+00 3.50013047e-01 -4.93799567e-01
-9.15985227e-01 1.10957003e+00 3.02961081e-01 -2.18087539e-01
5.02886653e-01 4.52133805e-01 5.01884520e-01 -4.91106510e-01
-1.15333453e-01 -1.78725466e-01 2.21193165e-01 6.51019990e-01
8.01473081e-01 2.08829865e-01 -9.79261875e-01 5.43344878e-02
2.47120604e-01 4.18300509e-01 5.32798767e-01 1.28690159e+00
-4.52497840e-01 -8.78875852e-01 -5.69755852e-01 5.96933842e-01
-9.16898847e-01 2.20814377e-01 3.93988900e-02 1.08983314e+00
1.13973968e-01 4.59769547e-01 -2.36025557e-01 4.16157752e-01
4.25659984e-01 1.16457760e-01 8.71524155e-01 -2.57948965e-01
-8.04491639e-01 3.33401531e-01 -2.89362594e-02 -2.75611103e-01
-9.54800785e-01 -6.91686571e-01 -1.63010335e+00 -1.15487486e-01
-3.01964611e-01 7.71561731e-03 8.92304659e-01 7.39372730e-01
-2.49762073e-01 4.74673063e-01 5.75791657e-01 -6.72472477e-01
-4.15146381e-01 -8.64001632e-01 -6.82522178e-01 6.92404628e-01
-3.11741084e-02 -5.09275198e-01 -3.79392922e-01 3.25942993e-01] | [14.052169799804688, -2.4981682300567627] |
8ffae3cc-05d6-428a-99e7-0e0061d968fe | improving-lidar-3d-object-detection-via-range | 2306.05663 | null | https://arxiv.org/abs/2306.05663v1 | https://arxiv.org/pdf/2306.05663v1.pdf | Improving LiDAR 3D Object Detection via Range-based Point Cloud Density Optimization | In recent years, much progress has been made in LiDAR-based 3D object detection mainly due to advances in detector architecture designs and availability of large-scale LiDAR datasets. Existing 3D object detectors tend to perform well on the point cloud regions closer to the LiDAR sensor as opposed to on regions that are farther away. In this paper, we investigate this problem from the data perspective instead of detector architecture design. We observe that there is a learning bias in detection models towards the dense objects near the sensor and show that the detection performance can be improved by simply manipulating the input point cloud density at different distance ranges without modifying the detector architecture and without data augmentation. We propose a model-free point cloud density adjustment pre-processing mechanism that uses iterative MCMC optimization to estimate optimal parameters for altering the point density at different distance ranges. We conduct experiments using four state-of-the-art LiDAR 3D object detectors on two public LiDAR datasets, namely Waymo and ONCE. Our results demonstrate that our range-based point cloud density manipulation technique can improve the performance of the existing detectors, which in turn could potentially inspire future detector designs. | ['Bingbing Liu', 'Mrigank Rochan', 'Yannis Y. He', 'Alaap Grandhi', 'Eduardo R. Corral-Soto'] | 2023-06-09 | null | null | null | null | ['3d-object-detection'] | ['computer-vision'] | [-1.77612111e-01 -3.62710178e-01 -1.00327075e-01 -4.13100541e-01
-5.55399835e-01 -5.64918041e-01 3.92163604e-01 4.48320895e-01
-7.05434859e-01 5.98195083e-02 -2.66449481e-01 -4.29681391e-01
1.39318824e-01 -1.03173804e+00 -5.88888407e-01 -3.22442919e-01
-5.49882241e-02 1.11888480e+00 1.01707542e+00 9.48745310e-02
4.37798470e-01 1.24883699e+00 -1.81957638e+00 -4.66715842e-01
7.40523934e-01 6.52613699e-01 3.25904578e-01 6.28549397e-01
-3.68597537e-01 -2.14476302e-01 -4.67262566e-01 -1.11018606e-02
6.85636699e-01 5.04684567e-01 9.18626487e-02 -1.22142464e-01
7.15545416e-01 -6.26602292e-01 -2.85158977e-02 9.29987848e-01
6.41536534e-01 -9.30954441e-02 7.39804327e-01 -1.30118144e+00
-3.42582822e-01 2.42862269e-01 -1.13364089e+00 3.17633927e-01
-1.42061472e-01 3.83136481e-01 6.97866321e-01 -1.12544429e+00
2.20629871e-01 1.61139810e+00 7.55198896e-01 2.26106882e-01
-1.39746559e+00 -9.40187633e-01 2.57072687e-01 -1.65953219e-01
-1.96972394e+00 -1.35010108e-01 7.07376957e-01 -6.07461751e-01
1.15777946e+00 -6.28159642e-02 5.49323142e-01 3.80152911e-01
-8.46578740e-03 4.14053589e-01 5.73075354e-01 -3.08455884e-01
3.20400506e-01 8.80086124e-02 -9.84768867e-02 4.31894749e-01
8.54892969e-01 2.93669581e-01 -3.58598143e-01 -2.52205878e-01
8.15431118e-01 2.55679209e-02 4.10769790e-01 -1.01127040e+00
-9.80578899e-01 9.68640029e-01 7.22971737e-01 -1.33827105e-01
-1.57975763e-01 2.15725079e-01 1.06588289e-01 -1.60431772e-01
5.52563488e-01 2.61289418e-01 -3.65050524e-01 2.51720026e-02
-8.31327498e-01 6.17201865e-01 3.92142266e-01 1.20451963e+00
1.01790106e+00 -2.38352329e-01 4.83867563e-02 5.47963500e-01
7.01456726e-01 1.07366920e+00 -3.39877099e-01 -8.02596927e-01
6.91700578e-01 1.00713706e+00 2.06004128e-01 -7.23148286e-01
-3.48159045e-01 -9.13551077e-02 -3.67048293e-01 6.25782669e-01
3.02275300e-01 8.22401047e-02 -1.15040374e+00 1.19021678e+00
8.10051382e-01 1.56471163e-01 -4.16606009e-01 1.00983334e+00
5.02528369e-01 4.83445555e-01 8.31153616e-02 3.99132937e-01
1.24201012e+00 -7.71956518e-02 -5.65611683e-02 -5.27276814e-01
7.47442663e-01 -7.69861042e-01 1.01103401e+00 -4.63959016e-02
-7.61442780e-01 -5.08747220e-01 -1.23383105e+00 -2.24932209e-01
-3.82631063e-01 4.63989738e-04 4.58254427e-01 7.91259289e-01
-7.62514055e-01 1.47583008e-01 -1.04723167e+00 -5.23712397e-01
6.55655921e-01 5.57514846e-01 2.12501556e-01 -5.40711842e-02
-4.41789538e-01 1.03260458e+00 4.55507904e-01 -2.10354447e-01
-4.83953297e-01 -1.06777632e+00 -6.24089718e-01 3.79431644e-03
5.21122992e-01 -7.72028327e-01 1.24229479e+00 2.64471173e-01
-9.40475464e-01 1.02397525e+00 -1.96184460e-02 -3.64519954e-01
5.06338477e-01 -2.94222534e-01 1.92381870e-02 -2.43064508e-01
2.54492342e-01 1.17401254e+00 6.89345539e-01 -1.27827322e+00
-1.01817393e+00 -8.07999134e-01 -2.92624444e-01 2.04584524e-01
3.75816412e-02 -2.14866951e-01 -5.51431596e-01 -7.72247016e-02
4.06975567e-01 -1.00638080e+00 -3.57026964e-01 4.96656984e-01
-1.69052958e-01 -3.79920632e-01 1.29694247e+00 3.49421561e-01
8.74297023e-01 -2.10153985e+00 -1.89599067e-01 3.03919673e-01
1.90709472e-01 2.91349649e-01 5.71885332e-03 2.76722550e-01
3.68480951e-01 2.31427416e-01 -7.42148012e-02 -3.20837736e-01
-8.64425153e-02 3.45932841e-01 -2.89868951e-01 4.60148901e-01
4.76123989e-01 6.77138686e-01 -8.81063521e-01 -6.17537856e-01
7.60616839e-01 5.69868565e-01 -7.10972011e-01 3.95927653e-02
-3.13009977e-01 1.59362599e-01 -5.92008770e-01 9.32580113e-01
1.32654583e+00 1.00713141e-01 -3.37552249e-01 -1.42212184e-02
-6.18307829e-01 2.53935874e-01 -1.36644244e+00 1.51446974e+00
-1.96560606e-01 3.72778773e-01 1.61152557e-01 -2.93044776e-01
1.24469304e+00 -4.23400700e-01 5.03479183e-01 -3.52784365e-01
4.11753058e-02 1.90982953e-01 8.13326091e-02 -1.63074173e-02
6.99863255e-01 -2.40184665e-01 2.75534578e-02 3.15156579e-01
-5.60602248e-01 -8.38715672e-01 1.44803207e-02 1.07009202e-01
9.00959611e-01 -3.38033997e-02 2.35110432e-01 -1.70305118e-01
1.56967610e-01 3.08262199e-01 2.85272866e-01 9.54636037e-01
-1.53015196e-01 4.51341510e-01 -3.28717269e-02 -1.69825837e-01
-1.12038624e+00 -1.60245204e+00 -6.53809249e-01 6.96188033e-01
4.03383225e-01 -3.26915354e-01 -2.64126658e-01 -4.78653222e-01
8.74028563e-01 6.85217619e-01 -1.55552313e-01 -1.51538849e-01
-5.50297439e-01 -4.66554344e-01 3.67326170e-01 6.94553733e-01
3.18825424e-01 -5.32529414e-01 -9.29800749e-01 1.67008992e-02
5.47026873e-01 -1.05686188e+00 -1.64727300e-01 2.23187193e-01
-1.37591529e+00 -7.38265634e-01 -2.00003505e-01 -3.01172167e-01
6.54864371e-01 9.19978738e-01 1.02265322e+00 1.21081360e-01
-3.90760779e-01 2.67804176e-01 -2.79828578e-01 -1.16196215e+00
-2.02825978e-01 5.25074720e-01 2.51124889e-01 -7.44680583e-01
1.05623341e+00 -5.68078518e-01 -5.16061664e-01 4.15523261e-01
-7.31266379e-01 -2.59134650e-01 6.82478666e-01 1.29718795e-01
6.80406690e-01 -9.83502418e-02 1.57801935e-03 -5.40998995e-01
3.12375218e-01 -4.41739738e-01 -1.27861035e+00 -3.14667404e-01
-7.00533390e-01 2.41319492e-01 -1.22731864e-01 -4.56809998e-01
-4.80271101e-01 4.04392749e-01 8.94679725e-02 -7.78134823e-01
-1.85604930e-01 3.70160524e-05 -2.58731931e-01 -9.83918980e-02
7.91253924e-01 -3.16489071e-01 -1.20706685e-01 -6.41719162e-01
4.35936570e-01 7.31510043e-01 2.84201503e-01 -7.31147587e-01
1.31422663e+00 8.41123998e-01 2.60755628e-01 -9.74369109e-01
-6.24771893e-01 -8.42067659e-01 -9.72073317e-01 -2.44371802e-01
6.60998166e-01 -1.07505846e+00 -7.57214665e-01 1.72946617e-01
-1.09494901e+00 -3.65420952e-02 -3.92452508e-01 4.68150854e-01
-9.12333056e-02 5.40358201e-02 7.01033771e-02 -1.06252027e+00
-1.06112778e-01 -1.03341818e+00 1.68461049e+00 1.46264166e-01
1.49483318e-02 -4.79728490e-01 2.14022279e-01 -1.02649473e-01
7.04734400e-02 1.54134668e-02 8.34977448e-01 -1.23396240e-01
-1.27033591e+00 -4.10194665e-01 -5.26939690e-01 -1.15824223e-01
1.17896631e-01 2.64390320e-01 -9.55455184e-01 -2.85310775e-01
-3.17646295e-01 2.10027650e-01 8.40398729e-01 4.92694855e-01
9.09855664e-01 4.93568689e-01 -8.41819525e-01 5.75430095e-01
1.43288922e+00 -2.05444917e-02 4.52160388e-01 2.94434667e-01
7.17349291e-01 3.09503555e-01 8.62366498e-01 4.18928981e-01
4.54021841e-01 8.90418231e-01 7.34823108e-01 2.84465719e-02
7.08066567e-04 -6.03462934e-01 -1.34177819e-01 1.94471553e-01
1.29098997e-01 -2.30503622e-02 -1.29075074e+00 5.79448581e-01
-1.77631259e+00 -6.81150079e-01 -3.41417819e-01 2.40095115e+00
3.74833286e-01 5.00465870e-01 4.28420216e-01 -1.03492118e-01
6.67164803e-01 -5.61161302e-02 -8.83727372e-01 -9.43401083e-02
3.08779657e-01 2.25524873e-01 1.10662377e+00 5.95554113e-01
-9.55001295e-01 1.10054350e+00 6.58450794e+00 4.39183891e-01
-9.17409420e-01 -8.06342810e-02 -1.29949138e-01 -5.29853940e-01
1.11921411e-02 1.88645750e-01 -1.52740324e+00 3.66534591e-01
6.69467151e-01 -7.39367828e-02 2.87263785e-02 1.16685259e+00
4.03563976e-01 -4.22340602e-01 -1.08511305e+00 9.72292900e-01
-4.71962482e-01 -1.18489170e+00 2.86073331e-02 6.03541195e-01
2.53234476e-01 5.16856909e-01 -1.03693292e-01 2.70185292e-01
4.64428484e-01 -6.03330791e-01 7.40564287e-01 1.37254894e-01
6.59086406e-01 -8.95569265e-01 3.40113938e-01 7.49405503e-01
-1.54008913e+00 2.50188429e-02 -8.29536080e-01 -1.59149334e-01
2.15862945e-01 8.10450196e-01 -1.44670880e+00 -8.34414661e-02
9.35706019e-01 4.14755374e-01 -7.91966736e-01 1.18702185e+00
-1.34165138e-01 2.23470420e-01 -1.07316542e+00 -2.67328233e-01
-2.10946742e-02 -2.13181674e-01 8.07064950e-01 1.10554242e+00
4.54554737e-01 -1.71958227e-02 3.17709267e-01 1.15092719e+00
1.53065724e-02 -2.31598213e-01 -9.84968364e-01 3.73484641e-01
1.18156826e+00 1.17267704e+00 -7.75929093e-01 -1.56519804e-02
-2.86720008e-01 1.04270436e-01 3.69440526e-01 -1.27766430e-01
-7.53009856e-01 -8.92119184e-02 1.04069757e+00 8.30994129e-01
6.75911367e-01 -7.93874383e-01 -5.38075089e-01 -7.78342009e-01
6.41491190e-02 -1.35345042e-01 1.83743194e-01 -6.89278841e-01
-1.22864437e+00 -1.58211067e-01 5.84303141e-01 -1.29536414e+00
4.55748066e-02 -6.29625678e-01 -4.29532528e-01 8.48682821e-01
-1.54430187e+00 -1.02878797e+00 -2.46768564e-01 1.45645082e-01
3.61679137e-01 1.75281301e-01 2.74014711e-01 3.90994817e-01
-1.49903357e-01 2.09260672e-01 -1.64426267e-01 -7.81426877e-02
5.44034004e-01 -1.09300828e+00 7.75155365e-01 7.97458827e-01
1.51062056e-01 5.55509508e-01 6.19915485e-01 -9.93431568e-01
-1.46275330e+00 -1.06445539e+00 4.85064864e-01 -8.79255056e-01
5.15744686e-01 -8.72209072e-01 -8.38767409e-01 5.29318333e-01
-4.95274156e-01 6.84931176e-03 3.33528548e-01 3.28641027e-01
-2.62313753e-01 -2.27884620e-01 -1.37725067e+00 4.36353773e-01
1.31578958e+00 -2.64786512e-01 -4.34821963e-01 1.78878650e-01
6.65496051e-01 -5.06595254e-01 -5.51613748e-01 6.96131885e-01
4.55041021e-01 -8.10736299e-01 1.44587374e+00 -2.95039952e-01
-2.58673012e-01 -8.07920933e-01 -3.34797829e-01 -1.00270081e+00
-3.18624735e-01 -2.17455979e-02 -2.92272598e-01 1.16804433e+00
1.79521471e-01 -4.71055090e-01 1.20027053e+00 4.79746908e-01
-1.08891711e-01 -2.65631229e-01 -1.21739185e+00 -1.00877774e+00
1.20286249e-01 -7.06975162e-01 8.35872531e-01 3.21715117e-01
-6.96661592e-01 5.27960062e-01 3.16307932e-01 7.03071654e-01
8.41774046e-01 1.19736753e-01 1.37162364e+00 -1.73128605e+00
1.94303051e-01 -5.32100439e-01 -6.99079275e-01 -1.35596907e+00
-2.13688001e-01 -7.97391653e-01 1.16974078e-01 -1.34076679e+00
-1.89189781e-02 -9.23362195e-01 3.24516058e-01 2.06272513e-01
-2.62493938e-01 6.62150905e-02 3.43198746e-01 4.30908799e-01
-1.19473025e-01 4.61071312e-01 9.29750681e-01 -3.78625505e-02
-4.60718185e-01 1.40033707e-01 -4.70081329e-01 7.77552068e-01
6.14149690e-01 -8.80695522e-01 -2.40985632e-01 -7.88010597e-01
5.51594384e-02 -6.86176777e-01 4.26785707e-01 -1.24042761e+00
2.10824564e-01 -2.31769457e-01 4.93614972e-01 -1.59719336e+00
6.62127018e-01 -1.08128262e+00 -1.01305917e-01 4.91731852e-01
3.16703051e-01 2.24020973e-01 4.97558266e-01 5.38295865e-01
5.08007467e-01 -2.19300494e-01 1.02746832e+00 2.82307249e-02
-6.29852176e-01 3.60266477e-01 -1.72732607e-01 -2.49565393e-01
1.13396871e+00 -4.89585042e-01 -8.55067894e-02 1.00837424e-01
-1.65750101e-01 4.70275283e-01 8.67801130e-01 4.97171372e-01
6.34701192e-01 -1.30943537e+00 -6.99485898e-01 3.39520067e-01
4.87646133e-01 6.18351042e-01 -3.59043688e-01 3.84365410e-01
-5.32835662e-01 3.25371802e-01 2.51709968e-01 -1.49853861e+00
-1.30258918e+00 5.68046153e-01 1.53837293e-01 1.48433223e-01
-7.38635480e-01 7.43377149e-01 -1.71245158e-01 -6.89631701e-01
1.27147138e-01 -7.76823997e-01 4.53223139e-01 -4.44336534e-02
2.75051892e-01 3.98513794e-01 8.51842389e-02 -4.04943138e-01
-6.28213465e-01 9.35606837e-01 -1.38252825e-01 -2.73803826e-02
1.15516925e+00 -1.56582631e-02 4.35306817e-01 4.68178183e-01
6.57196283e-01 5.43939583e-02 -1.34150016e+00 -1.58434346e-01
1.83621690e-01 -1.09417224e+00 3.82112056e-01 -3.07610452e-01
-8.40335369e-01 9.60935116e-01 1.07349694e+00 2.03207344e-01
5.03517151e-01 4.84874099e-01 4.65373129e-01 4.76048917e-01
6.01479292e-01 -1.00639236e+00 -1.92842722e-01 4.59722966e-01
4.39891309e-01 -1.42658126e+00 5.78807116e-01 -5.07124841e-01
-1.75183743e-01 7.85489559e-01 7.55187809e-01 -2.75076509e-01
7.40595520e-01 6.18227839e-01 -5.70126064e-02 -4.96237725e-01
-3.37387562e-01 -5.45340955e-01 1.05448358e-01 8.99819434e-01
1.10253789e-01 1.47584677e-01 2.71734685e-01 -3.30567151e-01
-1.90299183e-01 -1.54483795e-01 5.60345985e-02 1.22113574e+00
-1.12277079e+00 -1.20112395e+00 -9.12639022e-01 6.52438223e-01
3.88360083e-01 1.63531974e-01 -4.89941150e-01 1.11289430e+00
2.24899203e-01 7.12118447e-01 5.90891004e-01 -2.11277246e-01
7.56076217e-01 -1.09494895e-01 6.81874752e-01 -1.09990704e+00
-9.16170776e-02 2.94857565e-02 -2.88423091e-01 -3.44135940e-01
-2.12313190e-01 -9.79295313e-01 -1.40610957e+00 -5.50563991e-01
-6.61141455e-01 -2.41626501e-01 1.03277230e+00 5.49579740e-01
5.81634104e-01 5.13965636e-02 4.18660939e-01 -1.27828169e+00
-6.61349475e-01 -8.20426762e-01 -4.51315016e-01 -1.71741545e-01
9.46117043e-02 -1.15268469e+00 -3.10009390e-01 -4.83618349e-01] | [7.754235744476318, -2.6837055683135986] |
8965cc50-5731-49b1-995a-d0c4044b6e91 | one-shot-segmentation-in-clutter | 1803.09597 | null | http://arxiv.org/abs/1803.09597v2 | http://arxiv.org/pdf/1803.09597v2.pdf | One-Shot Segmentation in Clutter | We tackle the problem of one-shot segmentation: finding and segmenting a
previously unseen object in a cluttered scene based on a single instruction
example. We propose a novel dataset, which we call $\textit{cluttered
Omniglot}$. Using a baseline architecture combining a Siamese embedding for
detection with a U-net for segmentation we show that increasing levels of
clutter make the task progressively harder. Using oracle models with access to
various amounts of ground-truth information, we evaluate different aspects of
the problem and show that in this kind of visual search task, detection and
segmentation are two intertwined problems, the solution to each of which helps
solving the other. We therefore introduce $\textit{MaskNet}$, an improved model
that attends to multiple candidate locations, generates segmentation proposals
to mask out background clutter and selects among the segmented objects. Our
findings suggest that such image recognition models based on an iterative
refinement of object detection and foreground segmentation may provide a way to
deal with highly cluttered scenes. | ['Claudio Michaelis', 'Matthias Bethge', 'Alexander S. Ecker'] | 2018-03-26 | one-shot-segmentation-in-clutter-1 | https://icml.cc/Conferences/2018/Schedule?showEvent=2303 | http://proceedings.mlr.press/v80/michaelis18a/michaelis18a.pdf | icml-2018-7 | ['one-shot-segmentation', 'foreground-segmentation'] | ['computer-vision', 'computer-vision'] | [ 7.02766657e-01 1.37212604e-01 -5.17436489e-02 -4.26958799e-01
-8.49651694e-01 -7.62509346e-01 1.99211046e-01 1.51893213e-01
-7.14498937e-01 4.64252681e-01 -3.58112723e-01 -6.12861097e-01
-1.54821062e-02 -3.11910540e-01 -9.40471172e-01 -6.41013324e-01
-4.22352590e-02 7.09937811e-01 8.23443890e-01 2.83406768e-02
5.40043294e-01 4.71233279e-01 -1.60563505e+00 1.74842805e-01
8.28104436e-01 8.69503498e-01 5.92187881e-01 1.07646108e+00
-2.87650436e-01 6.07597709e-01 -9.07069385e-01 -2.64248669e-01
5.56764483e-01 -2.48719946e-01 -9.78205144e-01 6.55802190e-01
8.62416267e-01 -2.50706732e-01 -1.05453342e-01 1.32688117e+00
1.62549093e-01 3.89396191e-01 5.08063138e-01 -1.24298918e+00
-1.89715669e-01 5.88101208e-01 -8.00806642e-01 8.65389168e-01
9.37008485e-02 5.61256468e-01 1.02872193e+00 -8.16090584e-01
7.44400084e-01 1.12626016e+00 2.30483949e-01 4.21582907e-01
-1.52506268e+00 -2.21217364e-01 7.37281919e-01 1.37372324e-02
-1.24972844e+00 -3.32446694e-01 5.00670791e-01 -5.40352046e-01
8.11510146e-01 4.54536825e-01 5.86722255e-01 6.68379962e-01
8.28922465e-02 1.36966705e+00 9.44485605e-01 -4.87926573e-01
4.12717909e-01 1.45053044e-01 6.81824028e-01 9.47687387e-01
5.46917498e-01 -5.46636023e-02 -4.07546192e-01 1.92585737e-01
8.87276709e-01 -1.32352412e-01 -2.94212937e-01 -9.85100508e-01
-1.26194930e+00 6.69460773e-01 3.89010638e-01 3.41777444e-01
-1.18797004e-01 3.01977247e-01 1.69485193e-02 1.38109103e-01
1.40135244e-01 7.86323488e-01 -4.01995867e-01 4.01185686e-03
-1.31471264e+00 4.40474562e-02 8.99492323e-01 1.22705317e+00
9.30839717e-01 1.73306227e-01 -2.35604718e-01 3.16628367e-01
1.67383835e-01 2.60007679e-01 1.37102166e-02 -1.07728910e+00
3.78623962e-01 5.24076939e-01 2.88197786e-01 -6.47430301e-01
-3.40803802e-01 -5.07460475e-01 -2.71992888e-02 3.21234226e-01
8.57319891e-01 -2.71923184e-01 -1.52370477e+00 1.60359120e+00
4.16793793e-01 2.35876948e-01 -1.77469194e-01 9.02947545e-01
3.36059570e-01 4.48730469e-01 7.66061470e-02 3.65689583e-02
1.36800480e+00 -1.31282532e+00 -5.76024234e-01 -7.72109032e-01
5.17921865e-01 -6.76480174e-01 1.02044117e+00 5.76249540e-01
-1.20863521e+00 -6.02489769e-01 -1.32304978e+00 -7.34378472e-02
-6.14077508e-01 4.88815596e-03 5.81542432e-01 6.83546126e-01
-1.24615347e+00 5.05265176e-01 -9.82157588e-01 -3.73298913e-01
5.60003102e-01 6.04838014e-01 1.75307155e-01 -2.51466721e-01
-4.63620067e-01 7.97299981e-01 5.95814347e-01 1.73089281e-01
-1.30405319e+00 -2.29197130e-01 -9.00680244e-01 1.30031928e-01
1.07426834e+00 -3.04997444e-01 1.30669975e+00 -1.11539268e+00
-9.10680354e-01 8.87247324e-01 -1.16186239e-01 -3.17199856e-01
4.08738196e-01 -2.02772260e-01 -3.94678712e-02 3.50230664e-01
3.24748635e-01 8.42986405e-01 1.08787584e+00 -1.56843972e+00
-7.96740830e-01 -4.41638559e-01 8.53630889e-04 1.74280450e-01
2.99873739e-01 2.59608272e-02 -8.90090168e-01 -4.92189944e-01
2.33150214e-01 -7.02523828e-01 -6.93522632e-01 -1.12492897e-01
-5.88574469e-01 -8.39687660e-02 8.64535511e-01 -3.71886700e-01
1.17625701e+00 -2.19389987e+00 3.04250300e-01 3.69099051e-01
4.56203848e-01 1.62654966e-01 -2.77311802e-01 -4.03872617e-02
1.02734990e-01 1.49968848e-01 -3.48040462e-01 -2.27412507e-01
2.81976946e-02 3.82652253e-01 1.49786379e-02 5.17730892e-01
4.50714409e-01 9.35655057e-01 -1.10412860e+00 -7.06356525e-01
4.25765403e-02 -7.82620758e-02 -5.37068665e-01 1.62407145e-01
-6.28976166e-01 1.32560596e-01 -4.80756700e-01 8.46990287e-01
5.17491460e-01 -4.42742676e-01 9.17953849e-02 2.41331160e-01
-2.04507351e-01 -3.62215310e-01 -1.57648349e+00 1.80638421e+00
3.32752049e-01 6.87555850e-01 6.49861455e-01 -9.76749599e-01
5.83368421e-01 -2.72493571e-01 2.49117896e-01 -4.59822685e-01
3.12803417e-01 1.77390918e-01 1.72685102e-01 -5.73636234e-01
7.77419448e-01 1.86900556e-01 -1.62716776e-01 4.60177809e-01
3.36631238e-01 -2.88033843e-01 5.01836836e-01 4.63128418e-01
1.35857260e+00 2.61875927e-01 4.51684706e-02 -4.98091251e-01
6.92440942e-02 5.70672214e-01 3.23164105e-01 1.50002277e+00
-6.87015533e-01 4.84360993e-01 5.64579368e-01 -4.32725757e-01
-8.37426305e-01 -1.20763266e+00 1.44932240e-01 1.45444322e+00
6.27155483e-01 -1.18324310e-02 -1.09365463e+00 -8.10135424e-01
-1.61910549e-01 7.38353074e-01 -5.39132535e-01 1.99213341e-01
-8.93509686e-01 -7.04068244e-01 7.70158470e-02 5.24051011e-01
2.14585632e-01 -1.08672869e+00 -1.32008731e+00 1.77004978e-01
1.33925095e-01 -9.62858915e-01 -7.72301137e-01 1.03137779e+00
-7.80333519e-01 -1.24164903e+00 -7.37645328e-01 -1.11725175e+00
9.64903474e-01 4.15866017e-01 1.27811468e+00 2.33161494e-01
-8.17272425e-01 7.78410137e-01 -1.55422138e-02 -2.52684355e-01
-1.61045328e-01 -7.79972076e-02 -2.55827188e-01 -9.43084210e-02
3.92689466e-01 1.48709163e-01 -5.14586151e-01 2.16756299e-01
-1.15034211e+00 -4.39094864e-02 7.53533125e-01 7.01530337e-01
7.12473154e-01 -3.64361294e-02 -3.28388065e-03 -1.08767724e+00
4.23649788e-01 -3.47739786e-01 -8.83403778e-01 4.06481504e-01
-2.45951414e-01 2.94185847e-01 2.18335673e-01 -6.97042525e-01
-7.70857692e-01 5.06563485e-01 4.42176521e-01 -7.21882343e-01
-3.53596509e-01 1.45604342e-01 -6.64229542e-02 -1.43997461e-01
6.11469388e-01 3.12839150e-01 -1.67731509e-01 -4.45792466e-01
4.99385238e-01 -9.27697867e-02 6.34461701e-01 -7.10939229e-01
6.91243649e-01 1.70637086e-01 -2.55232096e-01 -8.41642976e-01
-7.89768040e-01 -7.86360741e-01 -8.39473724e-01 -1.70206860e-01
1.20945764e+00 -6.23319209e-01 -4.80968207e-01 7.32478946e-02
-1.07442117e+00 -7.19752252e-01 -5.99981844e-01 1.64194658e-01
-7.25906491e-01 3.89196992e-01 -5.15215874e-01 -9.35275376e-01
2.65602440e-01 -1.58545792e+00 1.19248331e+00 3.48614484e-01
-3.56259160e-02 -6.17550194e-01 -1.54785469e-01 4.25961912e-01
2.61115998e-01 -9.95594859e-02 1.05791199e+00 -1.10741460e+00
-1.41738999e+00 -4.92917048e-03 -3.66530567e-01 8.03009346e-02
-2.85478503e-01 -1.47654682e-01 -8.12911749e-01 -4.30008918e-01
1.41962290e-01 -2.96529621e-01 8.96898925e-01 3.35185587e-01
1.18635988e+00 -1.86105296e-01 -5.11353076e-01 3.61956030e-01
1.49612153e+00 5.38608730e-01 3.39066267e-01 1.72588706e-01
6.62480712e-01 5.60367346e-01 6.76687360e-01 4.06117961e-02
8.45832080e-02 2.45940164e-01 5.49880207e-01 -2.58701682e-01
-5.87789202e-03 1.17096424e-01 6.91611022e-02 4.40872371e-01
3.87088954e-01 -4.25195038e-01 -1.04341125e+00 8.10421586e-01
-1.85408986e+00 -7.35757649e-01 1.45459607e-01 2.01380563e+00
7.14756072e-01 5.39280474e-01 1.56626910e-01 -1.75055370e-01
6.98908746e-01 1.36591569e-01 -8.90407562e-01 -3.11349213e-01
1.48281157e-01 3.55215579e-01 6.14958465e-01 7.68126249e-01
-1.31284082e+00 1.23589945e+00 7.08626795e+00 7.05304503e-01
-8.22399616e-01 -1.01615176e-01 9.57733154e-01 -1.69836748e-02
-1.52703105e-02 5.40916668e-03 -8.87940764e-01 1.40507057e-01
7.37217426e-01 2.14078456e-01 4.26147163e-01 8.35574746e-01
-2.79602647e-01 -7.53715396e-01 -1.43857384e+00 6.17013574e-01
2.83306748e-01 -1.14176774e+00 -1.27128303e-01 -1.02997810e-01
7.07406223e-01 -5.14032617e-02 1.31946295e-01 3.46559078e-01
8.27315331e-01 -9.49895084e-01 8.24083447e-01 2.99414754e-01
2.42973477e-01 -2.67657638e-01 3.28025192e-01 4.40601707e-01
-1.17176569e+00 -9.80873853e-02 -1.69660691e-02 2.51190037e-01
-7.07022250e-02 -7.48449042e-02 -8.76897633e-01 3.83972563e-02
5.07669389e-01 1.01590708e-01 -8.93909633e-01 1.51615572e+00
3.01833861e-02 3.01432103e-01 -3.46563458e-01 -1.43669024e-01
5.69754779e-01 -4.92514782e-02 6.09538555e-01 1.27021492e+00
1.72889307e-02 1.50299400e-01 8.50343704e-01 1.14318335e+00
2.22177893e-01 -6.69969916e-02 -4.94516701e-01 -9.10121500e-02
1.88366160e-01 9.92919683e-01 -1.72700906e+00 -6.88449025e-01
-2.40581587e-01 1.08456731e+00 3.06431323e-01 6.86239004e-01
-7.85107911e-01 -4.43764001e-01 3.30282480e-01 -1.33824751e-01
8.41854274e-01 -4.38723922e-01 -3.65270138e-01 -1.23066366e+00
-2.73781538e-01 -9.55666780e-01 4.01532412e-01 -6.62847519e-01
-6.92986667e-01 4.16672140e-01 2.85525560e-01 -6.43628061e-01
4.66528721e-02 -8.55906188e-01 -4.97959018e-01 5.23290873e-01
-1.26302397e+00 -4.38920677e-01 -8.08121543e-03 4.27581578e-01
1.08597183e+00 3.02676767e-01 2.83504188e-01 3.11959870e-02
-8.91758978e-01 2.62231052e-01 -1.71333492e-01 1.22171067e-01
1.74408257e-01 -1.56413925e+00 2.72546947e-01 1.34146917e+00
5.57298899e-01 6.29606783e-01 9.26070511e-01 -6.74557388e-01
-1.50026095e+00 -7.67715096e-01 4.36488897e-01 -6.79840624e-01
6.80685163e-01 -6.17750049e-01 -8.56267452e-01 9.04575408e-01
2.23963797e-01 -2.12180149e-03 4.30139631e-01 -2.49862239e-01
-8.47660527e-02 2.54463941e-01 -1.10765123e+00 7.05590665e-01
1.03258228e+00 -1.49012670e-01 -7.04015136e-01 3.51511896e-01
8.53606761e-01 -4.75823790e-01 -2.43743569e-01 3.82968150e-02
6.35539414e-03 -8.42446566e-01 9.38458323e-01 -7.22106874e-01
3.83069701e-02 -3.61302197e-01 -2.64025867e-01 -8.83647144e-01
-6.15647137e-02 -6.48612857e-01 -2.20483597e-02 5.05831420e-01
6.00399017e-01 -5.75026013e-02 1.10068703e+00 7.89462507e-01
-2.81689793e-01 -6.12488151e-01 -9.22444701e-01 -6.69218719e-01
-3.22473615e-01 -4.40809101e-01 7.14717954e-02 5.49084306e-01
-2.90446222e-01 3.74563992e-01 8.26881733e-03 2.78418809e-01
7.89729774e-01 2.62580514e-01 6.83463573e-01 -1.16615331e+00
-3.52615178e-01 -5.29563308e-01 -2.42474154e-01 -1.50230181e+00
-1.75446793e-01 -5.51308870e-01 8.25428367e-01 -1.29862022e+00
2.34864399e-01 -4.07870650e-01 -3.26483190e-01 4.65139478e-01
-1.80585757e-01 1.01075895e-01 3.71675342e-01 -1.03169419e-01
-1.31454468e+00 -6.80267960e-02 1.34158480e+00 -4.42669004e-01
-2.82104939e-01 -9.19916257e-02 -6.19758010e-01 8.02054822e-01
3.29813361e-01 -4.53827292e-01 -3.00497383e-01 -6.01502419e-01
-2.23731935e-01 2.75662303e-01 2.88503021e-01 -1.05519080e+00
5.71657062e-01 -2.77231067e-01 3.88057888e-01 -7.38615930e-01
5.26419163e-01 -9.23099339e-01 -3.55802029e-01 5.41978180e-01
-4.29475635e-01 1.05884522e-01 4.02851522e-01 8.07629168e-01
9.23599899e-02 -6.01004958e-01 7.10095406e-01 -4.96129155e-01
-1.23754036e+00 9.15722921e-02 -6.80173218e-01 2.87017554e-01
1.29664719e+00 -6.65776432e-01 -2.74307668e-01 6.79254681e-02
-1.19976676e+00 4.55669105e-01 4.27679181e-01 6.53604120e-02
6.07783139e-01 -6.60976350e-01 -9.89579707e-02 3.90577257e-01
-1.42522469e-01 2.34248221e-01 -1.41696960e-01 6.53574646e-01
-6.12437427e-01 4.08970475e-01 -9.25139487e-02 -8.46846342e-01
-1.22048211e+00 9.44994628e-01 2.70783454e-01 -3.00464809e-01
-3.41237366e-01 1.33030152e+00 4.34022397e-01 8.41137618e-02
7.52239168e-01 -6.40211582e-01 1.99880004e-02 1.46407679e-01
3.52291197e-01 2.31311604e-01 -2.86831081e-01 -4.34849322e-01
-2.21247241e-01 2.78382301e-01 -2.88749516e-01 -8.28602985e-02
9.96259928e-01 -1.82295114e-01 1.02254897e-02 5.32903731e-01
8.40133727e-01 -1.98132932e-01 -1.62717652e+00 -2.62218237e-01
5.83454788e-01 -5.52485824e-01 -7.99856111e-02 -7.75592804e-01
-1.05257428e+00 7.96743810e-01 6.22334003e-01 2.98202187e-01
9.28116620e-01 1.20921738e-01 3.65931839e-01 7.42201388e-01
4.17107642e-01 -1.14425802e+00 7.09273040e-01 5.88048756e-01
2.19174907e-01 -1.40059447e+00 -6.27597868e-02 -3.68413657e-01
-4.16215628e-01 9.48902786e-01 1.02508068e+00 -1.00504935e-01
3.86941284e-01 4.14796442e-01 7.20187351e-02 -4.62035179e-01
-5.79878747e-01 -6.64771020e-01 1.88719541e-01 3.84919465e-01
-1.17249191e-01 -2.03461722e-01 1.73941582e-01 2.58091897e-01
2.17670083e-01 -3.20768952e-01 5.06309867e-01 1.41467571e+00
-1.06268752e+00 -7.84576952e-01 -5.51312149e-01 5.97473562e-01
-3.84500742e-01 -1.14312403e-01 -4.16556358e-01 9.55840647e-01
2.20152780e-01 8.00045788e-01 1.74257562e-01 -9.73019600e-02
5.73309362e-02 3.32121819e-01 4.71208274e-01 -1.06726134e+00
-6.74704790e-01 3.71823102e-01 -1.41372323e-01 -7.41189122e-01
-2.07626894e-01 -5.52784324e-01 -1.04848504e+00 2.96503365e-01
-4.15282875e-01 7.80693144e-02 4.29772764e-01 8.16282749e-01
5.83465621e-02 6.58785462e-01 8.08328688e-02 -1.10237980e+00
-6.62447095e-01 -3.39613914e-01 -5.84743500e-01 1.99368358e-01
5.17256081e-01 -4.92453218e-01 -2.17913464e-01 -8.25936906e-03] | [9.283905982971191, 0.05174309015274048] |
b2d48b6c-d68b-4337-a107-a8092a6599d3 | geometric-pooling-maintaining-more-useful | 2306.12341 | null | https://arxiv.org/abs/2306.12341v1 | https://arxiv.org/pdf/2306.12341v1.pdf | Geometric Pooling: maintaining more useful information | Graph Pooling technology plays an important role in graph node classification tasks. Sorting pooling technologies maintain large-value units for pooling graphs of varying sizes. However, by analyzing the statistical characteristic of activated units after pooling, we found that a large number of units dropped by sorting pooling are negative-value units that contain useful information and can contribute considerably to the final decision. To maintain more useful information, a novel pooling technology, called Geometric Pooling (GP), was proposed to contain the unique node features with negative values by measuring the similarity of all node features. We reveal the effectiveness of GP from the entropy reduction view. The experiments were conducted on TUdatasets to show the effectiveness of GP. The results showed that the proposed GP outperforms the SOTA graph pooling technologies by 1%\sim5% with fewer parameters. | ['Shuai Wang', 'Hongsen Zhao', 'Shuyue Zhou', 'Ruihua Zhang', 'Yanxia Bao', 'Kenan Lou', 'Yang shen', 'Jia Liu', 'Hao Xu'] | 2023-06-21 | null | null | null | null | ['node-classification'] | ['graphs'] | [ 1.29096344e-01 4.62756425e-01 -4.79385763e-01 9.38050523e-02
-1.05301410e-01 -4.08103138e-01 2.04238147e-01 3.83414656e-01
-1.25571772e-01 8.17246914e-01 2.21842706e-01 1.12556785e-01
-1.46123454e-01 -1.25666749e+00 -1.62310258e-01 -7.21233189e-01
-6.92726552e-01 -4.44226235e-01 6.18580222e-01 -2.53046840e-01
4.08785015e-01 4.71242368e-01 -1.12117064e+00 4.20740753e-01
8.09015453e-01 1.12558317e+00 8.50373358e-02 4.12350982e-01
-2.07976937e-01 7.13111103e-01 -8.96193266e-01 -5.72910249e-01
4.18003201e-01 -9.88820344e-02 -4.80715990e-01 -2.70345479e-01
1.99532241e-01 -2.33416364e-01 -7.51473486e-01 1.22095299e+00
4.90243137e-01 1.59782454e-01 3.82646888e-01 -1.46648359e+00
-4.19735104e-01 9.49201167e-01 -6.52449489e-01 3.88282776e-01
3.88251334e-01 -1.52417704e-01 1.43740332e+00 -5.27895689e-01
7.21724510e-01 1.25742030e+00 7.32283950e-01 1.43713877e-01
-9.37479377e-01 -7.97962606e-01 9.63425785e-02 -1.40750587e-01
-1.42547369e+00 -5.64798452e-02 9.03374612e-01 4.57220189e-02
1.32846308e+00 5.92968881e-01 6.70721829e-01 4.84141827e-01
8.42926860e-01 6.29415751e-01 6.42521799e-01 -5.14306724e-02
-7.95297176e-02 1.57605082e-01 6.07993841e-01 1.01221824e+00
9.38810945e-01 -5.33254206e-01 -5.50487399e-01 -3.66705596e-01
5.51118016e-01 2.21923620e-01 -2.99058676e-01 6.52989596e-02
-1.08139336e+00 7.19080269e-01 9.55429375e-01 4.13580209e-01
-4.14073497e-01 2.63099283e-01 5.11843979e-01 4.01972055e-01
6.56953692e-01 6.24719560e-01 -2.78735846e-01 2.39137843e-01
-4.68157142e-01 7.76381493e-02 8.66600931e-01 1.22380519e+00
7.37657785e-01 -1.21528558e-01 -7.28725612e-01 4.02185082e-01
1.02955274e-01 2.00193673e-01 6.43174350e-01 -4.28218067e-01
9.30473030e-01 1.60985875e+00 -5.49422741e-01 -1.61870265e+00
-4.53841776e-01 -3.42082560e-01 -1.08328283e+00 -4.05255735e-01
-7.86856189e-02 -4.08479661e-01 -9.05819178e-01 1.50131965e+00
-1.94346353e-01 -1.06003881e-01 1.32413441e-02 1.75932482e-01
1.41119838e+00 6.91465676e-01 3.36835235e-02 -3.21835339e-01
1.32800174e+00 -6.39245510e-01 -1.10982382e+00 1.65652242e-02
7.10377038e-01 -4.23215806e-01 6.71548843e-01 -2.06246190e-02
-1.04869485e+00 -3.96329015e-01 -1.37235880e+00 1.33014634e-01
-8.85340750e-01 -1.53853506e-01 9.07809973e-01 1.09022021e+00
-1.32882011e+00 9.00901020e-01 -3.71005744e-01 -5.36863804e-01
5.75201035e-01 7.07187176e-01 -5.00357866e-01 2.78187603e-01
-1.38273048e+00 4.87576395e-01 6.71821058e-01 5.18188588e-02
-2.38186836e-01 -4.26483572e-01 -9.16311264e-01 6.70664370e-01
4.14061368e-01 -1.74829751e-01 4.55112427e-01 -2.11912423e-01
-1.04148495e+00 1.77334487e-01 -1.90653905e-01 -3.47984701e-01
1.75229400e-01 3.23211282e-01 -2.21530288e-01 3.26078624e-01
-2.47778788e-01 4.28974003e-01 5.77115357e-01 -7.93739378e-01
-3.03909302e-01 -2.07139701e-01 5.31240255e-02 2.82690644e-01
-9.44699347e-01 -2.04520687e-01 -4.40283895e-01 -6.72423184e-01
4.97564018e-01 -5.95180869e-01 -1.63974300e-01 -6.30441785e-01
-5.91477871e-01 -4.04606014e-01 9.63784635e-01 -6.01139426e-01
1.90714347e+00 -2.00270319e+00 -1.27251491e-01 6.98789716e-01
7.97045171e-01 1.72171116e-01 -3.47708128e-02 6.66823387e-01
2.17507958e-01 1.02756178e+00 7.75139332e-02 6.10550530e-02
-2.87402630e-01 -9.72190052e-02 4.50533070e-02 2.09276661e-01
2.89721429e-01 1.09198987e+00 -8.92119586e-01 -7.90941477e-01
2.06779502e-02 1.28182366e-01 -5.25799870e-01 -1.86689887e-02
4.19290453e-01 -5.23320198e-01 -9.11450922e-01 9.44193721e-01
8.79058957e-01 -2.86008120e-01 5.12130618e-01 -1.89778075e-01
3.04771692e-01 2.67982855e-02 -1.07491744e+00 1.07576644e+00
3.73496681e-01 6.37049019e-01 -5.22105917e-02 -6.05194271e-01
1.18634975e+00 2.12347820e-01 6.07791245e-01 -3.19681793e-01
4.00288433e-01 -6.41638786e-02 1.47713825e-01 -2.24466756e-01
1.23802400e+00 3.71892452e-01 -3.29963654e-01 1.97074980e-01
3.02267909e-01 -1.81390360e-01 2.70929098e-01 6.44459784e-01
1.67921686e+00 -7.97379732e-01 4.30828035e-01 -5.08075714e-01
3.15055579e-01 -4.29747880e-01 6.41753674e-01 6.70407414e-01
-6.30924642e-01 5.13499498e-01 1.08057427e+00 -7.73969293e-02
-4.00268465e-01 -8.25939178e-01 6.52657747e-02 6.78730786e-01
4.19565976e-01 -9.28459466e-01 -5.83460867e-01 -9.46450174e-01
2.73758560e-01 1.02424227e-01 -6.55634403e-01 -4.35551733e-01
-3.81627262e-01 -1.10361278e+00 5.79812109e-01 4.49305475e-01
8.63853216e-01 -1.17971253e+00 -1.68547675e-01 3.10521070e-02
-1.87593654e-01 -9.47308898e-01 -5.04962027e-01 1.77563533e-01
-1.13142586e+00 -8.35311413e-01 -4.33550328e-01 -8.35903525e-01
9.22254860e-01 7.09526837e-01 8.92095625e-01 5.57692945e-01
-8.03241432e-02 -4.64283973e-02 -5.00904083e-01 -2.65005946e-01
3.22643444e-02 7.06106663e-01 -1.90279379e-01 -3.07621211e-01
2.86732972e-01 -4.43466574e-01 -4.49924618e-01 2.54736960e-01
-6.01210117e-01 -3.32207561e-01 7.27715731e-01 6.39224589e-01
2.03353256e-01 5.82126796e-01 8.17832530e-01 -9.70950007e-01
1.37198877e+00 -4.66426551e-01 -5.31480350e-02 3.69244039e-01
-3.96138996e-01 2.08328113e-01 4.32125807e-01 -1.40838727e-01
-7.67291963e-01 -5.47803938e-01 4.79483306e-01 7.66219664e-03
8.61688077e-01 5.00338674e-01 -2.86596000e-01 -4.66702789e-01
3.17019939e-01 -1.11494660e-01 -3.95861678e-02 -1.94091931e-01
7.24258199e-02 5.08961678e-01 -9.59912539e-02 -1.04653805e-01
4.36296046e-01 1.91275537e-01 2.55952924e-01 -7.90517807e-01
2.29696304e-01 -3.71815950e-01 -4.08974499e-01 -1.88743234e-01
6.97103679e-01 -6.50234520e-01 -9.81959224e-01 2.98259526e-01
-9.28118289e-01 2.83412218e-01 -1.19242944e-01 1.72096014e-01
9.18849260e-02 5.55964112e-01 -8.83608401e-01 -8.52017462e-01
-7.88838983e-01 -9.39013243e-01 5.28959155e-01 5.74449062e-01
-1.25199914e-01 -7.45201886e-01 -4.38544661e-01 -5.10118343e-02
3.52421731e-01 4.26977515e-01 9.65473115e-01 -8.19407642e-01
-6.54035747e-01 -8.14335287e-01 -5.93503892e-01 3.09077591e-01
2.34833255e-01 1.11997016e-01 -8.74592483e-01 -4.39910412e-01
-4.23323601e-01 2.16519743e-01 1.08571577e+00 3.00391108e-01
1.13565195e+00 -1.68688118e-01 -7.31557906e-01 2.15016067e-01
1.37520993e+00 2.50292122e-01 8.37104023e-01 -3.59196156e-01
8.29062700e-01 4.68883574e-01 2.48612240e-01 3.36980462e-01
1.45462230e-01 1.18659168e-01 3.12632501e-01 1.93738230e-02
-8.55080336e-02 -4.02062953e-01 4.20137942e-01 1.04320872e+00
-3.42097193e-01 -7.37148643e-01 -4.30166990e-01 3.69841158e-01
-1.85929859e+00 -9.12405729e-01 -1.01892225e-01 2.01160502e+00
3.91366541e-01 6.36208117e-01 -1.31098881e-01 2.44268179e-01
8.93679082e-01 4.96125489e-01 -2.30542839e-01 -6.08798802e-01
-1.25082478e-01 1.42970711e-01 1.04402173e+00 1.12539597e-01
-9.10414338e-01 9.91899908e-01 7.27632093e+00 9.49406445e-01
-6.61142528e-01 -3.16256046e-01 5.00587761e-01 2.03023285e-01
-3.10282290e-01 -2.36546189e-01 -6.73050106e-01 5.25332570e-01
5.53505063e-01 -6.03410006e-01 1.33469805e-01 6.32798612e-01
-1.92653555e-02 -3.00179780e-01 -6.47102773e-01 6.38152063e-01
-3.55291157e-03 -1.14881730e+00 2.16439575e-01 3.13459098e-01
7.76220620e-01 -1.71328142e-01 -2.08213389e-01 4.17621076e-01
3.79112542e-01 -8.34863365e-01 -1.84255708e-02 3.75588208e-01
2.38626987e-01 -7.57773399e-01 1.25850582e+00 -1.79891452e-01
-1.79360068e+00 -6.89800829e-02 -7.90685177e-01 -2.80861825e-01
-2.10116476e-01 6.19059741e-01 -1.03970575e+00 9.64091301e-01
5.73330045e-01 7.88050175e-01 -9.35205638e-01 9.26599979e-01
-7.75055364e-02 3.11613172e-01 -3.41081023e-01 -5.58575153e-01
3.15877609e-02 -1.19895443e-01 6.08573377e-01 1.01763856e+00
3.83991152e-01 -6.20386340e-02 3.97921354e-02 5.26918173e-01
-6.39890194e-01 3.30895722e-01 -8.31969261e-01 -3.26652586e-01
6.03659630e-01 1.57135427e+00 -1.17919958e+00 -4.45483059e-01
-2.96932250e-01 5.51471353e-01 1.62017986e-01 1.42673135e-01
-5.61947942e-01 -1.18376040e+00 3.71992111e-01 -7.83059746e-02
2.48629913e-01 -7.55617097e-02 -6.75568402e-01 -9.21603262e-01
1.63780108e-01 -2.49664992e-01 6.06923223e-01 -2.95083731e-01
-1.14601469e+00 6.47901475e-01 4.16785702e-02 -1.09859335e+00
2.39554822e-01 -5.26501119e-01 -9.11438286e-01 7.68230438e-01
-1.01233864e+00 -7.78759062e-01 -5.84066272e-01 3.33506197e-01
2.95494441e-02 -1.87818721e-01 4.49448794e-01 7.70456567e-02
-8.67498100e-01 8.42435420e-01 -2.73722857e-01 2.89672077e-01
3.80714625e-01 -1.14199901e+00 4.97263491e-01 8.20523500e-01
-3.56688410e-01 7.17319071e-01 3.35773528e-01 -1.08008051e+00
-1.45697844e+00 -8.43611658e-01 1.00955749e+00 -1.42143980e-01
4.10727739e-01 -4.36407626e-01 -8.55910957e-01 5.13440013e-01
3.39315265e-01 2.64073233e-03 5.07038414e-01 7.73216784e-02
1.33942040e-02 -1.43762946e-01 -1.65387905e+00 6.96091235e-01
1.25553727e+00 -3.01277667e-01 -4.90684927e-01 -1.10974750e-02
1.02998471e+00 -4.04445658e-04 -1.07727313e+00 5.48779845e-01
5.63373327e-01 -6.47714317e-01 7.49549925e-01 -3.60865951e-01
1.00441404e-01 -8.55673701e-02 -7.72515088e-02 -1.26332641e+00
-3.98180455e-01 -7.00874865e-01 -4.87336479e-02 1.22725582e+00
6.46216929e-01 -1.05015755e+00 9.46417868e-01 6.67432427e-01
1.02906756e-01 -6.97088957e-01 -7.12303221e-01 -7.20998645e-01
-2.76647776e-01 1.81616947e-01 8.28225136e-01 8.12671900e-01
9.12393868e-01 4.90747355e-02 -1.07622720e-01 -1.25485271e-01
2.39123434e-01 -2.50992209e-01 4.52685356e-01 -1.34206522e+00
3.61289710e-01 -5.86044014e-01 -9.95207727e-01 -6.38854444e-01
-7.57407993e-02 -1.16923726e+00 -2.76500553e-01 -1.70935547e+00
4.05883700e-01 -1.20228164e-01 -8.28581929e-01 6.11009717e-01
-4.16555405e-01 2.50834823e-01 2.82973111e-01 3.81922871e-02
-4.67764735e-01 2.85801291e-01 1.55744958e+00 -1.39210775e-01
-6.35454535e-01 -1.71925128e-01 -9.35728848e-01 2.30625615e-01
1.07630765e+00 -1.93931937e-01 -5.41745543e-01 8.45422372e-02
2.28422195e-01 -3.71406227e-01 -2.19266713e-01 -8.88815463e-01
1.94796458e-01 7.53251985e-02 4.21616346e-01 -6.37074471e-01
2.33054131e-01 -5.68315923e-01 -2.22327009e-01 7.22046077e-01
-1.52844593e-01 1.71345323e-01 2.89251268e-01 4.40312117e-01
-1.71582580e-01 -6.99370354e-02 3.03420499e-02 -1.25982344e-01
-7.52195418e-01 3.35043162e-01 -2.12593868e-01 -2.54433930e-01
1.21123898e+00 -4.52267319e-01 -6.61921561e-01 -3.20218861e-01
-4.35603738e-01 4.85945821e-01 1.18037485e-01 2.47147352e-01
6.33359551e-01 -1.39259422e+00 -4.44550812e-01 3.25237334e-01
2.85565555e-02 -3.54072988e-01 2.77413607e-01 5.27262688e-01
-5.13439894e-01 3.44662756e-01 -2.97820121e-01 -7.19608963e-02
-1.41865504e+00 3.11057329e-01 1.74177345e-02 -6.94929600e-01
-5.39904237e-01 8.42182755e-01 -2.37669218e-02 -6.35706112e-02
1.41675189e-01 -9.13693845e-01 -4.28887218e-01 5.35667360e-01
2.95394838e-01 8.17115664e-01 3.03534985e-01 -2.97046930e-01
-4.03507113e-01 2.40746856e-01 -1.81877330e-01 2.50265777e-01
1.01231027e+00 5.14937192e-02 -3.10365319e-01 -3.87031236e-03
1.30084860e+00 1.58739075e-01 -7.67956495e-01 -7.47603411e-03
-3.07049602e-02 -5.22616625e-01 2.02341229e-01 -2.80268043e-01
-1.46022892e+00 5.37680387e-01 1.23808175e-01 9.43229258e-01
1.01874411e+00 -2.12833732e-01 6.13266349e-01 4.23491687e-01
5.74549079e-01 -9.91884172e-01 -9.90007631e-03 1.91680834e-01
7.90755868e-01 -1.10355794e+00 4.63288277e-01 -1.19554126e+00
-5.71838498e-01 1.08834636e+00 6.34220481e-01 -3.50694895e-01
8.88151109e-01 2.02294841e-01 -6.06416643e-01 -3.27427357e-01
-5.95628440e-01 -2.23958120e-01 3.79270971e-01 4.53014761e-01
4.48647350e-01 5.36998153e-01 -7.50869095e-01 7.92319834e-01
-2.53931224e-01 -2.57460505e-01 6.89135611e-01 1.11534011e+00
-5.41618466e-01 -8.83107185e-01 8.32588449e-02 1.00071025e+00
-2.95456022e-01 -1.80617422e-01 -8.69184792e-01 9.28420842e-01
-1.83228269e-01 1.04727924e+00 1.03127576e-01 -1.16738653e+00
2.72626340e-01 -1.98649652e-02 2.40642250e-01 -4.69345599e-01
-1.08387101e+00 -4.16316837e-01 1.43710598e-01 -4.90871042e-01
-1.30658839e-02 -2.94084132e-01 -1.12356448e+00 -7.87034869e-01
-6.18388653e-01 -1.01726642e-02 1.93194866e-01 2.79903889e-01
4.83344436e-01 9.01185930e-01 7.77282000e-01 -5.99977911e-01
-2.36263767e-01 -1.21662712e+00 -9.43073928e-01 1.88029811e-01
-7.00211748e-02 -5.60289919e-01 -6.85502708e-01 -6.70820177e-01] | [7.064884662628174, 6.256589889526367] |
86a2997d-b32d-4c15-ac2b-d18fa48fd13b | deep-unsupervised-learning-using-spike-timing | 2307.04054 | null | https://arxiv.org/abs/2307.04054v1 | https://arxiv.org/pdf/2307.04054v1.pdf | Deep Unsupervised Learning Using Spike-Timing-Dependent Plasticity | Spike-Timing-Dependent Plasticity (STDP) is an unsupervised learning mechanism for Spiking Neural Networks (SNNs) that has received significant attention from the neuromorphic hardware community. However, scaling such local learning techniques to deeper networks and large-scale tasks has remained elusive. In this work, we investigate a Deep-STDP framework where a convolutional network is trained in tandem with pseudo-labels generated by the STDP clustering process on the network outputs. We achieve $24.56\%$ higher accuracy and $3.5\times$ faster convergence speed at iso-accuracy on a 10-class subset of the Tiny ImageNet dataset in contrast to a $k$-means clustering approach. | ['Abhronil Sengupta', 'Sen Lu'] | 2023-07-08 | null | null | null | null | ['clustering'] | ['methodology'] | [ 3.46947938e-01 -3.04995269e-01 2.53653258e-01 -6.37124956e-01
-3.11095327e-01 -5.45333624e-01 3.70620638e-01 -1.69545636e-01
-7.99232483e-01 9.01414990e-01 -3.36049885e-01 -1.09226488e-01
-2.19033718e-01 -6.07461333e-01 -1.13272023e+00 -1.02548945e+00
-2.11130127e-01 2.95188367e-01 5.25205135e-01 2.07862020e-01
4.95178759e-01 4.17991281e-01 -1.59178400e+00 5.63097656e-01
4.67759192e-01 1.36109757e+00 1.15973838e-01 3.76624107e-01
-5.72826080e-02 6.55908942e-01 -4.03213263e-01 1.59563318e-01
5.42987764e-01 -5.07686257e-01 -3.67748201e-01 -4.20152575e-01
4.49822187e-01 3.88622165e-01 -6.17083788e-01 1.12249959e+00
5.96450984e-01 -1.00150868e-01 5.03548503e-01 -1.18978691e+00
-3.69765103e-01 8.56433988e-01 -2.23933980e-01 4.94828552e-01
-5.29616773e-01 3.25661361e-01 6.17052257e-01 -7.35168695e-01
6.48136199e-01 7.31543243e-01 9.66834486e-01 6.89080715e-01
-1.69751799e+00 -1.19550920e+00 -3.84538144e-01 -1.37419671e-01
-1.48880053e+00 -4.18052375e-01 4.32148099e-01 -3.89578462e-01
1.44590592e+00 -5.39555252e-01 8.34467709e-01 1.01929629e+00
5.97472966e-01 2.88162977e-01 1.41266024e+00 1.17577672e-01
8.01037014e-01 -6.00483537e-01 2.21811980e-01 3.76913846e-01
2.87604809e-01 1.04565769e-01 -9.77003634e-01 1.76039219e-01
9.62857962e-01 1.74640179e-01 1.13234907e-01 -7.53364861e-02
-9.07146513e-01 4.17057097e-01 7.78179646e-01 3.06096196e-01
-2.84681052e-01 9.38401997e-01 2.43055642e-01 3.40322107e-01
-7.52460808e-02 4.66942042e-01 -5.71416199e-01 -4.17099088e-01
-1.18479538e+00 2.52786577e-01 7.09508955e-01 7.13063538e-01
1.10798085e+00 5.08915544e-01 2.21881822e-01 1.03069019e+00
1.88680887e-01 5.17933726e-01 6.44013166e-01 -1.18527055e+00
2.69057993e-02 7.93202579e-01 -5.25242984e-01 -7.92831779e-01
-3.51500243e-01 -2.96439111e-01 -9.88598347e-01 6.55568302e-01
5.67685843e-01 -1.33860454e-01 -1.28676450e+00 1.85670316e+00
-5.54499209e-01 4.16231722e-01 -1.09464340e-01 5.63874900e-01
4.27504361e-01 4.48750734e-01 1.06652183e-02 1.88685566e-01
6.73793674e-01 -5.91545880e-01 -1.26716241e-01 -4.71152306e-01
2.95797914e-01 -1.98969886e-01 4.89868760e-01 3.37865293e-01
-9.56621945e-01 -4.17967021e-01 -1.03068066e+00 1.26969963e-01
-6.35865867e-01 -2.59449273e-01 5.02939522e-01 4.92832303e-01
-1.67884994e+00 8.02115798e-01 -1.10538304e+00 -4.94782031e-01
1.05063403e+00 9.45234478e-01 -1.66697159e-01 -9.43159163e-02
-4.67611492e-01 5.57168543e-01 4.20352757e-01 -2.01730013e-01
-1.15003514e+00 -7.52571404e-01 -2.92493254e-01 -5.91923669e-02
-4.41884071e-01 -1.94906831e-01 8.69518399e-01 -8.51639450e-01
-1.38349485e+00 9.98893857e-01 -3.30509901e-01 -1.01959026e+00
-1.90538377e-01 3.26616973e-01 -3.36311199e-02 4.16413173e-02
-1.78898886e-01 1.12202919e+00 6.00385070e-01 -1.03416646e+00
-4.26367849e-01 -5.41706026e-01 -7.56978393e-01 -2.26392046e-01
-1.01738043e-01 -1.12171352e-01 -2.05413222e-01 -6.08206749e-01
6.26099050e-01 -1.11228216e+00 -3.39671403e-01 3.20367873e-01
-1.58797652e-01 -5.66536793e-03 8.05058181e-01 -1.53637692e-01
6.35785580e-01 -2.29629040e+00 -6.54684380e-02 5.11395454e-01
3.78959239e-01 2.72446245e-01 -8.42481032e-02 -1.43110044e-02
-1.91763192e-01 -6.27717236e-03 -7.42950857e-01 -2.56614625e-01
-1.96278408e-01 5.36955416e-01 -2.58958846e-01 3.30912143e-01
3.02861214e-01 1.13371146e+00 -4.84152257e-01 1.95785463e-02
-2.39770427e-01 4.14631158e-01 -5.10671258e-01 -2.84482419e-01
-1.50013313e-01 2.76123315e-01 2.73999482e-01 8.75824213e-01
5.59632421e-01 -4.19613630e-01 2.14687750e-01 1.41939551e-01
-3.85145605e-01 2.04524890e-01 -6.56454921e-01 1.89627373e+00
1.81460172e-01 1.03068054e+00 -1.32298961e-01 -1.30312335e+00
1.45017731e+00 -8.94618332e-02 6.54331565e-01 -1.05260265e+00
3.29625577e-01 6.19238973e-01 5.09005666e-01 2.01395378e-01
-1.29345998e-01 -6.93873391e-02 1.05271444e-01 5.82419038e-01
6.39289200e-01 6.68612495e-02 6.06171377e-02 5.71131632e-02
1.92230570e+00 -6.63120002e-02 -4.59151834e-01 -8.56977463e-01
-3.10017318e-01 -6.72506019e-02 5.97506106e-01 8.88790667e-01
-3.50238949e-01 6.67728364e-01 4.01956707e-01 -3.45101595e-01
-1.03019452e+00 -1.39994133e+00 -4.06848431e-01 8.70955348e-01
-7.93848783e-02 -1.64827835e-02 -6.90123856e-01 8.34205672e-02
1.58925787e-01 1.32321138e-02 -7.55224764e-01 -1.86464921e-01
-6.13083422e-01 -7.85796106e-01 1.29105866e+00 7.51132429e-01
6.94678068e-01 -1.54039049e+00 -6.60346031e-01 4.50187922e-01
5.23461223e-01 -1.02520454e+00 9.84554589e-02 1.23511958e+00
-1.15787542e+00 -8.92813683e-01 -5.26840448e-01 -1.37983036e+00
9.17673767e-01 -2.36045539e-01 7.55589008e-01 -2.58537740e-01
-5.38612366e-01 -1.66157854e-03 1.54244695e-02 -3.18406165e-01
1.94986075e-01 -6.42462000e-02 1.78362891e-01 -2.47899473e-01
7.53152311e-01 -1.32231081e+00 -6.58569634e-01 1.43279821e-01
-8.23232234e-01 -3.45050693e-01 6.09013796e-01 6.94516122e-01
1.05523777e+00 -3.48131284e-02 7.23009467e-01 -7.56224751e-01
4.51123953e-01 -4.54227388e-01 -5.60699999e-01 -2.66759127e-01
-6.69159174e-01 2.13063195e-01 5.08875370e-01 -4.67222124e-01
-4.44405019e-01 3.02566439e-01 -1.48996070e-01 -3.34804118e-01
-2.21392944e-01 2.79729933e-01 3.49888265e-01 -6.40821099e-01
1.05973577e+00 6.87681973e-01 5.10470681e-02 -1.02123745e-01
-2.66511083e-01 1.54777855e-01 7.11000800e-01 -6.57912672e-01
6.75806165e-01 5.83294988e-01 -1.45797580e-02 -5.91709077e-01
-1.14908054e-01 -1.53589532e-01 -4.15233552e-01 -1.65398210e-01
6.51169479e-01 -8.31692040e-01 -6.19044423e-01 1.04913998e+00
-9.10158098e-01 -1.00124991e+00 -3.17396402e-01 2.11578712e-01
-6.64550304e-01 -3.07244271e-01 -8.64244163e-01 -4.24617559e-01
-3.61684948e-01 -9.41427529e-01 4.33844000e-01 5.34690022e-01
-1.30405903e-01 -6.27847254e-01 2.66399860e-01 -4.37547594e-01
8.51635695e-01 1.42881960e-01 7.50717998e-01 -6.87811971e-01
-6.35253131e-01 7.82436877e-02 -5.44929504e-01 3.71452332e-01
4.63132001e-02 8.53061303e-02 -1.17032456e+00 -6.77174255e-02
-1.48404583e-01 -5.98586082e-01 1.34017622e+00 5.94682515e-01
1.51925278e+00 6.83837384e-02 -2.73891300e-01 8.49460363e-01
1.73109162e+00 4.21443075e-01 9.75193202e-01 2.66124457e-01
3.16595405e-01 2.23110348e-01 -5.66812992e-01 4.04595435e-01
5.90392016e-02 -3.62746976e-02 4.32916015e-01 4.34169412e-01
-3.37205470e-01 -1.78427761e-03 1.58981547e-01 8.45704257e-01
4.07765396e-02 2.30017245e-01 -1.41402066e+00 7.14741468e-01
-1.76650453e+00 -8.43111038e-01 1.27156034e-01 1.97396028e+00
1.10838974e+00 3.88845026e-01 -1.68425336e-01 2.33608723e-01
8.17430973e-01 -1.91269398e-01 -1.01457918e+00 -2.40547016e-01
-7.47954667e-01 1.02783012e+00 5.03922164e-01 -1.47500917e-01
-6.07074022e-01 9.44193006e-01 6.58155918e+00 5.37837267e-01
-1.42075634e+00 -1.94817945e-01 7.38612652e-01 -9.39513966e-02
2.69738864e-02 -5.92130534e-02 -8.28105211e-01 7.83908665e-01
1.21798193e+00 -3.64232212e-02 8.69671762e-01 7.29730487e-01
-6.12719432e-02 -2.30982468e-01 -9.99747276e-01 1.35054600e+00
-1.73968583e-01 -1.78283501e+00 -2.77721256e-01 1.69556826e-01
1.15434659e+00 9.32323933e-01 2.97315866e-01 1.98268384e-01
4.47147042e-01 -1.19955981e+00 3.45704615e-01 5.19082725e-01
7.68513620e-01 -6.47507787e-01 3.65720123e-01 1.46323711e-01
-1.15527189e+00 -2.12804258e-01 -5.37838161e-01 -2.26109713e-01
-3.37026715e-01 7.22880900e-01 -3.84378254e-01 -5.60641229e-01
1.34700501e+00 9.63540077e-01 -4.91201311e-01 1.51574278e+00
3.37000377e-02 8.29005063e-01 -6.24577463e-01 -1.96845144e-01
1.68860123e-01 -4.28838730e-02 -1.24219172e-01 1.23316824e+00
4.19244468e-01 8.82089809e-02 -5.18689632e-01 1.09186292e+00
-6.86364710e-01 -5.64789772e-01 -6.61260664e-01 -4.15220588e-01
8.54174197e-01 1.05468595e+00 -1.15274382e+00 -1.70655131e-01
1.26495197e-01 7.59341121e-01 5.04113853e-01 3.95172477e-01
-5.40477812e-01 -6.14032924e-01 8.53742421e-01 2.91606411e-03
6.25895023e-01 -4.84453022e-01 -1.07028568e+00 -7.05675662e-01
-1.85462624e-01 -4.30238903e-01 -1.36283606e-01 -6.79765344e-01
-1.40293801e+00 5.10187626e-01 -8.04043293e-01 -8.82592320e-01
-7.87641406e-02 -9.49548006e-01 -8.07274818e-01 6.45142674e-01
-1.26079357e+00 -4.56147432e-01 -2.35402599e-01 8.77061009e-01
1.44318134e-01 -1.35743991e-01 9.35200870e-01 2.41328984e-01
-3.74147862e-01 5.51555812e-01 4.43522066e-01 4.08727676e-01
5.53179979e-01 -1.03810179e+00 3.63167346e-01 8.52686644e-01
-2.31856983e-02 9.23076332e-01 3.39957863e-01 -3.72430086e-01
-1.36207557e+00 -1.39221191e+00 7.35992968e-01 -1.27965048e-01
9.09994006e-01 -4.87388670e-01 -1.04344022e+00 6.26846433e-01
2.91134208e-01 4.42082316e-01 7.77210534e-01 -3.10974777e-01
-8.19464684e-01 -4.50601876e-01 -1.41569042e+00 3.34828436e-01
1.22298467e+00 -7.69029081e-01 -3.12916964e-01 -2.64409304e-01
3.25429976e-01 -4.54638898e-03 -8.69523406e-01 3.00329834e-01
5.60760736e-01 -8.33014965e-01 6.10847771e-01 -1.39007583e-01
4.63635415e-01 -3.42137039e-01 -3.68059963e-01 -1.07097924e+00
-2.54440159e-01 -4.34287488e-01 -1.55460630e-02 8.95393074e-01
6.11239731e-01 -7.64004469e-01 1.12724650e+00 5.54749548e-01
-4.56819773e-01 -7.20778048e-01 -1.25340533e+00 -7.43058681e-01
3.23971659e-01 -5.44305384e-01 -5.02276607e-02 6.20041847e-01
1.08260699e-01 -2.21797705e-01 2.45718747e-01 -4.83366586e-02
9.03475821e-01 -1.30764499e-01 2.59523958e-01 -1.25518477e+00
-6.94714561e-02 -7.86030889e-01 -6.96610093e-01 -8.34527075e-01
4.80623655e-02 -9.22262490e-01 6.96683764e-01 -1.20890009e+00
7.15000480e-02 -5.54214895e-01 -8.81320119e-01 9.60031211e-01
5.34456193e-01 8.66096079e-01 -2.77086437e-01 3.57115567e-01
-7.33284175e-01 2.34473750e-01 4.33776587e-01 -9.04791281e-02
2.98374984e-02 -4.10073608e-01 -4.26955879e-01 5.30810714e-01
1.44406772e+00 -8.39243114e-01 -1.68974906e-01 -6.89831078e-01
9.44899991e-02 -5.04343688e-01 3.12101871e-01 -1.75396311e+00
9.41764832e-01 1.95623145e-01 6.02551222e-01 -2.10814223e-01
3.18528265e-01 -4.30393606e-01 -3.82971764e-02 6.61200941e-01
-4.06562656e-01 5.99961765e-02 4.89213973e-01 5.85949302e-01
-1.52759269e-01 1.47523046e-01 1.11442947e+00 -2.02337265e-01
-8.44095170e-01 5.99988341e-01 -8.99991333e-01 1.15837686e-01
6.64510727e-01 -6.25593662e-01 -6.66801333e-01 2.91435301e-01
-5.47121942e-01 -9.87059101e-02 4.10077870e-01 7.65681267e-02
9.59210157e-01 -1.20309389e+00 -2.20801577e-01 4.32147324e-01
1.08722106e-01 9.95343849e-02 -3.46723795e-02 6.46069944e-01
-5.65426230e-01 1.90532610e-01 -9.11193192e-01 -8.24674606e-01
-5.99349976e-01 -1.44340247e-01 4.99488413e-01 3.56552333e-01
-2.67364770e-01 1.27060771e+00 -3.81650805e-01 -5.16624331e-01
3.51185173e-01 -3.39663804e-01 2.94576287e-01 -4.30485845e-01
4.31933761e-01 9.63306054e-02 5.24822026e-02 -2.23869905e-01
-4.94641036e-01 4.13540363e-01 7.33358189e-02 -2.67859697e-01
1.77175391e+00 3.07811469e-01 -5.28288484e-01 7.19554007e-01
1.28020406e+00 -7.94827461e-01 -1.67794418e+00 -3.57733577e-01
3.71727288e-01 1.18519664e-01 -3.27036887e-01 -9.05032635e-01
-1.27345872e+00 1.02973902e+00 8.17058325e-01 -1.11466810e-01
9.32802141e-01 1.84534639e-02 7.01692939e-01 8.46292496e-01
6.74618483e-01 -1.26070440e+00 3.47878456e-01 9.90450382e-01
3.76724631e-01 -9.76116359e-01 -6.51712000e-01 4.16907936e-01
-1.92286655e-01 1.15876830e+00 8.75921130e-01 -9.29165483e-01
1.08682191e+00 9.93475676e-01 2.26132870e-02 -1.48749128e-01
-8.28993380e-01 5.07186987e-02 -3.36899608e-01 7.82335401e-01
2.70059854e-01 -6.04541674e-02 6.13718890e-02 6.11522377e-01
-4.32561487e-02 3.49990308e-01 1.62940502e-01 1.25731266e+00
-8.96289885e-01 -9.12979007e-01 2.61948645e-01 8.29164505e-01
-2.27810815e-01 -4.87611681e-01 -3.93575847e-01 1.57032654e-01
2.86261737e-01 6.33404374e-01 4.24405694e-01 -8.21883202e-01
-1.50427133e-01 2.97646761e-01 4.35265332e-01 -5.53677082e-01
-6.77219808e-01 -1.78304642e-01 -6.30477428e-01 -6.83800101e-01
-4.11478609e-01 -5.04169762e-01 -2.01902652e+00 -3.12023848e-01
3.68269056e-01 -1.61494434e-01 1.02455783e+00 9.02431011e-01
6.96319580e-01 3.83655339e-01 3.80689740e-01 -8.94185543e-01
-3.86109166e-02 -7.53514349e-01 -8.33353043e-01 1.35457635e-01
-1.52709231e-01 -2.35694855e-01 -5.36451638e-01 1.75573096e-01] | [8.223857879638672, 2.4957525730133057] |
3adf992c-ac25-46ea-87f9-b120d59355dc | cfilt-iit-bombay-lt-edi-eacl2021-hope-speech | null | null | https://aclanthology.org/2021.ltedi-1.29 | https://aclanthology.org/2021.ltedi-1.29.pdf | CFILT IIT Bombay@LT-EDI-EACL2021: Hope Speech Detection for Equality, Diversity, and Inclusion using Multilingual Representation fromTransformers | With the internet becoming part and parcel of our lives, engagement in social media has increased a lot. Identifying and eliminating offensive content from social media has become of utmost priority to prevent any kind of violence. However, detecting encouraging, supportive and positive content is equally important to prevent misuse of censorship targeted to attack freedom of speech. This paper presents our system for the shared task Hope Speech Detection for Equality, Diversity, and Inclusion at LT-EDI, EACL 2021. The data for this shared task is provided in English, Tamil, and Malayalam which was collected from YouTube comments. It is a multiclass classification problem where each data instance is categorized into one of the three classes: ‘Hope speech’, ‘Not hope speech’, and ‘Not in intended language’. We propose a system that employs multilingual transformer models to obtain the representation of text and classifies it into one of the three classes. We explored the use of multilingual models trained specifically for Indian languages along with generic multilingual models. Our system was ranked 2nd for English, 2nd for Malayalam, and 7th for the Tamil language in the final leader board published by organizers and obtained a weighted F1-score of 0.92, 0.84, 0.55 respectively on the hidden test dataset used for the competition. We have made our system publicly available at GitHub. | ['Pushpak Bhattacharyya', 'Prince Kumar', 'Pankaj Singh'] | null | null | null | null | eacl-ltedi-2021-4 | ['hope-speech-detection'] | ['natural-language-processing'] | [-1.80904225e-01 2.76696295e-01 -3.71710926e-01 -1.76404729e-01
-1.13810694e+00 -7.19985843e-01 9.52076435e-01 2.06672236e-01
-5.89457154e-01 1.01325953e+00 6.82572246e-01 -6.02371335e-01
-1.07644901e-01 -4.06761199e-01 -3.60205412e-01 -3.02578360e-01
9.78517979e-02 4.26634192e-01 9.22879055e-02 -4.63933945e-01
2.40449816e-01 3.47204536e-01 -1.21479309e+00 7.18246281e-01
7.88234532e-01 6.34922743e-01 -4.66479689e-01 8.16821098e-01
-9.85465869e-02 1.16720629e+00 -6.90600276e-01 -8.58648777e-01
1.32344654e-02 -3.30234349e-01 -1.05809593e+00 -3.29034597e-01
4.61533129e-01 -1.92604139e-01 -4.26106572e-01 1.20292258e+00
6.87491298e-01 -1.51915535e-01 5.98774433e-01 -1.29953945e+00
-4.49565381e-01 9.63848472e-01 -5.18381000e-01 3.75038743e-01
3.84676874e-01 -4.11818832e-01 1.03723228e+00 -8.44015896e-01
7.86664426e-01 1.29117620e+00 3.69394064e-01 5.22265911e-01
-7.33937562e-01 -9.65157688e-01 -3.62674147e-01 2.72603214e-01
-1.38605046e+00 -7.88210511e-01 6.27257049e-01 -4.63877171e-01
8.13920259e-01 7.55759776e-01 4.25584167e-01 1.60070729e+00
8.20195451e-02 1.05129862e+00 1.29751360e+00 -3.75976682e-01
-2.04494417e-01 6.49687350e-01 1.69552192e-01 6.40448511e-01
-9.14142579e-02 -2.32927829e-01 -5.11577427e-01 -3.87889475e-01
-2.31007800e-01 -3.14495951e-01 -1.70839518e-01 2.85656869e-01
-8.77515256e-01 1.24155247e+00 -3.25130448e-02 4.96791810e-01
8.22064728e-02 -5.55019319e-01 6.29598975e-01 3.30709189e-01
8.57523263e-01 8.23848173e-02 -2.49172345e-01 -4.49049532e-01
-9.70370591e-01 1.10903300e-01 9.50800955e-01 5.61655521e-01
1.33908585e-01 -1.47791758e-01 -3.01701520e-02 1.42596984e+00
2.94136256e-01 6.28109872e-01 4.56788749e-01 -6.37018502e-01
7.45401382e-01 5.00264645e-01 -1.31497443e-01 -1.07850718e+00
-4.11264867e-01 -4.92257416e-01 -7.70516336e-01 -5.27611040e-02
2.86735535e-01 -3.50689501e-01 -6.50812030e-01 1.57174551e+00
1.84409529e-01 -2.62807697e-01 3.20064396e-01 5.04464090e-01
1.03034258e+00 8.80171835e-01 -5.36657237e-02 -2.65476137e-01
1.15288949e+00 -7.87729204e-01 -7.24545062e-01 2.62246225e-02
7.04032540e-01 -1.18699050e+00 6.56724811e-01 6.23232722e-01
-8.66617858e-01 2.81106457e-02 -9.03629899e-01 -1.41605660e-01
-6.18685484e-01 6.28179172e-03 6.92333877e-02 9.38675880e-01
-8.00331712e-01 3.70135248e-01 -2.14618176e-01 -6.07471526e-01
4.31772053e-01 4.00749147e-02 -6.79333448e-01 1.80201560e-01
-1.52159977e+00 8.82737756e-01 1.91607580e-01 -2.65796095e-01
-7.41881788e-01 2.20115762e-03 -6.22955441e-01 -3.56704712e-01
1.28625967e-02 5.14783859e-01 8.05124998e-01 -8.56368959e-01
-1.10314500e+00 1.20577860e+00 2.17213616e-01 -3.70437413e-01
6.96021438e-01 -2.44232684e-01 -9.55217481e-01 -1.62746221e-01
3.27449173e-01 3.44678253e-01 7.15484202e-01 -8.29465270e-01
-8.72678518e-01 -3.74165207e-01 1.76554057e-03 -3.12599652e-02
-8.24772775e-01 7.12259352e-01 -6.82870820e-02 -6.14958167e-01
-1.79973990e-01 -1.06594980e+00 3.91620845e-01 -6.57436073e-01
-7.91315436e-01 -2.96119362e-01 1.23988020e+00 -1.44822061e+00
1.62339425e+00 -2.14015007e+00 3.57041880e-02 1.52312845e-01
8.00863877e-02 3.75706941e-01 3.11405480e-01 5.87745845e-01
-1.10137939e-01 5.52635252e-01 3.73425166e-04 -2.35381633e-01
-7.39646927e-02 3.57448962e-03 -3.36888433e-01 6.20459855e-01
-1.66860595e-01 2.28301242e-01 -8.05333197e-01 -5.17008901e-01
-1.83714807e-01 5.13638854e-01 -4.86842811e-01 -2.76757274e-02
4.92210269e-01 3.74632448e-01 -3.26976478e-01 6.23936117e-01
4.69300061e-01 2.39516348e-01 1.24357805e-01 4.53920700e-02
-5.18457890e-01 3.85625720e-01 -8.36238384e-01 8.79757404e-01
-3.60437751e-01 9.56131697e-01 2.29118615e-01 -6.76692724e-01
9.83135343e-01 5.07511199e-01 3.00223649e-01 -7.04672337e-01
3.10530931e-01 5.01115263e-01 7.41928741e-02 -4.93054211e-01
5.58772683e-01 3.62011269e-02 -4.07470763e-01 3.34587485e-01
-9.58798081e-02 2.09876850e-01 2.06537873e-01 5.60061932e-01
8.89898062e-01 -3.59110713e-01 3.25430125e-01 -3.03285122e-01
7.45544732e-01 -2.90162444e-01 2.91430831e-01 5.97234190e-01
-5.75923741e-01 4.76996839e-01 7.24692166e-01 -2.22666621e-01
-1.03768599e+00 -8.42216551e-01 -2.87680268e-01 1.32749915e+00
-4.38064456e-01 -5.63322306e-01 -5.12541056e-01 -9.05048788e-01
-4.38726723e-01 1.02567816e+00 -4.45429742e-01 -1.80228353e-01
-3.97787988e-01 -5.63469291e-01 1.03636003e+00 -2.58730352e-01
6.69365406e-01 -9.15699422e-01 -1.74301788e-01 -1.34984165e-01
-7.15427995e-01 -1.01948285e+00 -3.53191376e-01 1.34205282e-01
-1.00530744e-01 -1.07066607e+00 -7.53639042e-01 -6.58684850e-01
1.24146625e-01 -6.88203052e-02 5.37374139e-01 -1.44316301e-01
-1.40157506e-01 4.81497198e-02 -6.16206288e-01 -5.05049586e-01
-6.84332669e-01 3.14478815e-01 -2.05299184e-02 2.61413574e-01
1.75046816e-01 -2.46045917e-01 -9.30820480e-02 2.48382747e-01
-6.48253262e-01 -1.80270746e-02 1.20531648e-01 6.40951753e-01
-1.72219977e-01 -8.88477359e-03 5.70536196e-01 -1.13655388e+00
8.51309597e-01 -8.92252326e-01 -1.75191518e-02 -1.83781832e-02
-2.40462288e-01 -3.68926883e-01 5.33189535e-01 -1.34814888e-01
-9.00156558e-01 -2.86188543e-01 -5.49886346e-01 -2.88591981e-02
7.16735423e-02 4.88439351e-01 -1.74404085e-01 2.54159689e-01
5.85168660e-01 3.25680524e-02 -2.90967941e-01 -5.44275582e-01
6.09136112e-02 1.48539901e+00 1.70259774e-01 -3.18367630e-01
5.21905124e-01 2.52927840e-01 -5.12822568e-01 -1.38641453e+00
-9.21091437e-01 -6.50472105e-01 -3.74936551e-01 -5.39029181e-01
9.69879150e-01 -7.84031928e-01 -5.00771999e-01 6.45739853e-01
-1.10343897e+00 1.15361392e-01 1.65936187e-01 3.46094817e-01
6.02121204e-02 4.49086219e-01 -5.87206066e-01 -9.89428937e-01
-5.31618237e-01 -9.75570440e-01 7.60752618e-01 -2.02740848e-01
-3.81290883e-01 -9.29107249e-01 1.71054259e-01 8.85658860e-01
3.84050727e-01 3.60188663e-01 8.74072731e-01 -1.39490891e+00
4.06835735e-01 -5.58439076e-01 -1.28291503e-01 6.87619567e-01
1.02410018e-01 1.57653302e-01 -9.85856473e-01 -3.13167691e-01
1.51410913e-02 -7.82084525e-01 7.50290990e-01 -1.46568134e-01
7.86225021e-01 -8.33866298e-01 -6.30440041e-02 1.21881366e-02
8.62729192e-01 1.36729687e-01 7.18910635e-01 4.23116744e-01
6.82128251e-01 7.02212572e-01 3.76531452e-01 5.53722262e-01
3.25797558e-01 6.65786743e-01 3.02689642e-01 1.36218503e-01
-1.65939592e-02 -3.95325124e-01 6.67252183e-01 1.08718181e+00
1.21707521e-01 -2.94980139e-01 -1.19574475e+00 6.28526568e-01
-1.48319316e+00 -1.36614048e+00 -4.17913675e-01 2.27423549e+00
8.65840077e-01 3.52183580e-01 4.47439462e-01 4.90020186e-01
8.70087206e-01 3.17163676e-01 2.21626520e-01 -9.17996645e-01
-2.93425739e-01 -2.35251859e-02 5.67347527e-01 8.29755902e-01
-1.43056846e+00 9.70369339e-01 5.01564360e+00 1.09199643e+00
-1.22311950e+00 5.13591409e-01 7.92967677e-01 -1.15388885e-01
-7.47638345e-02 -5.23777418e-02 -1.05109632e+00 6.76707745e-01
1.34213841e+00 -1.69918567e-01 2.56290942e-01 7.23695874e-01
2.38119632e-01 1.64244071e-01 -4.91583675e-01 8.82705033e-01
3.77733409e-01 -1.04191399e+00 3.84310000e-02 2.94746518e-01
5.95128119e-01 4.31088269e-01 1.92495942e-01 4.69929248e-01
3.32888514e-01 -9.96722639e-01 9.77687359e-01 1.70352772e-01
6.36702716e-01 -9.51810002e-01 6.47996068e-01 7.86063612e-01
-6.43260002e-01 -1.76155090e-01 -5.78111447e-02 1.40546918e-01
-5.94442450e-02 2.45148227e-01 -7.45541990e-01 3.14224511e-01
8.01154613e-01 8.14497352e-01 -6.26494408e-01 7.08560050e-01
-2.11499974e-01 9.47126508e-01 -3.26137513e-01 -2.51415521e-01
4.74341720e-01 2.27460012e-01 8.96531105e-01 1.45154655e+00
3.11201662e-01 -1.31257057e-01 2.25627109e-01 -4.24862057e-02
-2.02134460e-01 5.75947285e-01 -8.33661854e-01 -2.35391498e-01
2.42063925e-01 1.17086828e+00 -4.52386856e-01 -2.30993524e-01
-3.68765503e-01 8.39936435e-01 2.75914073e-01 -4.28632274e-02
-9.35899615e-01 -5.76847970e-01 4.73508909e-02 2.55235702e-01
-2.08944380e-01 5.18810675e-02 5.80767468e-02 -1.14202404e+00
-2.70734340e-01 -1.24452412e+00 6.95531487e-01 -3.76333416e-01
-1.08212054e+00 8.45706522e-01 -2.70049553e-02 -1.11008060e+00
-1.95599452e-01 -5.46247065e-01 -2.21933767e-01 6.84581339e-01
-1.07401371e+00 -1.12659979e+00 1.90945968e-01 7.76549757e-01
6.98027909e-01 -5.68349779e-01 6.92782819e-01 8.23445380e-01
-6.44811809e-01 7.23029196e-01 2.49708429e-01 4.92655039e-01
8.11624050e-01 -8.21380079e-01 -1.42315505e-02 7.13691354e-01
1.89155638e-01 3.89792353e-01 7.71477461e-01 -6.58903062e-01
-7.31817544e-01 -1.14947462e+00 1.62985182e+00 -4.58540708e-01
1.04947531e+00 -4.56415951e-01 -6.34198725e-01 6.87022686e-01
4.15957510e-01 -5.95808566e-01 9.43514884e-01 1.07966885e-01
-4.80954498e-01 7.64504299e-02 -1.20608211e+00 4.44191247e-01
6.98563278e-01 -6.60650730e-01 -3.95188898e-01 7.65107870e-01
1.84753582e-01 -2.13078156e-01 -5.94269216e-01 1.52845923e-02
6.01776659e-01 -8.94233108e-01 5.34305990e-01 -7.88453519e-01
6.99976146e-01 2.98643023e-01 -5.00517428e-01 -1.12847853e+00
-7.93669075e-02 -4.97739851e-01 1.99102134e-01 1.54997039e+00
7.94890523e-01 -6.70553923e-01 5.61313510e-01 2.53629416e-01
-4.92073931e-02 -4.35050219e-01 -1.32475638e+00 -5.57798982e-01
2.91446090e-01 -5.31463921e-01 -9.42243934e-02 1.24884093e+00
1.95312992e-01 8.66423428e-01 -1.07461500e+00 -1.50401622e-01
6.01220787e-01 -5.24694324e-01 6.71352386e-01 -1.17344975e+00
4.68059331e-02 -4.45498019e-01 -3.19788903e-01 -3.76177788e-01
2.51519710e-01 -1.36127687e+00 -4.64693159e-01 -1.37107909e+00
3.86083513e-01 -1.63365021e-01 -6.57755062e-02 6.53576434e-01
3.86159778e-01 4.33000833e-01 2.73383588e-01 4.15512830e-01
-4.99868453e-01 2.99154371e-01 6.65789485e-01 -3.64222556e-01
6.81574419e-02 2.38850936e-01 -8.28162491e-01 7.76500404e-01
9.60980237e-01 -6.96038306e-01 -1.82975322e-01 -2.00687096e-01
3.70512336e-01 -6.98721930e-02 1.69866160e-01 -9.16228831e-01
1.14753274e-02 -2.36562621e-02 8.58293474e-02 -5.82544684e-01
3.82950604e-01 -7.08561003e-01 -3.03705875e-02 5.51897466e-01
-5.95595300e-01 -1.79802150e-01 -8.86595156e-03 1.72383800e-01
-2.56314099e-01 -2.11575031e-01 8.74060988e-01 3.87451537e-02
-2.71867365e-01 -3.47028896e-02 -4.80747879e-01 3.04765850e-01
9.07824516e-01 8.39309767e-02 -5.18335879e-01 -7.25448072e-01
-9.40094531e-01 7.90636614e-02 -6.50038719e-02 7.94248104e-01
5.72932184e-01 -1.25352788e+00 -1.33830893e+00 4.61764336e-02
1.26502901e-01 -1.12410545e+00 1.80703327e-02 8.26681137e-01
-4.08055365e-01 4.80107754e-01 -1.48228556e-01 -2.56859452e-01
-1.60235178e+00 3.69243771e-02 9.13463458e-02 -3.72234613e-01
-1.94816142e-01 6.65718973e-01 -3.24499607e-01 -6.89136684e-01
2.29652345e-01 4.13138151e-01 -7.11001992e-01 3.69334728e-01
6.18432939e-01 7.27632642e-01 8.63403827e-02 -1.40351307e+00
-4.61588889e-01 3.54402103e-02 -3.91388714e-01 -2.85021484e-01
1.24491310e+00 -1.84576232e-02 -3.52732420e-01 6.12527549e-01
1.60810947e+00 6.23308957e-01 -1.58079877e-01 1.40174627e-01
3.12470868e-02 -3.87349367e-01 1.00393631e-01 -1.05027604e+00
-8.95807803e-01 8.31138432e-01 5.19991457e-01 6.40919626e-01
6.71918273e-01 2.93927062e-02 7.87808418e-01 2.10433483e-01
2.06336856e-01 -1.18193817e+00 -1.26527801e-01 8.42599094e-01
1.25432849e+00 -1.23769295e+00 -1.49326503e-01 -1.68684661e-01
-7.69648015e-01 9.09646630e-01 2.16926917e-01 2.10710943e-01
8.44601512e-01 -4.19328734e-02 1.42509356e-01 3.01269162e-02
-6.19721830e-01 1.80004641e-01 2.58664459e-01 2.64624804e-01
7.39571512e-01 1.91110447e-01 -8.00596833e-01 4.37434822e-01
-3.94464850e-01 -4.31604832e-01 5.98589242e-01 7.33469784e-01
-5.87760687e-01 -9.48753417e-01 -2.67375022e-01 5.22336304e-01
-1.26539969e+00 -1.36807591e-01 -8.53603244e-01 8.20243239e-01
9.39095691e-02 1.21249461e+00 -3.59225988e-01 -6.50535405e-01
2.96175092e-01 1.70571342e-01 -1.91539913e-01 -4.46823329e-01
-6.85203493e-01 1.51211962e-01 8.39536250e-01 -1.88768536e-01
-9.30364579e-02 -7.56223440e-01 -8.26045394e-01 -5.13370156e-01
-6.38147295e-02 4.79673624e-01 8.64940822e-01 7.60937095e-01
1.81516558e-02 6.32467195e-02 7.60125399e-01 -3.55099440e-01
-4.20256525e-01 -9.69086528e-01 -4.37158883e-01 4.18158948e-01
3.15012187e-01 -3.49226743e-01 -5.69672763e-01 -2.99199343e-01] | [8.988812446594238, 10.631540298461914] |
c3f59511-3314-4083-ae07-15fc3732be64 | interpreting-deep-urban-sound-classification | 2111.10235 | null | https://arxiv.org/abs/2111.10235v1 | https://arxiv.org/pdf/2111.10235v1.pdf | Interpreting deep urban sound classification using Layer-wise Relevance Propagation | After constructing a deep neural network for urban sound classification, this work focuses on the sensitive application of assisting drivers suffering from hearing loss. As such, clear etiology justifying and interpreting model predictions comprise a strong requirement. To this end, we used two different representations of audio signals, i.e. Mel and constant-Q spectrograms, while the decisions made by the deep neural network are explained via layer-wise relevance propagation. At the same time, frequency content assigned with high relevance in both feature sets, indicates extremely discriminative information characterizing the present classification task. Overall, we present an explainable AI framework for understanding deep urban sound classification. | ['Stavros Ntalampiras', 'Marco Colussi'] | 2021-11-19 | null | null | null | null | ['sound-classification'] | ['audio'] | [ 2.21102446e-01 1.95215896e-01 2.95905083e-01 -6.47947431e-01
-7.71956444e-01 3.38151725e-03 2.18325734e-01 2.09094822e-01
-1.32645771e-01 6.24183536e-01 4.35037553e-01 -4.53668594e-01
-3.91563714e-01 -9.02343094e-01 -5.82465529e-01 -5.48598468e-01
-4.55438383e-02 -6.05590865e-02 -4.53800596e-02 -3.72027338e-01
1.96719915e-01 3.37413430e-01 -2.10442567e+00 5.44523478e-01
6.18117929e-01 1.48316693e+00 1.60528004e-01 8.62096250e-01
7.05948239e-03 1.02754772e+00 -7.52567410e-01 -3.69026005e-01
-1.62069798e-01 -2.93051064e-01 -7.17615187e-01 -5.44647753e-01
1.92764491e-01 -2.45881557e-01 -5.61624885e-01 9.69335675e-01
6.65940106e-01 2.64223158e-01 7.48439014e-01 -1.40181303e+00
-6.02757990e-01 9.36897874e-01 1.61495864e-01 2.79592216e-01
2.60538548e-01 2.10819632e-01 1.39054763e+00 -8.82830858e-01
-2.87361056e-01 1.08772075e+00 6.22279882e-01 5.57097137e-01
-7.28997767e-01 -7.08322227e-01 3.39138716e-01 8.16875875e-01
-1.26027012e+00 -6.61030173e-01 1.29184759e+00 -5.82970977e-01
8.53953302e-01 6.06392622e-01 7.99979448e-01 1.13751137e+00
2.98875421e-01 8.40789676e-01 6.11222982e-01 -1.79037884e-01
3.66126269e-01 7.29138851e-02 3.53929609e-01 1.92551523e-01
7.40822330e-02 1.94104388e-01 -7.63247192e-01 4.04513590e-02
-6.30430207e-02 -2.68042743e-01 -1.17885523e-01 4.96354669e-01
-6.50996506e-01 6.05265737e-01 5.47159374e-01 1.18509904e-01
-5.58687210e-01 6.67747617e-01 3.69509071e-01 5.02818003e-02
4.60960656e-01 3.18066061e-01 -2.66569883e-01 -1.46970108e-01
-6.69824362e-01 2.86177069e-01 3.37101936e-01 4.78595227e-01
6.64209783e-01 5.40550590e-01 -9.57682878e-02 7.80375540e-01
5.90499222e-01 4.98677254e-01 2.71194339e-01 -6.81070447e-01
2.18415990e-01 1.26987278e-01 -1.30079865e-01 -1.10065591e+00
-6.20713472e-01 -9.42404747e-01 -7.58025885e-01 1.06427632e-01
-1.14859287e-02 -1.66456282e-01 -8.63616109e-01 1.80692375e+00
-2.14973062e-01 3.91361356e-01 2.77792513e-01 8.55246484e-01
1.05983603e+00 6.90683424e-01 3.99495691e-01 1.83526203e-01
1.33681047e+00 -5.67635655e-01 -1.01160932e+00 -4.41781789e-01
1.49824321e-01 -5.64406157e-01 9.85888422e-01 4.12612975e-01
-9.20209825e-01 -1.04390574e+00 -1.15422106e+00 -1.34223506e-01
-4.66224015e-01 4.20648865e-02 6.62540913e-01 5.50743997e-01
-9.42378163e-01 2.55164087e-01 -3.65531743e-01 2.28312373e-01
3.92615080e-01 2.36805722e-01 1.30853653e-01 1.32370055e-01
-1.76444113e+00 7.85658956e-01 1.83067232e-01 5.95176578e-01
-9.24256206e-01 -8.55943978e-01 -7.00806916e-01 3.14734459e-01
-4.01891857e-01 -7.13264227e-01 1.51397121e+00 -5.29105186e-01
-1.21540749e+00 5.90737939e-01 -3.39402914e-01 -8.69666994e-01
3.01638424e-01 -4.65311885e-01 -9.49428797e-01 -2.32780762e-02
-1.16330326e-01 5.84100723e-01 8.82899880e-01 -1.37023568e+00
-9.18817580e-01 -9.57351103e-02 1.19100310e-01 1.16307531e-02
-3.13439459e-01 -6.68466985e-02 3.25134218e-01 -5.58015227e-01
1.24086626e-01 -5.13811529e-01 -1.56537727e-01 -2.24377468e-01
-5.77805758e-01 -3.52499694e-01 5.90224087e-01 -8.69048119e-01
1.50947475e+00 -2.26773238e+00 -3.16414297e-01 2.96520799e-01
4.52383608e-01 1.74719878e-02 -3.70254405e-02 2.21568763e-01
-1.61816120e-01 1.03950799e-01 -3.08726549e-01 -2.36867100e-01
3.76706988e-01 -2.14983243e-02 -7.65671849e-01 1.20306194e-01
4.32704091e-01 7.72231698e-01 -7.72360861e-01 -1.76354691e-01
1.03171185e-01 6.11171067e-01 -8.39331210e-01 1.44037738e-01
2.86917463e-02 3.01829338e-01 -4.88110363e-01 5.22021770e-01
5.25869191e-01 3.55423003e-01 -3.99014920e-01 -2.80862272e-01
-1.29669100e-01 6.06501877e-01 -8.09649527e-01 1.25066721e+00
-8.23860347e-01 1.22870934e+00 -6.89522997e-02 -1.11755061e+00
1.12728512e+00 4.51503873e-01 3.31378609e-01 -8.09945226e-01
1.59646660e-01 3.12466085e-01 3.45255047e-01 -6.54855430e-01
6.46093369e-01 -2.57245928e-01 -3.01639512e-02 1.83002472e-01
-2.63457686e-01 -1.11446254e-01 -5.81107974e-01 -3.01683933e-01
7.33221889e-01 -3.40209544e-01 -6.14674129e-02 4.71304811e-04
5.04057288e-01 -4.22365636e-01 4.92437154e-01 6.23920023e-01
-5.35694659e-01 5.64130723e-01 2.24348307e-01 -4.92237270e-01
-4.58388358e-01 -9.27284241e-01 -5.48452079e-01 1.17887831e+00
1.87228277e-01 -2.68341482e-01 -5.64628422e-01 -2.44792134e-01
2.42057759e-02 1.21230865e+00 -6.49603307e-01 -8.38558137e-01
-5.46128571e-01 -3.86967182e-01 8.86711955e-01 7.56410122e-01
3.62195760e-01 -1.12678576e+00 -7.54504979e-01 3.50081354e-01
-4.33728337e-01 -9.11126494e-01 1.26000628e-01 5.56568086e-01
-1.91671953e-01 -6.00127220e-01 -3.71417731e-01 -9.64594543e-01
2.77820192e-02 1.78432256e-01 1.15453839e+00 -1.30621288e-02
-2.85701990e-01 2.35844746e-01 -2.31489092e-01 -1.08828151e+00
-2.34495535e-01 -2.30655313e-01 2.28232265e-01 2.86264807e-01
4.74831492e-01 -7.40401864e-01 -7.48743355e-01 7.46103600e-02
-6.18336856e-01 -1.69890597e-02 5.47989070e-01 6.24699056e-01
4.71620172e-01 3.08617055e-01 1.06994987e+00 -2.09431544e-01
9.44677472e-01 -5.54403782e-01 1.97264969e-01 9.94555429e-02
-1.08463407e-01 -1.49359241e-01 7.01968491e-01 -1.36092231e-01
-1.02023625e+00 -7.82974064e-02 -8.92429292e-01 -8.05364624e-02
-6.76108837e-01 6.01221561e-01 -3.75668526e-01 4.07493770e-01
8.26673508e-01 2.47882351e-01 -4.41978902e-01 -4.75000590e-01
3.46946299e-01 1.05990314e+00 6.65347278e-01 -2.25493759e-01
6.40867054e-01 2.86716402e-01 -1.51581287e-01 -9.50063348e-01
-7.80981064e-01 -1.73226193e-01 -3.32181573e-01 -4.97816056e-01
1.00416183e+00 -7.45801866e-01 -7.29856074e-01 4.81930137e-01
-1.37621689e+00 -6.26110099e-03 -4.41509664e-01 7.15997219e-01
-6.63434982e-01 -2.66664177e-01 -1.21385753e-01 -1.46103418e+00
-1.34653226e-01 -1.14367068e+00 1.06868160e+00 5.14520481e-02
-4.77753729e-01 -7.89306283e-01 -1.90308630e-01 3.86873662e-01
5.81274629e-01 8.20986629e-02 1.22368145e+00 -5.41292250e-01
-3.20786625e-01 -2.44933069e-01 -1.34645939e-01 2.67481118e-01
1.22654691e-01 -2.25089751e-02 -2.00671101e+00 3.84315133e-01
-4.43727709e-02 -1.48217425e-01 1.27356434e+00 7.34059870e-01
1.74826670e+00 -2.61281371e-01 6.65397290e-03 5.13707280e-01
6.81955695e-01 4.95582700e-01 5.99185050e-01 1.34054899e-01
4.75988477e-01 8.97549808e-01 5.90446949e-01 4.57271576e-01
4.99128133e-01 5.30466795e-01 7.80436039e-01 -2.28926674e-01
-3.83225143e-01 -4.85126883e-01 2.66027510e-01 7.19008327e-01
-2.72738934e-02 -3.21935862e-01 -9.41627324e-01 6.21949196e-01
-1.67342782e+00 -1.06030512e+00 -1.72354504e-01 1.69499898e+00
5.61248899e-01 4.48767662e-01 -1.12070419e-01 9.80379164e-01
5.97551584e-01 2.11086884e-01 -6.47658408e-01 -3.81475359e-01
-1.10263444e-01 2.14752272e-01 -3.79454531e-03 6.92548692e-01
-1.25621855e+00 8.68188381e-01 6.69021273e+00 8.87115121e-01
-1.26642334e+00 -2.64134794e-01 7.18682468e-01 6.24311604e-02
-6.55594707e-01 -4.21446294e-01 -5.34887016e-01 2.86370486e-01
1.20608568e+00 -1.11118212e-01 2.68330306e-01 7.64841318e-01
4.87329572e-01 3.26157510e-01 -1.04221094e+00 1.04837584e+00
-2.43413746e-01 -1.10254490e+00 2.45127976e-01 -1.64887264e-01
1.64531097e-01 -2.87224352e-01 7.19684184e-01 3.17415506e-01
-6.91120327e-02 -1.26603186e+00 1.34960616e+00 7.64581561e-01
6.77101254e-01 -9.80892658e-01 7.55873919e-01 8.27581584e-02
-1.31719160e+00 -4.55858886e-01 -5.53567946e-01 -3.74487162e-01
1.67713806e-01 7.34361410e-01 -9.43560660e-01 3.18411589e-01
6.15686834e-01 5.96918702e-01 -3.72143507e-01 1.00529647e+00
-3.77023011e-01 1.18892086e+00 -3.21077704e-02 -4.55636904e-02
8.00899714e-02 4.35998708e-01 5.39004862e-01 1.38984966e+00
3.46410811e-01 1.29188243e-02 -2.45466664e-01 9.57286060e-01
1.87002912e-01 -1.03885815e-01 -7.09778845e-01 2.07867756e-01
5.06872714e-01 8.25562000e-01 -2.36928448e-01 3.21029536e-02
-1.07571194e-02 3.78521860e-01 -1.95636358e-02 5.77797890e-01
-9.65543985e-01 -6.26751184e-01 1.31520998e+00 6.02719784e-02
-8.29086900e-02 -1.64797097e-01 -8.82135749e-01 -5.39036870e-01
-2.42337342e-02 -3.21217746e-01 1.05997678e-02 -8.26167762e-01
-1.08908260e+00 9.18425918e-01 -1.66663304e-01 -1.50776768e+00
-3.13595057e-01 -5.89221776e-01 -8.64292324e-01 1.01923203e+00
-2.21734190e+00 -1.12145615e+00 -3.24521095e-01 5.13248265e-01
5.10093808e-01 -2.23749965e-01 8.94269168e-01 4.66418177e-01
-5.00509083e-01 8.92370701e-01 -3.96261424e-01 9.67056230e-02
2.65424281e-01 -9.95118260e-01 6.50674582e-01 5.82390964e-01
2.94501781e-01 5.34103990e-01 8.55275333e-01 -2.31180176e-01
-9.85097826e-01 -1.30447757e+00 1.04524791e+00 -2.78308570e-01
5.87692380e-01 -1.52814999e-01 -9.05148208e-01 1.43424407e-01
3.29632033e-03 -2.17831150e-01 1.03600693e+00 1.64941490e-01
-1.25412837e-01 -3.78595263e-01 -8.79128933e-01 4.48706061e-01
1.06102061e+00 -1.03600574e+00 -6.80415452e-01 1.57096237e-01
9.12236035e-01 2.35081203e-02 -4.80586648e-01 3.69320869e-01
6.80238962e-01 -8.56434464e-01 1.23481286e+00 -8.75875711e-01
5.16136348e-01 -3.53892714e-01 -6.34436369e-01 -1.39664567e+00
-5.30159473e-01 -1.92166135e-01 -1.63627163e-01 1.00397432e+00
6.58563018e-01 -5.75226188e-01 4.70241427e-01 5.07117450e-01
-7.51832604e-01 -7.46255696e-01 -1.23758674e+00 -3.92468274e-01
-4.18082327e-02 -1.36355507e+00 9.92861092e-01 4.99676645e-01
-1.43955350e-01 1.53529495e-01 -5.57338297e-01 5.28834641e-01
3.63687456e-01 -1.42502904e-01 3.41566354e-01 -1.56449592e+00
-1.34063199e-01 -6.91294253e-01 -8.13293099e-01 -1.11311269e+00
3.51158321e-01 -8.84340346e-01 3.82678539e-01 -1.70599031e+00
-4.34859842e-01 -4.76890147e-01 -8.57089818e-01 4.14047360e-01
-2.59224623e-01 3.87535214e-01 1.87291224e-02 -5.79148084e-02
-8.40009302e-02 8.13107550e-01 9.75161195e-01 -4.93988752e-01
-4.85687703e-02 4.82735932e-01 -9.84904826e-01 1.03806221e+00
1.08877003e+00 -1.59759119e-01 -4.42330003e-01 -6.65375233e-01
3.08476210e-01 -1.69863063e-03 6.92701042e-01 -1.30882418e+00
1.78787261e-01 -2.28454039e-01 1.94876567e-01 -5.83368838e-01
7.15266705e-01 -8.98806691e-01 -2.05804303e-01 4.28791940e-01
-9.13634181e-01 -4.40396369e-01 3.07014763e-01 6.77126825e-01
-5.75900197e-01 1.48823028e-02 6.28372431e-01 3.81900966e-01
-9.90580380e-01 1.72410175e-01 -7.27347374e-01 -2.62078613e-01
5.99925756e-01 -3.78965020e-01 -1.85107246e-01 -8.15865040e-01
-9.72942770e-01 -1.17354654e-01 -6.51443839e-01 6.74497724e-01
1.02841914e+00 -1.50469577e+00 -8.67456436e-01 5.04118621e-01
2.17009947e-01 -3.05324972e-01 5.75113058e-01 4.23313558e-01
-5.75014018e-02 5.16447902e-01 -1.42252386e-01 -5.54421902e-01
-9.60952520e-01 7.36826146e-03 5.35738766e-01 4.07355845e-01
-4.24775988e-01 1.27734947e+00 5.79842865e-01 -7.00748190e-02
6.02926672e-01 -9.11661506e-01 -7.70677567e-01 2.01165527e-01
6.48796916e-01 3.09341162e-01 3.55793834e-01 -7.85044730e-01
-5.15055597e-01 4.75604445e-01 4.66818243e-01 -1.61311433e-01
1.27153492e+00 -8.44665393e-02 3.41943026e-01 7.06358850e-01
1.09691942e+00 3.22548975e-03 -1.07233596e+00 6.16108514e-02
-1.83096603e-01 -1.87389836e-01 3.69147420e-01 -8.84262860e-01
-9.93091047e-01 1.48599041e+00 8.33343983e-01 4.93913859e-01
1.22780037e+00 -5.95403388e-02 8.76819432e-01 5.33021986e-01
2.94951145e-02 -9.88391578e-01 -2.48107389e-01 5.91256499e-01
1.19575202e+00 -1.06386673e+00 -5.06576002e-01 -1.40640676e-01
-6.07209802e-01 1.09815395e+00 5.17211020e-01 2.31305122e-01
9.47568595e-01 1.17117248e-01 2.98797816e-01 -8.92522279e-03
-7.99749196e-01 -5.09514034e-01 7.04980850e-01 7.65975595e-01
4.85732585e-01 4.38188940e-01 1.60803229e-01 1.29857051e+00
-9.94290650e-01 -4.54777420e-01 8.24476853e-02 5.06946743e-01
-8.55411470e-01 -4.30198848e-01 -4.21545893e-01 4.46943313e-01
-2.19526082e-01 -1.07509553e-01 -4.98403579e-01 2.07975239e-01
3.32022339e-01 1.50437248e+00 6.42408058e-02 -1.10238564e+00
5.53443074e-01 1.63152605e-01 -2.72327542e-01 -2.83985674e-01
-4.16273683e-01 -2.50756025e-01 2.53356606e-01 -1.45864159e-01
-1.15878440e-01 -2.59946018e-01 -1.41893363e+00 7.13836551e-02
-1.95057333e-01 2.28513360e-01 6.24394357e-01 9.03719723e-01
1.59687862e-01 1.19098389e+00 8.03797722e-01 -8.25232744e-01
-3.16897720e-01 -9.59488332e-01 -6.03547812e-01 1.33918524e-01
8.30663681e-01 -6.54886305e-01 -3.45183969e-01 1.89753342e-02] | [15.184419631958008, 5.2258100509643555] |
8de1f18e-041d-4572-aab6-8c8b2ca2aaed | all-you-need-is-boundary-toward-arbitrary | 1911.09550 | null | https://arxiv.org/abs/1911.09550v1 | https://arxiv.org/pdf/1911.09550v1.pdf | All You Need Is Boundary: Toward Arbitrary-Shaped Text Spotting | Recently, end-to-end text spotting that aims to detect and recognize text from cluttered images simultaneously has received particularly growing interest in computer vision. Different from the existing approaches that formulate text detection as bounding box extraction or instance segmentation, we localize a set of points on the boundary of each text instance. With the representation of such boundary points, we establish a simple yet effective scheme for end-to-end text spotting, which can read the text of arbitrary shapes. Experiments on three challenging datasets, including ICDAR2015, TotalText and COCO-Text demonstrate that the proposed method consistently surpasses the state-of-the-art in both scene text detection and end-to-end text recognition tasks. | ['Mengchao He', 'Yongchao Xu', 'HUI ZHANG', 'Mingkun Yang', 'Wenyu Liu', 'Hao Wang', 'Yongpan Wang', 'Xiang Bai', 'Pu Lu'] | 2019-11-21 | null | null | null | null | ['text-spotting'] | ['computer-vision'] | [ 4.91056651e-01 -5.11959732e-01 1.33896157e-01 -3.30873132e-01
-9.39494312e-01 -8.29190731e-01 7.94889748e-01 1.72468379e-01
-3.64956260e-01 9.22531039e-02 -1.27784297e-01 -2.47197941e-01
2.25316063e-01 -4.01244044e-01 -6.31172121e-01 -4.08468395e-01
6.96971595e-01 8.69164407e-01 3.03576261e-01 2.95932591e-01
6.73076332e-01 1.80089816e-01 -1.27751148e+00 5.57426810e-01
1.01210713e+00 9.20780659e-01 3.43394846e-01 8.58462751e-01
-6.85544491e-01 4.13597137e-01 -6.02342546e-01 -6.51820660e-01
-1.64976101e-02 -1.88102737e-01 -6.98712945e-01 7.27246881e-01
1.09301734e+00 -2.80246288e-01 -5.99887490e-01 1.02676821e+00
5.16483903e-01 -2.23734140e-01 9.44346368e-01 -7.04976559e-01
-5.85874677e-01 5.16718507e-01 -1.05301642e+00 2.36244779e-02
4.54646826e-01 -1.15357652e-01 9.37176108e-01 -1.54917729e+00
5.48020720e-01 1.12253356e+00 5.43292582e-01 2.80222654e-01
-9.93639231e-01 -4.74429756e-01 3.70181412e-01 -1.14248492e-01
-1.47540736e+00 -4.84223336e-01 6.50311649e-01 -5.09668291e-01
6.84214115e-01 3.93522382e-01 2.44673043e-01 9.78927016e-01
-4.44292538e-02 1.76864517e+00 7.05599427e-01 -7.19547033e-01
-2.88062543e-02 -1.04147620e-01 3.51167172e-01 8.69489849e-01
2.78953522e-01 -4.95764405e-01 -7.11917639e-01 -8.48514028e-03
5.00418007e-01 8.41519013e-02 -2.21607134e-01 -2.18779311e-01
-1.51415658e+00 4.64271039e-01 -1.21031329e-01 1.51527733e-01
1.79711860e-02 -2.17138324e-02 6.98511064e-01 -1.60951465e-01
6.55166447e-01 -7.59581178e-02 -1.91753030e-01 -7.48931319e-02
-1.66745281e+00 4.09522876e-02 7.31046081e-01 1.15006614e+00
1.72149599e-01 9.91351530e-03 -4.92085904e-01 1.07551396e+00
2.91458756e-01 9.83166575e-01 3.73588920e-01 1.83130726e-01
1.05379772e+00 8.66685510e-01 2.30578966e-02 -7.40487933e-01
-6.52682185e-02 -1.22746103e-01 -9.01960731e-01 -2.33963877e-01
5.02498984e-01 -3.37911807e-02 -1.35551775e+00 6.52578235e-01
3.76072019e-01 -6.53691739e-02 -2.39845023e-01 8.15670431e-01
9.42409158e-01 6.39894247e-01 -2.22813755e-01 1.28602773e-01
1.40878606e+00 -1.28379548e+00 -8.46360385e-01 -5.29137969e-01
7.52235115e-01 -1.16694319e+00 1.13407433e+00 5.79610705e-01
-8.12782943e-01 -3.28527868e-01 -7.75667191e-01 -2.75494665e-01
-4.48788941e-01 8.68733644e-01 5.65572008e-02 5.87506711e-01
-5.99029005e-01 1.42762745e-02 -6.29849374e-01 -4.71335351e-01
7.29424059e-01 1.88238651e-01 -1.25914738e-01 -1.67031273e-01
-4.60415423e-01 2.84206659e-01 3.94107431e-01 8.13087001e-02
-6.95708573e-01 -2.52286136e-01 -6.28503561e-01 -1.05337732e-01
5.99281311e-01 -5.47783613e-01 1.16917884e+00 -1.03507280e+00
-1.26912856e+00 1.32291710e+00 -4.85485107e-01 -2.76318252e-01
1.05987310e+00 -5.40463030e-01 -1.87601492e-01 2.73896456e-01
1.07050918e-01 5.97966969e-01 1.53401434e+00 -1.00826776e+00
-7.92309225e-01 -6.01105273e-01 -8.42075229e-01 4.03100431e-01
-4.73212481e-01 3.57011318e-01 -1.05791152e+00 -9.74913299e-01
2.34135598e-01 -6.03272498e-01 2.63053626e-01 3.97102475e-01
-1.02563214e+00 -5.76657534e-01 1.62809193e+00 -7.11828947e-01
1.10076249e+00 -1.98989904e+00 3.33171263e-02 -4.79805395e-02
2.48796403e-01 2.84983784e-01 4.56370600e-02 2.54311681e-01
2.34428018e-01 1.83987990e-01 -2.81506509e-01 -8.47751319e-01
2.48810425e-01 -3.31648976e-01 -7.04196453e-01 7.49873221e-01
-1.51722640e-01 9.75901246e-01 -4.12570417e-01 -9.67923462e-01
6.25501454e-01 3.53063405e-01 1.36027643e-02 4.38087955e-02
-5.24326384e-01 -2.35240571e-02 -7.13909924e-01 9.58989084e-01
7.78879046e-01 -4.02118713e-01 -1.35537192e-01 2.39944607e-01
2.61207297e-02 -1.40770286e-01 -1.16637623e+00 1.51805270e+00
1.67323843e-01 1.11702061e+00 1.97104499e-01 -7.02836752e-01
8.57330143e-01 8.50088000e-02 2.22860247e-01 -5.20769238e-01
3.26817960e-01 2.37844400e-02 -7.53250659e-01 -6.46979809e-01
6.74970269e-01 3.61363679e-01 -5.21887951e-02 4.19737965e-01
-4.88093019e-01 -1.95804104e-01 2.76545376e-01 2.26644382e-01
7.80341029e-01 1.37976781e-01 9.01289284e-03 -1.56384230e-01
6.24292314e-01 1.36972770e-01 -2.30990052e-01 9.38671112e-01
2.23824140e-02 9.12795424e-01 1.76422209e-01 -3.98977637e-01
-1.14134860e+00 -8.53188455e-01 -2.64525235e-01 1.33294427e+00
2.37837717e-01 -4.14485663e-01 -1.04946816e+00 -1.11456037e+00
3.44360098e-02 5.29029131e-01 -5.48684299e-01 6.00088775e-01
-6.21536970e-01 -4.80506599e-01 9.44976628e-01 5.20768225e-01
7.89438367e-01 -8.96334052e-01 -4.79259402e-01 -1.66752413e-01
-4.23260659e-01 -1.48855174e+00 -1.07895708e+00 9.00245607e-02
-8.98343205e-01 -1.02600276e+00 -1.16948807e+00 -1.25020599e+00
9.94912803e-01 5.20221889e-01 8.75605047e-01 4.92124446e-02
-7.18648970e-01 6.30041361e-01 -4.05425042e-01 -4.17020112e-01
-2.54210413e-01 1.53562114e-01 -4.99677122e-01 2.54018337e-01
3.74696314e-01 4.09816980e-01 -4.51439470e-01 5.38315296e-01
-1.03611207e+00 3.87829632e-01 4.50544924e-01 6.88745379e-01
7.23103344e-01 9.33390483e-02 4.39684950e-02 -7.54249871e-01
4.41634923e-01 9.93279070e-02 -6.65657163e-01 5.14763355e-01
-3.95468950e-01 -9.20832604e-02 6.30044997e-01 -4.79016751e-01
-9.38533306e-01 5.69245040e-01 9.26947892e-02 -5.35683513e-01
-5.32149971e-01 3.33740741e-01 -7.81242177e-02 6.34260848e-02
3.92391920e-01 9.42418635e-01 -4.77635324e-01 -5.71453452e-01
3.50669801e-01 1.13005376e+00 5.48397005e-01 -4.78519917e-01
7.58702040e-01 7.88294256e-01 -3.73790860e-01 -1.29289865e+00
-8.01934004e-01 -9.44200337e-01 -1.07480621e+00 -1.21560372e-01
8.81646991e-01 -8.33702147e-01 -5.47228694e-01 8.87685359e-01
-1.19570744e+00 -2.67384678e-01 1.43330544e-01 -9.92167592e-02
-4.19334859e-01 9.51533258e-01 -4.58682567e-01 -9.74300504e-01
-9.48446393e-01 -8.76773298e-01 1.93758035e+00 6.30642921e-02
1.13478206e-01 -1.01398468e+00 -3.46189111e-01 6.50807440e-01
-1.24987967e-01 -6.34613857e-02 8.30828547e-01 -7.43552268e-01
-5.68783462e-01 -6.64690137e-01 -4.72832710e-01 -1.52156293e-01
-1.69969961e-01 2.37415522e-01 -9.68918383e-01 -3.23378503e-01
-3.93118441e-01 -2.62342423e-01 1.21227360e+00 2.62556404e-01
1.26151490e+00 -1.48618937e-01 -7.12154329e-01 5.11140525e-01
1.40624917e+00 -6.38905093e-02 5.65892696e-01 1.40454292e-01
1.02236617e+00 3.08049262e-01 6.54567838e-01 5.89745820e-01
6.23695627e-02 5.09341478e-01 3.47313136e-01 -2.58472621e-01
-1.15445979e-01 -2.18261749e-01 2.95787424e-01 3.07167560e-01
6.55258238e-01 -7.37671077e-01 -1.16104066e+00 6.80484533e-01
-1.92255640e+00 -6.99340641e-01 -5.64321041e-01 2.08232689e+00
5.62633157e-01 2.59800047e-01 1.96899995e-01 3.32059115e-01
1.18920982e+00 2.36503452e-01 -6.24921679e-01 4.40472178e-02
-3.09126019e-01 -2.47398838e-01 4.99714702e-01 1.59199983e-01
-1.49592948e+00 1.43905199e+00 6.55953693e+00 1.17385614e+00
-1.14163566e+00 -2.55491257e-01 6.41481698e-01 1.82908386e-01
4.40656722e-01 -3.20496321e-01 -1.15177524e+00 3.51289332e-01
2.29913488e-01 8.81997719e-02 1.65739536e-01 8.45560074e-01
2.11824760e-01 -2.30511218e-01 -1.21066177e+00 1.28831017e+00
5.95584571e-01 -1.17219341e+00 3.79538059e-01 -2.42708802e-01
7.46230483e-01 -1.34712448e-02 1.61950186e-01 8.23424850e-03
-5.55449873e-02 -1.08423400e+00 1.02956951e+00 2.13138327e-01
1.15360355e+00 -4.72526401e-01 3.04454625e-01 6.62221551e-01
-1.34812248e+00 1.67759195e-01 -2.40216807e-01 3.47248346e-01
-1.96150467e-01 6.08925760e-01 -1.16448545e+00 2.61184275e-01
4.36482668e-01 8.19809377e-01 -8.64383459e-01 1.28530884e+00
-2.18782932e-01 7.29088724e-01 -3.71009856e-01 -4.70857769e-01
2.89163977e-01 1.44646661e-02 5.65746844e-01 1.77019036e+00
5.10940813e-02 -2.40503088e-01 4.11637396e-01 9.28134978e-01
-5.02719223e-01 4.41311002e-01 -4.71563667e-01 -2.44777754e-01
1.71500757e-01 1.22209716e+00 -1.38345051e+00 -6.05196178e-01
-2.18432590e-01 1.52709925e+00 5.56481332e-02 3.42460006e-01
-8.13047707e-01 -7.45742500e-01 -1.29550934e-01 6.99801072e-02
7.60217845e-01 -3.43418330e-01 -8.17436993e-01 -1.23283064e+00
4.28071916e-01 -8.85328174e-01 3.90341818e-01 -8.78336370e-01
-1.13849139e+00 3.53922248e-01 -4.66273516e-01 -1.03281689e+00
3.66614938e-01 -8.31967115e-01 -7.04582691e-01 5.17691076e-01
-1.18974781e+00 -1.44934022e+00 -5.60572565e-01 7.57734060e-01
1.43519890e+00 3.38750309e-03 4.49786305e-01 -1.93157885e-02
-9.19746757e-01 8.21382046e-01 6.37178540e-01 7.83443034e-01
8.06815982e-01 -1.12242687e+00 7.49690890e-01 9.88225758e-01
4.81392175e-01 1.49067327e-01 6.13950610e-01 -9.49534595e-01
-1.62866151e+00 -1.16579258e+00 8.06394458e-01 -7.23352313e-01
4.45267230e-01 -8.54748130e-01 -7.61490166e-01 5.46606243e-01
3.29546511e-01 -1.83530673e-01 1.10666975e-01 -2.26479679e-01
-3.67166400e-01 3.73656273e-01 -9.42042530e-01 7.60946453e-01
8.46300602e-01 -3.90967846e-01 -6.38535440e-01 8.13417196e-01
1.63611263e-01 -6.76589191e-01 -1.22147657e-01 5.69375567e-02
3.87190968e-01 -4.96664256e-01 7.97396958e-01 -2.89649069e-01
5.08836985e-01 -1.31085008e-01 6.78279921e-02 -6.03329539e-01
1.83158532e-01 -7.03554392e-01 -4.27188538e-02 1.22488940e+00
2.76990443e-01 -1.26030371e-01 1.09004688e+00 3.36306721e-01
9.86729562e-03 -5.63939929e-01 -9.81692731e-01 -5.50323904e-01
1.94477677e-01 -4.29642141e-01 -9.81179811e-03 8.49915802e-01
5.10249846e-03 5.36983490e-01 -3.24099362e-01 1.19388662e-03
7.66213477e-01 3.44940633e-01 8.56800437e-01 -1.32532907e+00
1.75783589e-01 -6.84218109e-01 -1.57558441e-01 -1.78208137e+00
1.87622577e-01 -9.36445713e-01 2.90714890e-01 -1.86189175e+00
3.88085634e-01 -8.34088326e-02 4.12653327e-01 4.99618322e-01
-3.04904729e-01 1.84543923e-01 1.75653771e-01 3.43133301e-01
-1.14683545e+00 4.90146607e-01 1.22412872e+00 -6.30505979e-01
-3.53742652e-02 -1.79769173e-02 -2.31382072e-01 7.71134853e-01
4.26662534e-01 -5.75792491e-01 3.48988138e-02 -6.30522549e-01
1.89432576e-01 7.81036243e-02 2.40832135e-01 -7.74380147e-01
5.67404807e-01 -2.36306358e-02 7.72314548e-01 -1.50550985e+00
1.30568087e-01 -8.69556427e-01 -7.62171507e-01 7.80881569e-02
-4.68907207e-01 -2.56638259e-01 3.33012670e-01 8.33847642e-01
9.16638747e-02 -4.49762881e-01 7.92128921e-01 1.63875431e-01
-4.83600080e-01 2.05724835e-01 -5.89644790e-01 3.05781424e-01
1.00383282e+00 -5.96308649e-01 -4.74699855e-01 -4.11647111e-02
-4.09043014e-01 3.33193064e-01 4.51711148e-01 5.16355097e-01
1.00876331e+00 -7.83214688e-01 -9.98208761e-01 1.79314151e-01
2.40250662e-01 2.73771912e-01 -3.47381197e-02 7.57615745e-01
-5.46422064e-01 6.86867714e-01 5.02909780e-01 -1.09481645e+00
-1.88278317e+00 5.41776061e-01 3.10012609e-01 -2.26054713e-01
-1.07206321e+00 7.28512824e-01 4.34528828e-01 -1.13946170e-01
7.56511509e-01 -2.78766841e-01 1.36836573e-01 -1.19126901e-01
5.51741779e-01 3.03764194e-01 2.36552618e-02 -4.82219160e-01
-2.88061917e-01 8.89626443e-01 -4.89469886e-01 -4.97241020e-02
8.10866773e-01 -2.95202106e-01 1.31450728e-01 3.19591910e-01
9.07568991e-01 5.19256704e-02 -1.15955114e+00 -4.13567394e-01
2.29663000e-01 -5.67990005e-01 1.03147164e-01 -1.05987442e+00
-7.67548501e-01 1.14322424e+00 4.97216702e-01 1.24704145e-01
8.95578682e-01 -1.52839333e-01 8.81967247e-01 8.25853169e-01
1.85568482e-02 -1.41944408e+00 3.38236213e-01 7.91677952e-01
8.01502228e-01 -1.41256094e+00 1.72073931e-01 -5.50995290e-01
-5.96414983e-01 1.45338452e+00 4.13204521e-01 5.76877259e-02
3.26231927e-01 5.42137325e-01 -9.06435177e-02 -2.21703425e-01
-4.25955683e-01 -1.34070531e-01 5.74277818e-01 2.23238215e-01
3.22983414e-01 1.92669295e-02 2.14105710e-01 2.52496183e-01
2.78500527e-01 -2.48304412e-01 3.41717362e-01 1.00119579e+00
-7.60838866e-01 -5.88616908e-01 -8.56830060e-01 6.96976304e-01
-6.20976806e-01 -3.76653165e-01 -1.13587391e+00 7.08040118e-01
-5.34346163e-01 9.66151178e-01 9.04502049e-02 -5.48829474e-02
2.11561769e-01 3.56780440e-01 3.08672071e-01 -5.32088101e-01
-5.49567163e-01 6.57169163e-01 -1.21574685e-01 1.25290126e-01
7.82440752e-02 -5.84122539e-01 -1.53298450e+00 -1.99903786e-01
-8.92592490e-01 -2.58148134e-01 8.28129292e-01 1.00224376e+00
2.90230364e-01 2.62278497e-01 4.90958363e-01 -7.81998634e-01
-3.43181193e-01 -1.03314221e+00 -5.45809746e-01 3.95521343e-01
3.34409624e-01 -1.15991846e-01 -3.10423583e-01 7.17153430e-01] | [11.958138465881348, 2.271026849746704] |
abd8c231-7998-4fb5-9ed6-735751199e5b | the-impact-of-z_score-on-twitter-sentiment | null | null | https://aclanthology.org/S14-2113 | https://aclanthology.org/S14-2113.pdf | The Impact of Z\_score on Twitter Sentiment Analysis | null | ["Frederic B{\\'e}chet", 'Patrice Bellot', 'Hussam Hamdan'] | 2014-08-01 | null | null | null | semeval-2014-8 | ['twitter-sentiment-analysis'] | ['natural-language-processing'] | [-8.63703638e-02 1.71006292e-01 -6.22772932e-01 -4.08054382e-01
-8.41685571e-03 -9.08429027e-01 6.55310392e-01 -6.53472245e-01
-2.85945535e-01 1.06888819e+00 -4.63127941e-02 -1.01159286e+00
-3.91567826e-01 -9.63214397e-01 -4.95059669e-01 -6.31337762e-01
-9.79754329e-01 7.25764990e-01 3.30370307e-01 -6.93831444e-01
7.03166842e-01 7.88774848e-01 -1.68942046e+00 7.18545914e-01
7.04417467e-01 8.52217197e-01 2.49141872e-01 1.14950800e+00
-1.95044339e-01 1.55633950e+00 -7.48382092e-01 -5.46825826e-01
3.13719302e-01 -1.23176083e-01 -7.22945035e-01 -1.01074085e-01
9.28529128e-02 -8.59008506e-02 -2.09758401e-01 9.22211111e-01
5.37373662e-01 4.49454933e-02 1.08379531e+00 -1.42548037e+00
-5.91619551e-01 6.10313773e-01 -4.01565880e-02 1.21627934e-01
1.03678203e+00 -5.39447069e-01 1.19919395e+00 -1.13026452e+00
7.20913768e-01 1.26888943e+00 8.66221786e-01 5.44149756e-01
-1.22286928e+00 -1.94712028e-01 -3.26822817e-01 -9.51717794e-02
-1.46558487e+00 -3.25250506e-01 4.25783843e-02 -2.08119690e-01
1.66093647e+00 1.26596653e+00 1.20609856e+00 1.01401424e+00
1.26658809e+00 8.34431887e-01 1.04267764e+00 -5.13792276e-01
3.35295945e-01 3.66983831e-01 1.54683650e-01 6.33519173e-01
8.40953708e-01 5.26628852e-01 -7.06372619e-01 -9.13127720e-01
9.33553874e-01 -2.94925272e-01 1.71355158e-01 -5.05680561e-01
-9.05919552e-01 6.91228509e-01 1.78732842e-01 3.83959889e-01
-1.39880210e-01 9.89067405e-02 1.26390755e-01 5.30987144e-01
-2.58292928e-02 6.47037446e-01 -9.11868811e-01 -1.33165747e-01
-8.71728659e-01 5.10332465e-01 1.25398111e+00 1.52653182e+00
1.24482810e-01 2.94908643e-01 -9.34252143e-02 3.17179203e-01
8.92314315e-01 1.01808000e+00 4.28362608e-01 -1.36146402e+00
-6.87414408e-02 1.72361732e-01 5.01781464e-01 -8.52631688e-01
-6.33224547e-01 -9.64177120e-03 -8.93263519e-01 4.49267089e-01
3.49161088e-01 4.57367361e-01 -8.02827001e-01 5.07305264e-01
4.33481112e-02 -2.34125629e-01 4.53833073e-01 5.55570945e-02
4.99930978e-01 3.76208365e-01 -1.34477139e-01 -5.73289394e-01
1.06082785e+00 -1.36716676e+00 -1.35299087e+00 2.33215362e-01
9.05734658e-01 -1.07320261e+00 4.35900748e-01 5.33875942e-01
-1.55548143e+00 -1.37560293e-01 -1.08699942e+00 1.78573877e-01
-7.27255583e-01 -3.14239264e-01 8.57801437e-01 1.43120694e+00
-1.60129595e+00 9.73287821e-01 -4.91727620e-01 6.59165755e-02
1.20568443e-02 8.24621081e-01 -2.64718989e-03 4.62812334e-01
-1.33193445e+00 1.08501506e+00 2.22979754e-01 -1.21242590e-01
-1.65216476e-01 -2.13068098e-01 -8.23704481e-01 -5.63443303e-01
-4.78693932e-01 -5.29636025e-01 1.44139910e+00 -2.59346128e-01
-1.65295815e+00 9.71794367e-01 -1.42069459e-01 -1.97814897e-01
6.14786744e-01 -1.28011424e-02 -8.31891418e-01 2.42498964e-01
-1.89849049e-01 5.76383233e-01 9.28263724e-01 -1.35132408e+00
-7.59897232e-01 -1.67359829e-01 -1.23336017e-01 2.66287565e-01
-1.25510961e-01 1.89734384e-01 2.11616129e-01 -1.12999000e-01
3.27147305e-01 -7.20919967e-01 -2.53068686e-01 -5.32041907e-01
-1.46512717e-01 -7.10518599e-01 7.70373225e-01 -4.51523662e-01
1.83705616e+00 -1.67618537e+00 -2.06720144e-01 3.98590982e-01
3.57815564e-01 -1.24705513e-03 2.40583986e-01 1.08380008e+00
-2.76906848e-01 7.32199550e-01 4.11965609e-01 -1.10722095e-01
2.24991128e-01 4.85861301e-01 -4.16602850e-01 3.05609167e-01
-1.29282743e-01 1.15307164e+00 -1.16605783e+00 -5.23096442e-01
4.11106765e-01 9.42391157e-02 -4.58732933e-01 4.79237735e-01
2.99364805e-01 1.47170946e-01 -3.56553018e-01 1.39399457e+00
1.15709066e+00 -1.31984919e-01 1.45911396e-01 5.30878425e-01
-3.79135728e-01 3.55090618e-01 -6.96863770e-01 1.05554795e+00
7.08333924e-02 5.00173986e-01 1.02364108e-01 -7.94621468e-01
3.33247900e-01 8.61540735e-01 4.37155962e-01 -9.67555881e-01
-2.26398129e-02 6.92409754e-01 1.12803578e-01 -6.07703328e-01
7.58228302e-01 3.94563079e-02 -3.64872098e-01 6.40070081e-01
-2.37588286e-01 -6.59476995e-01 9.64643434e-02 3.08100313e-01
6.22585893e-01 -5.18246442e-02 5.62923312e-01 -1.05613089e+00
7.86340594e-01 -1.82965681e-01 -1.81299388e-01 1.03415680e+00
-3.09923887e-01 3.19085121e-01 2.99841821e-01 -6.65102363e-01
-6.45341039e-01 -1.12307119e+00 -4.89381433e-01 1.30636716e+00
3.24267983e-01 -4.39044595e-01 -9.54439282e-01 -2.49762803e-01
1.77620783e-01 6.89606130e-01 -5.90509653e-01 3.84124845e-01
-5.03739953e-01 -8.32535863e-01 7.39044368e-01 3.45434904e-01
-5.07752821e-02 -1.33414865e+00 -6.58416986e-01 1.25490099e-01
-2.20292807e-01 -6.63697243e-01 -6.23428151e-02 4.48765576e-01
-1.35989368e+00 -5.18594682e-01 -6.66252747e-02 -8.20914626e-01
5.87345481e-01 2.46782884e-01 1.27047324e+00 5.39230824e-01
-2.31483161e-01 4.26904231e-01 -1.21292919e-01 -4.95818377e-01
-4.59671497e-01 -8.00336525e-02 5.28869390e-01 -5.87835789e-01
5.19427478e-01 -2.50617653e-01 -7.29350567e-01 5.37953973e-01
-6.88540697e-01 1.62748516e-01 1.79803044e-01 1.04410267e+00
1.35816500e-01 -9.34035778e-02 1.22507080e-01 -6.38007045e-01
8.72274399e-01 -1.69219792e-01 -3.78732830e-01 5.77745810e-02
-6.77108407e-01 -3.74140263e-01 3.21430594e-01 -3.25342178e-01
-1.01981449e+00 -4.87835288e-01 -9.82677937e-02 2.45538145e-01
1.11353043e-02 -1.46784872e-01 6.47139177e-02 -5.24923325e-01
8.02199244e-01 9.25758183e-02 1.99174434e-02 -6.80815242e-03
3.01039815e-01 7.09525108e-01 -6.82967342e-03 -6.68678164e-01
8.44880998e-01 4.91470337e-01 7.98524171e-02 -9.57177758e-01
-1.52186140e-01 -2.60129690e-01 -9.51962709e-01 -6.54426932e-01
6.56643391e-01 -6.78531289e-01 -9.10833478e-01 3.91110867e-01
-9.38691139e-01 -3.38627815e-01 -3.91645581e-01 4.25431967e-01
-1.01278400e+00 2.75717527e-02 -3.90154392e-01 -1.27895141e+00
-5.10977268e-01 -1.02017939e+00 9.43384409e-01 5.30070923e-02
-5.10597289e-01 -1.26927447e+00 5.87685481e-02 2.71537274e-01
1.81734428e-01 -1.73075795e-01 6.90226793e-01 -2.38256708e-01
-4.24233019e-01 -1.53791070e-01 2.34436691e-02 -1.39755070e-01
1.70832314e-02 4.95917559e-01 -9.81751978e-01 -5.31145096e-01
6.65065646e-02 -1.92070693e-01 -1.08835101e-01 6.52520418e-01
5.91872573e-01 -2.29931593e-01 -8.56000841e-01 5.40386558e-01
1.38545322e+00 3.85070026e-01 5.32770038e-01 7.28214979e-01
1.41836226e-01 5.53460240e-01 9.17806149e-01 4.63203549e-01
1.30579369e-02 3.28798652e-01 2.40537539e-01 1.49327129e-01
1.11720070e-01 -1.54819340e-01 3.77893507e-01 1.16112018e+00
-8.18235934e-01 -2.69281328e-01 -5.07867396e-01 4.42987174e-01
-1.72482407e+00 -1.40330648e+00 -4.32368398e-01 6.90478683e-01
6.25676990e-01 1.56016424e-01 -1.48347050e-01 3.35214496e-01
4.99015123e-01 -2.03574806e-01 -1.19133167e-01 -1.06291151e+00
-1.43546045e-01 3.15233678e-01 7.37729073e-01 1.00061214e+00
-7.20721722e-01 1.03317809e+00 1.29781246e+01 1.02230716e+00
2.21112028e-01 1.03134915e-01 5.16071796e-01 3.48020852e-01
-4.36954498e-01 -4.56139445e-02 -1.04416132e+00 2.72933897e-02
1.38140702e+00 -4.30666685e-01 6.85999811e-01 5.44219851e-01
3.44648361e-01 -4.23268199e-01 -1.26188684e+00 5.26221812e-01
9.73738134e-02 -1.40886843e+00 -2.83300440e-04 6.85225725e-01
7.73699820e-01 -5.08050561e-01 6.22419357e-01 3.24184299e-01
6.09259963e-01 -1.14389277e+00 8.60300779e-01 2.53660440e-01
1.03040910e+00 -6.05088234e-01 5.67372203e-01 1.68872893e-01
-1.14389896e+00 -2.20873043e-01 -8.77727985e-01 -1.00755692e+00
3.93533185e-02 -1.81779593e-01 -4.29956943e-01 3.48861217e-01
9.58353162e-01 2.99398601e-01 -3.93658698e-01 9.95779395e-01
-4.78694476e-02 1.04875881e-02 -2.71853864e-01 -4.48467314e-01
4.83122796e-01 -3.54241252e-01 4.66730654e-01 1.00164843e+00
2.48499006e-01 3.51035744e-01 -9.84472036e-02 4.01770771e-01
5.45058846e-01 3.29446048e-02 -1.19659424e+00 -1.78908288e-01
2.83276141e-01 9.16795909e-01 -4.83487815e-01 -4.22520459e-01
-2.00212970e-01 8.62069130e-01 -3.55488248e-02 5.01107454e-01
-6.11489356e-01 -4.35615242e-01 9.72222984e-01 -1.27327025e-01
-1.14700586e-01 -3.48497719e-01 -6.23769283e-01 -7.30352640e-01
-5.89872956e-01 -4.54965204e-01 5.93606755e-02 -5.53365827e-01
-1.39813089e+00 5.79277515e-01 -2.27688253e-02 -1.40553558e+00
-6.99901402e-01 -1.27676582e+00 -4.76714373e-01 4.92853165e-01
-1.11898029e+00 -1.10984349e+00 2.50124663e-01 4.52870727e-01
1.64141744e-01 -5.34416080e-01 1.39563632e+00 3.57715860e-02
1.00637585e-01 9.24474537e-01 6.69434488e-01 -7.37814724e-01
5.56605101e-01 -1.27867436e+00 5.68737745e-01 -1.37897313e-01
-4.31265175e-01 9.05828118e-01 6.28349900e-01 -5.39804697e-01
-1.41196322e+00 -3.66917729e-01 1.08350635e+00 -9.83769417e-01
6.55218959e-01 -3.86345625e-01 4.23767231e-02 7.88592756e-01
7.15902448e-01 -6.18741751e-01 8.21781039e-01 -1.83753878e-01
1.80774391e-01 5.75296998e-01 -1.39248300e+00 6.12354755e-01
1.66275799e+00 -4.63594139e-01 -6.25784039e-01 7.60327101e-01
8.13696027e-01 -6.94087505e-01 -1.30082703e+00 3.34633321e-01
8.65424156e-01 -8.75409484e-01 1.61978090e+00 -1.32660246e+00
-4.43697497e-02 2.81152606e-01 -2.61993498e-01 -9.32519078e-01
-5.96193194e-01 -1.23518765e+00 -5.33532679e-01 -5.83747849e-02
5.96577883e-01 -1.13057327e+00 3.42365682e-01 8.74560475e-01
-2.82833427e-01 -6.42737269e-01 -1.06996536e+00 -1.32016802e+00
-3.35779637e-02 -1.45572275e-01 4.90409225e-01 7.63798356e-01
6.83744550e-01 1.09839931e-01 -6.36873543e-02 -1.00294888e-01
5.33176839e-01 9.55312885e-03 4.41501856e-01 -1.34294486e+00
3.86843324e-01 -5.75816095e-01 -3.07655483e-01 -9.45992947e-01
-8.85957032e-02 -8.12076271e-01 -6.53862000e-01 -1.28511906e+00
-8.32044985e-03 -1.91056758e-01 -1.11109078e-01 -1.65725678e-01
3.67937148e-01 2.13746816e-01 1.20859891e-02 1.03788137e-01
-3.71160030e-01 6.18435517e-02 1.29639816e+00 6.91750320e-05
-1.62315920e-01 4.85058486e-01 -4.81304944e-01 7.84440815e-01
8.58408585e-02 -2.99253196e-01 -6.78878546e-01 6.11881316e-02
6.69384480e-01 4.61409837e-02 3.24159935e-02 -7.42885649e-01
5.37211418e-01 -3.75702560e-01 4.78586555e-01 -1.32223868e+00
1.30741090e-01 -9.61415648e-01 6.95283338e-02 9.40189242e-01
2.74610907e-01 1.20424610e-02 8.66204947e-02 5.39500564e-02
-1.44871444e-01 -5.70943117e-01 9.21121240e-01 -4.07591403e-01
-4.92852688e-01 -5.20386267e-03 -1.03226590e+00 8.97834301e-02
9.92593169e-01 -7.84614205e-01 -3.59281451e-01 -4.20183957e-01
-8.29068601e-01 -1.95836127e-02 6.50830388e-01 3.03609259e-02
7.30431557e-01 -1.51530886e+00 -2.30721906e-01 7.18729138e-01
-3.22939813e-01 -3.74400020e-01 -1.70157343e-01 6.58265352e-01
-1.32361674e+00 1.02442718e+00 -5.41665435e-01 -4.55340147e-01
-1.14228773e+00 4.78126436e-01 4.28307921e-01 -2.41845414e-01
-2.15481281e-01 1.11954463e+00 2.71224789e-02 -8.23025763e-01
1.85185194e-01 -9.21545625e-02 -7.54407048e-01 3.55081353e-03
6.88606799e-01 1.05194807e+00 -2.91290224e-01 -6.04341030e-01
-4.56784427e-01 6.65885091e-01 2.32151806e-01 -2.87484169e-01
9.17833567e-01 -2.19243199e-01 -9.89108324e-01 4.28274393e-01
8.38715494e-01 -1.36269778e-01 -3.69319022e-02 4.16855574e-01
1.25943512e-01 -8.02164078e-01 -4.32406247e-01 -3.55811834e-01
-1.85641110e-01 5.54822803e-01 5.34874737e-01 8.99602413e-01
8.57008278e-01 -3.02566767e-01 8.18335712e-01 9.66778398e-01
5.72402716e-01 -1.68019545e+00 -2.13140488e-01 6.89524531e-01
9.12339568e-01 -9.28350806e-01 5.44190466e-01 -7.27165341e-01
-4.14997995e-01 1.32979155e+00 4.68304873e-01 -1.55325383e-01
1.27306652e+00 5.74917436e-01 1.14069022e-02 -3.70670199e-01
-9.44949508e-01 1.12705544e-01 3.75366658e-01 1.11147714e+00
5.06513238e-01 5.07374525e-01 -9.66500878e-01 3.21953118e-01
-7.28706717e-01 -2.34555230e-01 4.90474731e-01 1.41972518e+00
-6.43810987e-01 -1.20391917e+00 -7.23931909e-01 4.61561680e-01
-5.49773455e-01 -1.16372630e-01 -5.28106689e-01 8.46754074e-01
-5.76629937e-02 1.49448860e+00 -1.97535474e-03 -5.03491640e-01
4.11356747e-01 1.41089618e-01 7.21762300e-01 -1.23501487e-01
-9.04846430e-01 4.15413082e-01 3.84890139e-01 -1.23056793e+00
-8.58632207e-01 -1.05834293e+00 -1.40667629e+00 -1.19437599e+00
-5.12782812e-01 1.89310342e-01 3.83317530e-01 3.90289724e-01
-2.06836104e-01 2.85260603e-02 9.80917513e-01 -1.07949340e+00
-3.90341938e-01 -9.39418614e-01 -1.00026262e+00 -7.84516707e-02
2.89751232e-01 -8.00943017e-01 -7.83523321e-01 2.83909619e-01] | [-7.295073986053467, 3.6454503536224365] |
58d928ee-8600-4e75-8b3c-558840614c31 | attention-compilation-and-solver-based | 2306.06755 | null | https://arxiv.org/abs/2306.06755v1 | https://arxiv.org/pdf/2306.06755v1.pdf | Attention, Compilation, and Solver-based Symbolic Analysis are All You Need | In this paper we present a Java-to-Python (J2P) and Python-to-Java (P2J) back-to-back code translation method, and associated tool called CoTran, based on large language models (LLMs). Our method leverages the attention mechanism of LLMs, compilation, and symbolic execution-based test generation for equivalence testing between the input and output programs. More precisely, we modify the typical LLM training loop to incorporate compiler and symbolic execution loss. Via extensive experiments comparing CoTran with 10 other transpilers and LLM-based translation tools over a benchmark of more than 57,000 Java-Python equivalent pairs, we show that CoTran outperforms them on relevant metrics such as compilation and runtime equivalence accuracy. For example, our tool gets 97.43% compilation accuracy and 49.66% runtime equivalence accuracy for J2P translation, whereas the nearest competing tool only gets 96.44% and 6.8% respectively. | ['Vijay Ganesh', 'Aryan Mahajan', 'Gautham Kishore', 'Haoyang Ju', 'Piyush Jha', 'Prithwish Jana'] | 2023-06-11 | null | null | null | null | ['code-translation'] | ['computer-code'] | [ 4.03898247e-02 -2.84553766e-01 -3.48298937e-01 -3.20567012e-01
-1.38331223e+00 -7.68699646e-01 5.54452538e-01 6.47464022e-02
2.83722226e-02 6.52454853e-01 -3.26055437e-01 -9.47480381e-01
5.41681230e-01 -8.19106758e-01 -1.12557673e+00 6.45394996e-02
-8.78568273e-03 2.41396785e-01 1.27697960e-01 -5.00386804e-02
3.12263787e-01 -7.28599355e-02 -1.16126776e+00 6.20774508e-01
1.28025818e+00 5.88297904e-01 -2.66791344e-01 1.17764306e+00
-1.47844702e-01 1.04601038e+00 -5.75553536e-01 -6.59501195e-01
2.84632236e-01 -3.63859564e-01 -8.74710798e-01 -7.44247437e-01
3.28377634e-01 -1.21682622e-01 4.24239039e-01 1.08822262e+00
3.47257316e-01 -4.57358718e-01 3.55235666e-01 -1.62607849e+00
-4.29169565e-01 7.54111052e-01 -8.15488756e-01 -4.35523838e-01
6.28431618e-01 2.09057465e-01 7.87207961e-01 -7.31330097e-01
5.73436618e-01 1.09948933e+00 1.11984968e+00 1.56194016e-01
-1.51267946e+00 -6.70716405e-01 -6.27831817e-01 -3.18234831e-01
-1.50441563e+00 -2.42762163e-01 3.14978570e-01 -9.01339650e-01
1.59088194e+00 5.40671945e-01 3.17177325e-01 1.01230669e+00
8.05794239e-01 3.64835292e-01 1.45879698e+00 -8.58600318e-01
-2.45982073e-02 5.06211579e-01 2.11081982e-01 9.80509639e-01
8.66416171e-02 4.47082072e-01 -9.62845385e-02 -6.38638914e-01
2.59107351e-01 -5.24979651e-01 2.48465076e-01 4.73171100e-02
-1.26121461e+00 6.48126960e-01 -4.49844748e-02 7.67995939e-02
4.06788826e-01 4.62500930e-01 9.66338813e-01 6.26080751e-01
5.15505783e-02 4.46797937e-01 -7.57506847e-01 -5.19063830e-01
-1.05272293e+00 2.52312541e-01 1.19108117e+00 1.39915228e+00
9.58759785e-01 2.27631241e-01 -7.10614696e-02 5.44055998e-01
2.89359897e-01 4.45914567e-01 6.05551898e-01 -7.64908135e-01
8.65657508e-01 7.75755227e-01 -2.98295826e-01 -8.08752596e-01
-7.86348656e-02 -3.12593073e-01 -2.64667839e-01 3.44465822e-01
5.11790365e-02 -1.56796336e-01 -2.78732717e-01 1.46799040e+00
1.35630086e-01 -6.22079223e-02 2.07453921e-01 4.28344190e-01
4.09944624e-01 6.67251587e-01 -1.02896930e-03 2.25378186e-01
9.71553206e-01 -1.24637318e+00 2.07003817e-01 -1.68017432e-01
1.24142396e+00 -1.08333242e+00 1.47407472e+00 1.83808561e-02
-9.37344611e-01 -6.99695110e-01 -1.11710250e+00 9.62654362e-04
-3.05374056e-01 3.78847510e-01 5.25852203e-01 6.56309724e-01
-1.06814885e+00 7.60165393e-01 -9.02866662e-01 -3.22558969e-01
-2.02816010e-01 2.37783864e-01 -2.59655654e-01 1.24284163e-01
-7.53127337e-01 7.64906764e-01 4.10391510e-01 -4.08779055e-01
-1.05812550e+00 -9.96536970e-01 -8.19234014e-01 -2.01806501e-01
-2.68897861e-02 -7.08085954e-01 1.53287959e+00 -8.96142602e-01
-1.68755245e+00 1.02764654e+00 7.77061060e-02 -3.36262584e-01
5.95328331e-01 -3.69517744e-01 -5.29480159e-01 -3.36076200e-01
3.99375468e-01 2.50373602e-01 4.21639085e-01 -9.12457407e-01
-3.85267496e-01 1.49841979e-02 4.13043723e-02 -4.70452815e-01
1.22164942e-01 6.21924460e-01 -2.05687582e-01 -3.38093400e-01
-5.05906463e-01 -1.11311340e+00 3.25861350e-02 -3.79617840e-01
-7.65125573e-01 3.16765189e-01 4.09041554e-01 -1.08868146e+00
1.04158783e+00 -2.05323172e+00 1.50646819e-02 2.71220684e-01
2.92927362e-02 -1.32065460e-01 -3.30555499e-01 7.17698753e-01
-1.94513172e-01 2.49743417e-01 -3.42026323e-01 6.77719042e-02
4.67302054e-01 -4.10166159e-02 -4.72853094e-01 4.10057187e-01
2.39504591e-01 1.07757998e+00 -8.13394010e-01 -8.57375205e-01
-2.79705003e-02 1.72966197e-02 -9.91469800e-01 2.80510098e-01
-4.22896892e-01 1.72122300e-01 -2.05121800e-01 1.04331827e+00
4.11865920e-01 5.05424701e-02 3.00777614e-01 2.96892047e-01
-4.71917123e-01 3.81484061e-01 -4.77909654e-01 1.67768741e+00
-1.28497374e+00 6.84532464e-01 -2.19290465e-01 -6.02786839e-01
1.03595662e+00 2.76123852e-01 -2.29747787e-01 -7.42785394e-01
-9.96127129e-02 8.27095866e-01 1.33985266e-01 -3.29443246e-01
5.41332185e-01 1.51725888e-01 -6.89801455e-01 3.47649932e-01
-3.91760096e-02 -3.87081295e-01 3.18549633e-01 4.16566953e-02
1.18048644e+00 7.87901700e-01 5.64621210e-01 -4.05068785e-01
5.60362756e-01 3.33469927e-01 4.89714354e-01 7.45531619e-01
2.59987533e-01 2.09856927e-01 8.79074156e-01 -5.27010672e-02
-1.30701137e+00 -9.65959311e-01 3.81773002e-02 1.15271974e+00
-5.17293632e-01 -7.57447422e-01 -8.14039230e-01 -5.68062901e-01
-9.28572267e-02 1.14985991e+00 -2.84646481e-01 -2.42879108e-01
-6.92767799e-01 -4.35715497e-01 1.14578664e+00 6.21047258e-01
4.15190667e-01 -7.73492217e-01 -5.36480188e-01 1.68259695e-01
1.36150986e-01 -9.75843966e-01 -5.73798656e-01 9.68929976e-02
-8.68814528e-01 -9.93050396e-01 -1.04342215e-01 -8.84366930e-01
4.95029896e-01 -5.26269436e-01 1.55348039e+00 6.39236718e-02
-4.38389271e-01 2.81690694e-02 -2.90798217e-01 1.28653198e-01
-1.32123399e+00 1.61992192e-01 -2.05643222e-01 -6.76093757e-01
-5.98286614e-02 -7.55756974e-01 2.16689646e-01 2.57667780e-01
-4.07068402e-01 4.23704326e-01 6.75044537e-01 1.02929544e+00
2.96287835e-01 -4.66040432e-01 1.92293361e-01 -9.46205914e-01
4.28450495e-01 -4.19302344e-01 -1.32852066e+00 3.92165631e-01
-8.12846363e-01 5.18242866e-02 1.28452456e+00 -2.78651208e-01
-7.78218508e-01 -1.33105367e-01 -2.18011022e-01 -1.52930811e-01
7.03606978e-02 8.19916308e-01 -1.11728996e-01 -3.91930699e-01
7.97698617e-01 4.30652380e-01 -4.76108313e-01 -4.06941712e-01
1.65507615e-01 6.62135184e-01 6.09585404e-01 -1.35275614e+00
9.41207707e-01 -3.13830823e-01 -2.39107087e-01 -2.72802383e-01
-5.53658307e-02 1.09585211e-01 -2.28036061e-01 2.59987444e-01
4.03293878e-01 -7.41876066e-01 -5.10588408e-01 3.30378950e-01
-1.39692295e+00 -6.39900029e-01 4.57748286e-02 2.83690840e-01
-7.19995260e-01 4.06680465e-01 -8.51869881e-01 -5.46392202e-01
-6.21378601e-01 -1.57963836e+00 1.23240650e+00 -2.34013900e-01
-4.79812622e-01 -7.01062858e-01 4.64079201e-01 1.15331963e-01
5.61164200e-01 5.00163555e-01 1.46329546e+00 -6.12600386e-01
-3.88028651e-01 -4.34761137e-01 -2.92546511e-01 4.85647440e-01
-2.90910810e-01 5.52594423e-01 -6.21044934e-01 -2.41521239e-01
-3.45044792e-01 -3.40645343e-01 1.82061363e-02 -2.29774058e-01
8.53397071e-01 -5.23265719e-01 -2.43015721e-01 7.79677033e-01
1.75334823e+00 8.55956003e-02 6.63922131e-01 5.34103155e-01
5.79496205e-01 1.23795033e-01 5.37765026e-01 2.38088608e-01
3.41983885e-01 8.69359732e-01 6.95369318e-02 -2.61961995e-03
1.33516546e-03 -5.35126746e-01 1.15939999e+00 1.25578570e+00
2.74799913e-01 4.25214499e-01 -1.34099722e+00 3.38159978e-01
-1.52952194e+00 -4.98614728e-01 -3.82704765e-01 2.46488976e+00
1.30470860e+00 1.15770400e-01 -6.65184185e-02 -7.83865452e-02
4.86477077e-01 -4.51353610e-01 -1.00466423e-01 -1.06840467e+00
3.01846415e-01 5.34047782e-01 2.10248590e-01 5.28553486e-01
-7.52245486e-01 8.81604970e-01 5.97146845e+00 8.92799020e-01
-1.06117117e+00 2.28225484e-01 3.13822865e-01 3.20346028e-01
-1.41061053e-01 6.23900473e-01 -7.66186953e-01 4.79753345e-01
1.52332842e+00 -5.34490108e-01 6.22526705e-01 1.34304321e+00
-9.20930505e-02 -5.41973561e-02 -1.54112446e+00 5.33981919e-01
-3.42411280e-01 -1.26762700e+00 -3.34304690e-01 -3.31614614e-01
9.17213142e-01 2.74681926e-01 -3.02214056e-01 9.60708857e-01
4.62186128e-01 -1.03123510e+00 1.08001304e+00 2.39959300e-01
1.05160570e+00 -5.92470288e-01 9.06167924e-01 3.07584137e-01
-1.18887889e+00 3.51668775e-01 -4.66496646e-02 -1.86663777e-01
-3.54579240e-01 4.47082609e-01 -9.66048002e-01 8.92871559e-01
6.22527897e-01 3.52989167e-01 -7.94759810e-01 7.30962515e-01
-1.88240051e-01 7.88012564e-01 -1.70564935e-01 -2.09672973e-02
-3.86808030e-02 -1.56700388e-01 2.86249608e-01 1.65657842e+00
4.62985992e-01 -8.11677933e-01 3.85264963e-01 1.30124044e+00
-8.81503597e-02 3.22254419e-01 -5.25918841e-01 -2.84742355e-01
4.70301658e-01 1.21839142e+00 -2.45890766e-01 -5.20345151e-01
-6.42559230e-01 8.95210445e-01 3.92132044e-01 1.82781637e-01
-1.39881170e+00 -9.15650964e-01 4.79878396e-01 -1.48408905e-01
-4.52667698e-02 -1.65612131e-01 -2.50140101e-01 -1.28808928e+00
3.63088697e-01 -1.36630702e+00 -7.55786821e-02 -7.37667859e-01
-9.20377016e-01 6.41292751e-01 -8.32054690e-02 -1.25999820e+00
-5.89784145e-01 -4.49998945e-01 -8.67501855e-01 1.13674021e+00
-1.36345768e+00 -1.29129791e+00 -2.79808026e-02 1.23048676e-02
1.10338517e-01 -3.79993021e-01 1.06242251e+00 4.95812058e-01
-4.89833683e-01 1.12374914e+00 2.95035958e-01 2.94302374e-01
4.52119589e-01 -1.16271865e+00 7.88333833e-01 8.64788413e-01
-2.61536151e-01 9.92264390e-01 5.55820704e-01 -5.22679150e-01
-1.94020319e+00 -1.50901830e+00 9.92367685e-01 -4.59950328e-01
1.07454407e+00 -4.47407156e-01 -5.90995014e-01 9.48826551e-01
1.50375798e-01 -6.16018660e-02 5.57224512e-01 -6.27945364e-02
-8.31687152e-01 6.05348200e-02 -1.05477262e+00 7.10082233e-01
5.76765656e-01 -8.77879024e-01 -3.56398940e-01 4.56916243e-01
9.51825082e-01 -7.50405252e-01 -1.33524811e+00 1.66069523e-01
7.26778388e-01 -9.60702121e-01 7.75757074e-01 -5.69317877e-01
1.03796124e+00 -4.60319251e-01 -7.77700722e-01 -8.95128310e-01
2.39956200e-01 -7.13971734e-01 6.52333871e-02 1.53410900e+00
5.88274777e-01 -9.31638539e-01 1.91390425e-01 2.10598335e-01
-3.52199286e-01 -7.64190078e-01 -7.20578849e-01 -1.25679779e+00
4.73734200e-01 -7.14742661e-01 6.52114034e-01 9.90186334e-01
1.89575240e-01 2.18364522e-01 -2.40240023e-01 1.30603373e-01
4.43677604e-01 7.46947408e-01 1.16685414e+00 -4.90500182e-01
-1.16226029e+00 -3.85076493e-01 -3.30325931e-01 -4.70139086e-01
4.03685540e-01 -1.55035555e+00 -3.15697156e-02 -7.85921872e-01
6.47666156e-01 -3.43730152e-01 3.09993505e-01 6.97951674e-01
1.93190992e-01 2.55507022e-01 1.12411171e-01 4.44713496e-02
-3.62839520e-01 2.91388959e-01 5.90752542e-01 -1.57084644e-01
-1.16061859e-01 -5.80906533e-02 -4.46177602e-01 6.08927906e-01
7.33710110e-01 -7.76728213e-01 3.04185838e-01 -3.80380094e-01
4.10427660e-01 4.01648343e-01 6.37509286e-01 -1.07449925e+00
-2.06115723e-01 -1.84204370e-01 -9.86081138e-02 -1.78461775e-01
-2.78661877e-01 -3.51274192e-01 5.93936741e-01 7.97252834e-01
-3.50089103e-01 3.71425509e-01 5.88468015e-01 -1.15910219e-02
-2.14475721e-01 -3.85436237e-01 6.05732203e-01 2.69198697e-02
-6.02919340e-01 -3.24829906e-01 -2.33847827e-01 2.69845724e-01
8.87198031e-01 1.26306498e-02 -4.92964745e-01 2.16713682e-01
-1.58381447e-01 3.32352589e-03 8.59606385e-01 2.75048137e-01
2.40630001e-01 -1.27426910e+00 -8.26603234e-01 2.44729444e-01
4.20455217e-01 -7.31447935e-01 -3.89193177e-01 1.15919077e+00
-9.40233946e-01 5.83326161e-01 -8.54219124e-02 -6.71042502e-01
-1.25005829e+00 2.70460576e-01 2.48080745e-01 -4.55539167e-01
-3.95214528e-01 4.84464616e-01 -1.93930808e-02 -1.41582072e+00
-4.33254540e-01 -7.09639609e-01 8.97042215e-01 -1.01052105e+00
1.20227173e-01 6.02797925e-01 3.22270036e-01 -1.57360122e-01
-6.55816317e-01 6.66190863e-01 2.29441449e-01 -1.14042282e-01
1.04526341e+00 7.10155487e-01 -8.24288487e-01 4.99700457e-01
1.59605694e+00 3.46120983e-01 -5.00210404e-01 1.86187133e-01
1.60233229e-01 -4.11140442e-01 -2.99649179e-01 -1.14157915e+00
-5.60062408e-01 8.99481058e-01 2.77379006e-01 -2.17707768e-01
8.65532994e-01 -2.70408034e-01 6.15375400e-01 3.87986153e-01
7.63000667e-01 -6.72549605e-01 -3.71069044e-01 6.15129709e-01
6.89977109e-01 -1.01162052e+00 -1.03384420e-01 -3.23805392e-01
-1.79664075e-01 1.21814358e+00 7.16178298e-01 -2.73206569e-02
-3.49433273e-02 8.41938853e-01 -2.66033560e-01 4.06401455e-01
-9.15799379e-01 5.83689034e-01 -9.77803916e-02 3.68721694e-01
8.14459980e-01 2.19480053e-01 -3.35771114e-01 8.58208477e-01
-4.78553176e-01 4.80715722e-01 5.64720750e-01 1.10890687e+00
1.78782195e-01 -1.30770481e+00 -6.11936986e-01 4.82183367e-01
-2.66196221e-01 -5.67479610e-01 -8.68950263e-02 1.14582562e+00
-1.40696540e-01 5.79268277e-01 -3.28084350e-01 -7.73681402e-01
7.85755217e-02 2.30255350e-01 6.91823602e-01 -6.89936578e-01
-1.09815168e+00 -2.83841521e-01 4.28894073e-01 -6.55141294e-01
2.84225702e-01 -4.45099324e-01 -1.25748777e+00 -7.29202569e-01
-2.39411399e-01 2.11257204e-01 7.35753417e-01 6.98839903e-01
6.79112852e-01 5.85793078e-01 4.44303870e-01 -5.60185075e-01
-9.17919934e-01 -6.60786748e-01 -2.68229634e-01 3.89214751e-04
-6.73590750e-02 -1.27388924e-01 -9.45299119e-02 1.38219640e-01] | [7.728301525115967, 7.833614349365234] |
f3ef0b0e-e44d-494f-be88-1c3e3713dc3f | slide-constrain-parse-repeat-synchronous | 2305.17273 | null | https://arxiv.org/abs/2305.17273v1 | https://arxiv.org/pdf/2305.17273v1.pdf | Slide, Constrain, Parse, Repeat: Synchronous SlidingWindows for Document AMR Parsing | The sliding window approach provides an elegant way to handle contexts of sizes larger than the Transformer's input window, for tasks like language modeling. Here we extend this approach to the sequence-to-sequence task of document parsing. For this, we exploit recent progress in transition-based parsing to implement a parser with synchronous sliding windows over source and target. We develop an oracle and a parser for document-level AMR by expanding on Structured-BART such that it leverages source-target alignments and constrains decoding to guarantee synchronicity and consistency across overlapping windows. We evaluate our oracle and parser using the Abstract Meaning Representation (AMR) parsing 3.0 corpus. On the Multi-Sentence development set of AMR 3.0, we show that our transition oracle loses only 8\% of the gold cross-sentential links despite using a sliding window. In practice, this approach also results in a high-quality document-level parser with manageable memory requirements. Our proposed system performs on par with the state-of-the-art pipeline approach for document-level AMR parsing task on Multi-Sentence AMR 3.0 corpus while maintaining sentence-level parsing performance. | ['Salim Roukos', 'Radu Florian', 'Ramon Fernandez Astudillo', 'Tahira Naseem', 'Sadhana Kumaravel'] | 2023-05-26 | null | null | null | null | ['amr-parsing'] | ['natural-language-processing'] | [ 6.61964476e-01 5.00114918e-01 -4.28533442e-02 -5.33742189e-01
-1.44772851e+00 -9.25374806e-01 2.63956696e-01 5.02274632e-01
-3.12421292e-01 1.86875984e-01 1.80184618e-01 -1.26092410e+00
3.62284333e-01 -7.80973196e-01 -7.10615754e-01 7.50122070e-02
-1.58037126e-01 3.34772110e-01 7.95693099e-01 -2.37458304e-01
7.86951706e-02 7.45634213e-02 -1.01610458e+00 9.44518805e-01
5.08890271e-01 3.17597479e-01 5.57055056e-01 1.36640477e+00
-7.83998072e-01 8.59692156e-01 -8.65677655e-01 -8.10653687e-01
9.52228382e-02 -2.54830301e-01 -1.17155373e+00 -2.89799571e-01
3.58460099e-01 -1.37228686e-02 7.81800970e-02 7.19964445e-01
9.87417474e-02 -2.48066813e-01 -1.86362743e-01 -5.24623930e-01
-2.56675810e-01 1.51101291e+00 -4.21940714e-01 3.84243250e-01
6.89997196e-01 -1.44079566e-01 1.53867733e+00 -4.92884487e-01
8.04863334e-01 1.31904805e+00 5.14828086e-01 8.59256387e-01
-1.33549440e+00 -2.42648900e-01 5.38603842e-01 -5.08563161e-01
-8.75410795e-01 -6.61961138e-01 3.70997727e-01 -1.81458414e-01
2.00271893e+00 6.09677792e-01 3.43765527e-01 8.09064984e-01
4.80006546e-01 7.28625834e-01 6.74799323e-01 -9.62679863e-01
8.97174478e-02 -4.02215242e-01 7.44357049e-01 6.07079506e-01
4.73594759e-03 -5.08575141e-01 -6.38431966e-01 -2.24960834e-01
3.64537716e-01 -5.24739921e-01 3.08993042e-01 5.29769838e-01
-1.12379289e+00 7.20488489e-01 -5.99126458e-01 3.16445500e-01
1.02693930e-01 3.53421241e-01 6.98055685e-01 5.67689776e-01
4.68861222e-01 5.01931868e-02 -8.37262392e-01 -4.50742960e-01
-9.67004955e-01 1.40888378e-01 1.12703979e+00 1.11669421e+00
2.75477350e-01 -2.82466877e-02 -7.46552348e-02 8.10185015e-01
4.05370086e-01 3.94510001e-01 4.01985049e-01 -1.06265271e+00
1.16725636e+00 4.15406197e-01 -1.79264918e-01 -2.88997829e-01
-2.08822235e-01 -1.50755972e-01 -2.38959596e-01 -1.23694211e-01
4.69839782e-01 -9.48093235e-02 -8.22799146e-01 1.83539057e+00
4.35691357e-01 -3.38130325e-01 5.56827068e-01 1.88497573e-01
6.53835297e-01 9.41449165e-01 1.86513543e-01 -2.98650503e-01
1.88665056e+00 -7.97992766e-01 -6.55618787e-01 -8.74321580e-01
1.20858932e+00 -1.01438797e+00 1.08029711e+00 4.26111192e-01
-1.74122000e+00 -3.58763427e-01 -1.12979650e+00 -1.97558194e-01
3.97925824e-02 6.87840488e-03 7.33076096e-01 8.48658144e-01
-1.22291887e+00 5.25292873e-01 -1.26288140e+00 -1.80077150e-01
-1.65117756e-01 2.56308258e-01 -4.31137204e-01 4.37206030e-02
-1.15264106e+00 7.37550318e-01 3.51151824e-01 5.63226901e-02
-3.63284647e-01 -4.81531560e-01 -9.98246729e-01 -8.04479569e-02
1.80323839e-01 -4.55586046e-01 1.98930681e+00 -6.10593379e-01
-1.78909004e+00 1.04655075e+00 -5.53147674e-01 -7.07219005e-01
8.05507675e-02 -6.64127111e-01 -4.09868628e-01 3.17637995e-02
1.38323560e-01 3.08475524e-01 5.02724230e-01 -5.23846209e-01
-8.55169058e-01 -3.01607519e-01 2.51368999e-01 -5.04419878e-02
2.01429322e-01 8.42670262e-01 -5.32462776e-01 -4.43529338e-01
2.98373938e-01 -7.15422511e-01 -4.54795748e-01 -8.28530431e-01
-3.60125870e-01 -3.14649194e-01 1.70090407e-01 -8.55773270e-01
1.69748187e+00 -1.90484333e+00 1.81863084e-01 -1.57459691e-01
-1.07192382e-01 6.75007701e-02 -2.25805461e-01 9.10897374e-01
-1.75067574e-01 2.90414780e-01 -5.33212304e-01 -7.13108838e-01
-1.80976003e-01 6.29795015e-01 -6.24813378e-01 1.41844898e-01
4.86688405e-01 7.84363806e-01 -6.41946137e-01 -6.45337343e-01
-3.42307612e-02 -5.93491122e-02 -5.75854182e-01 5.21976411e-01
-5.38774788e-01 4.62153070e-02 -3.02141696e-01 5.94438612e-01
4.18657899e-01 2.22154528e-01 7.76034057e-01 6.46309316e-01
-3.44487339e-01 1.09202361e+00 -1.17124140e+00 2.20777655e+00
-8.57578397e-01 4.35633749e-01 2.33347043e-01 -8.47681582e-01
8.56392980e-01 4.83762503e-01 -2.26401478e-01 -5.40129304e-01
-4.44014877e-01 4.46135640e-01 2.84652442e-01 -1.49541065e-01
8.16479146e-01 -2.15097349e-02 -6.46418929e-01 3.91512960e-01
7.21553043e-02 -7.57667050e-02 2.53191590e-01 4.49147254e-01
1.70365667e+00 3.64154279e-01 6.00072622e-01 -1.35919586e-01
5.95263958e-01 1.55556589e-01 5.16496301e-01 8.76034260e-01
4.28719431e-01 5.33385098e-01 8.82831514e-01 -3.44020784e-01
-1.09580469e+00 -1.02499580e+00 -1.43101318e-02 1.48335493e+00
-4.85541761e-01 -9.93470728e-01 -1.05512416e+00 -6.87217951e-01
-5.05939364e-01 1.12148523e+00 -2.65700698e-01 4.08831328e-01
-1.58904111e+00 -5.06150424e-01 9.74690080e-01 6.03795052e-01
-1.15885980e-01 -9.99323368e-01 -8.00002337e-01 8.84436965e-01
-5.10061346e-02 -1.46387744e+00 -2.32245788e-01 5.65232813e-01
-1.05223370e+00 -8.59039187e-01 -3.40441130e-02 -7.42352366e-01
3.50355148e-01 -2.43066996e-01 1.54768932e+00 8.28807950e-02
-9.12902236e-04 1.33824825e-01 -4.61070806e-01 -1.35692462e-01
-1.31796336e+00 3.39309245e-01 -6.40279293e-01 -6.86720252e-01
1.00195862e-01 -4.82896447e-01 -2.06547469e-01 -4.15063500e-02
-8.90669823e-01 2.85657018e-01 4.92990524e-01 6.71142042e-01
4.62544143e-01 -4.62699234e-01 3.24684411e-01 -1.55147493e+00
5.89151025e-01 -2.12306380e-01 -8.15666795e-01 3.04194570e-01
-2.89301187e-01 2.90770411e-01 1.05579662e+00 -2.40558356e-01
-1.20847940e+00 1.14419714e-01 -8.19057524e-01 5.53592205e-01
-1.65567011e-01 3.41650873e-01 -3.18771094e-01 8.04339468e-01
3.58669668e-01 2.19950303e-01 -4.36044633e-01 -6.68349147e-01
6.69286728e-01 7.32894301e-01 6.55101776e-01 -1.06392407e+00
5.72227597e-01 1.24047967e-02 -2.16371864e-02 -4.44536626e-01
-7.98518240e-01 -5.59466302e-01 -5.40586233e-01 3.47912908e-01
9.04092193e-01 -9.37459528e-01 -3.75647396e-01 2.37514660e-01
-1.91047704e+00 -6.36424422e-01 -2.68021494e-01 -8.73166323e-02
-4.09433663e-01 5.65882027e-01 -1.05435407e+00 -9.74185884e-01
-7.73233175e-01 -1.00310481e+00 1.38406742e+00 -3.64083976e-01
-5.26901782e-01 -8.75586808e-01 2.83823431e-01 2.18457699e-01
1.26683369e-01 -1.18292466e-01 1.20811343e+00 -9.36166525e-01
-3.92556518e-01 -1.63156748e-01 1.49179131e-01 3.36018711e-01
-3.60002458e-01 1.87564120e-02 -7.70212173e-01 2.79422104e-02
-6.46911785e-02 1.12793557e-01 6.04306579e-01 6.42242208e-02
6.97425008e-01 -3.21631372e-01 -1.08331643e-01 2.58159071e-01
1.23105633e+00 1.63263068e-01 5.54748178e-01 4.29765522e-01
4.45134640e-01 5.56193948e-01 7.27362812e-01 7.88911954e-02
4.56482708e-01 5.20248652e-01 2.48803690e-01 2.27962449e-01
-7.99026340e-03 -3.38123232e-01 9.13263083e-01 1.37357473e+00
2.88492054e-01 -2.56173611e-01 -1.07406986e+00 5.40651143e-01
-1.88322723e+00 -5.43003798e-01 -3.49796712e-01 2.18675613e+00
1.10716271e+00 6.23732686e-01 -1.52134627e-01 4.60297288e-03
5.05442202e-01 4.34357285e-01 2.10006580e-01 -1.51260006e+00
2.07440808e-01 7.79479384e-01 5.35141289e-01 9.02172804e-01
-8.26228321e-01 1.38457012e+00 6.43779516e+00 6.36892259e-01
-5.84257483e-01 4.67484027e-01 2.39179194e-01 2.66117185e-01
-5.73181033e-01 4.40501004e-01 -1.42616618e+00 1.45675272e-01
1.84890378e+00 1.28790051e-01 2.20549658e-01 9.06592369e-01
-4.21136916e-02 -7.33883306e-02 -1.47341049e+00 3.63099903e-01
-3.33211064e-01 -1.35365868e+00 -1.36523291e-01 -3.33986491e-01
-6.02131039e-02 7.98203349e-02 -5.01866221e-01 3.95114630e-01
5.99736691e-01 -9.31161582e-01 1.06908894e+00 -1.25465199e-01
7.90413976e-01 -6.28138781e-01 6.75226212e-01 5.35389602e-01
-1.65888274e+00 1.54136270e-01 -4.14190561e-01 -2.73499072e-01
5.19619286e-01 4.60530430e-01 -7.01139688e-01 7.42996514e-01
2.95935392e-01 2.51040608e-01 -4.75126177e-01 1.92083731e-01
-4.49520469e-01 1.10314476e+00 -3.39576900e-01 2.06071548e-02
1.93421558e-01 -7.80624673e-02 7.27999866e-01 1.96611643e+00
2.02595279e-01 7.60958120e-02 1.25364125e-01 2.87435889e-01
2.86464486e-02 2.75775045e-01 -4.47400004e-01 6.31591827e-02
5.66032946e-01 1.13603091e+00 -8.18396807e-01 -5.92372775e-01
-7.09312081e-01 9.98888791e-01 6.18117094e-01 -1.70196518e-01
-5.63149571e-01 -2.91932225e-01 5.34143388e-01 -5.72550297e-02
4.12312478e-01 -6.78545833e-01 -3.09265971e-01 -1.11983299e+00
3.10484827e-01 -1.17182350e+00 6.83035314e-01 -3.97447795e-01
-6.92180276e-01 8.68748486e-01 1.60728440e-01 -5.88407755e-01
-5.89214504e-01 -7.21098840e-01 -7.81118631e-01 9.23045814e-01
-1.36780286e+00 -1.15529704e+00 6.03547812e-01 7.28892535e-02
1.12712753e+00 9.78645906e-02 1.35932291e+00 -4.16635238e-02
-5.58172941e-01 5.12884259e-01 -4.03653115e-01 2.32966989e-01
1.72916010e-01 -1.67036104e+00 1.55729973e+00 1.50128055e+00
4.87007231e-01 1.06121016e+00 7.32889533e-01 -5.99703074e-01
-1.89519978e+00 -9.72572386e-01 1.19185603e+00 -7.53493249e-01
1.04710686e+00 -8.74435484e-01 -9.52814043e-01 1.12793529e+00
3.40545386e-01 -1.84237972e-01 7.14809656e-01 4.18021202e-01
-4.93916392e-01 -3.26367058e-02 -6.73768103e-01 6.13488615e-01
1.22300744e+00 -4.92778569e-01 -1.16235840e+00 2.10188374e-01
1.34814191e+00 -9.91482258e-01 -1.04022193e+00 -6.52792603e-02
5.77143431e-01 -6.55744255e-01 6.48606300e-01 -7.16708660e-01
4.68042910e-01 -1.11026436e-01 -5.28513312e-01 -7.95001686e-01
1.89005718e-01 -1.21791446e+00 -2.22903803e-01 1.45898604e+00
8.95452797e-01 -7.02719331e-01 5.33212423e-01 5.11733413e-01
-5.77642322e-01 -6.74234629e-01 -1.22820759e+00 -7.06444621e-01
3.64238650e-01 -1.26962411e+00 4.01559263e-01 1.41554892e-01
1.34991407e-01 6.84462190e-01 4.89178579e-03 4.44278210e-01
5.41930497e-01 3.58672321e-01 6.21306956e-01 -8.32146704e-01
-9.89145279e-01 1.17709205e-01 -6.07005097e-02 -1.31737578e+00
2.83608645e-01 -9.67888892e-01 2.38988742e-01 -1.57576990e+00
5.13110235e-02 -3.40850323e-01 9.71439481e-02 5.74636698e-01
-4.03687693e-02 -2.84756660e-01 2.48490021e-01 5.28003904e-04
-6.04764521e-01 -3.27121019e-01 5.28670311e-01 2.91500568e-01
-1.72752813e-01 -2.18791447e-05 -4.86553937e-01 6.72963858e-01
7.40409374e-01 -8.97344291e-01 -1.26482412e-01 -8.35353255e-01
5.87535143e-01 5.46429753e-01 -1.96864575e-01 -5.54497600e-01
1.34874070e-02 -1.33874007e-02 -1.44901231e-01 -6.03324592e-01
-2.47406587e-02 -3.24326664e-01 1.26544923e-01 4.48775262e-01
-5.11442244e-01 6.62458777e-01 3.54736507e-01 2.74871439e-01
-2.58606579e-02 -6.65115774e-01 4.66761976e-01 -3.66961479e-01
-5.18034637e-01 -1.58381373e-01 -6.47890627e-01 4.10924196e-01
5.28779030e-01 -1.45421475e-01 -3.98415148e-01 1.83027729e-01
-7.18031585e-01 -3.95152606e-02 2.94477642e-01 3.03053409e-01
4.93688762e-01 -3.04017633e-01 -6.60883427e-01 1.42179251e-01
-9.57092196e-02 3.32850695e-01 -1.58417195e-01 4.40998942e-01
-6.93409622e-01 5.01973927e-01 4.39903289e-01 -5.62213480e-01
-1.76949823e+00 1.10786870e-01 1.10925818e-02 -9.19255972e-01
-9.92610931e-01 8.45521986e-01 -2.61182175e-03 -5.40301979e-01
-2.02737704e-01 -8.60163212e-01 1.52555004e-01 -4.56871986e-01
6.29692197e-01 -1.11234687e-01 4.01807845e-01 -2.51399338e-01
-6.50629163e-01 3.96195054e-01 -3.43532860e-01 -4.90193218e-01
1.33342755e+00 -4.83947024e-02 -3.74676436e-01 5.49111187e-01
8.45469058e-01 6.11270726e-01 -6.93523586e-01 1.85794309e-02
6.28221989e-01 8.13782364e-02 -3.92836720e-01 -4.87966239e-01
-2.31204689e-01 9.38938141e-01 -2.76090298e-02 5.31006396e-01
8.65272641e-01 3.12124670e-01 1.05761003e+00 5.36839068e-01
3.21848869e-01 -9.74520266e-01 -3.35309118e-01 8.47351074e-01
4.83049899e-01 -7.88653612e-01 -2.55942762e-01 -6.69857144e-01
-3.95018816e-01 1.38131475e+00 2.03574076e-01 -5.29374480e-02
1.28188312e-01 9.61176634e-01 9.58333015e-02 1.24410488e-01
-1.35390532e+00 5.66477925e-02 -1.28052041e-01 3.44054341e-01
9.20299172e-01 2.52445221e-01 -5.51614523e-01 9.22693312e-01
-4.88288701e-01 -4.51701522e-01 7.31119096e-01 1.24370110e+00
-5.86713731e-01 -1.83484364e+00 -1.50323823e-01 -1.86877474e-02
-1.39738309e+00 -7.10562646e-01 -1.72914565e-02 8.96753550e-01
-4.52185482e-01 1.07709837e+00 1.14987507e-01 7.35962987e-02
3.88583362e-01 4.17363018e-01 6.96403980e-01 -1.29685378e+00
-8.63695681e-01 1.70666367e-01 1.04205060e+00 -7.12053418e-01
-1.79786772e-01 -7.00467169e-01 -1.61687851e+00 1.26832258e-02
-2.19443232e-01 2.31334612e-01 8.56513023e-01 8.92053068e-01
1.89313814e-01 5.50676286e-01 4.03843731e-01 -1.34832114e-01
-7.14231372e-01 -8.69226933e-01 -1.38081297e-01 -1.63543731e-01
1.64214335e-02 3.70444268e-01 -1.86294079e-01 2.45825067e-01] | [10.383515357971191, 9.59814167022705] |
178f5286-9a23-49c8-bd08-86a5add44753 | rafola-a-rationale-annotated-corpus-for | 2205.02684 | null | https://arxiv.org/abs/2205.02684v1 | https://arxiv.org/pdf/2205.02684v1.pdf | RaFoLa: A Rationale-Annotated Corpus for Detecting Indicators of Forced Labour | Forced labour is the most common type of modern slavery, and it is increasingly gaining the attention of the research and social community. Recent studies suggest that artificial intelligence (AI) holds immense potential for augmenting anti-slavery action. However, AI tools need to be developed transparently in cooperation with different stakeholders. Such tools are contingent on the availability and access to domain-specific data, which are scarce due to the near-invisible nature of forced labour. To the best of our knowledge, this paper presents the first openly accessible English corpus annotated for multi-class and multi-label forced labour detection. The corpus consists of 989 news articles retrieved from specialised data sources and annotated according to risk indicators defined by the International Labour Organization (ILO). Each news article was annotated for two aspects: (1) indicators of forced labour as classification labels and (2) snippets of the text that justify labelling decisions. We hope that our data set can help promote research on explainability for multi-class and multi-label text classification. In this work, we explain our process for collecting the data underpinning the proposed corpus, describe our annotation guidelines and present some statistical analysis of its content. Finally, we summarise the results of baseline experiments based on different variants of the Bidirectional Encoder Representation from Transformer (BERT) model. | ['Riza Batista-Navarro', 'Viktor Schlegel', 'Erick Mendez Guzman'] | 2022-05-05 | null | https://aclanthology.org/2022.lrec-1.386 | https://aclanthology.org/2022.lrec-1.386.pdf | lrec-2022-6 | ['multi-label-text-classification', 'multi-label-text-classification'] | ['methodology', 'natural-language-processing'] | [ 8.35962176e-01 6.04752004e-01 -5.59233010e-01 -5.01352012e-01
-5.60170949e-01 -6.36407852e-01 1.06381893e+00 4.24481153e-01
-5.90874732e-01 8.91932726e-01 8.06811929e-01 -6.72922790e-01
-5.77204347e-01 -4.75393206e-01 -2.04976186e-01 -4.76786435e-01
3.72206062e-01 1.01092505e+00 -2.50085026e-01 -4.79020447e-01
5.05275130e-01 2.66128868e-01 -1.35898185e+00 5.54087996e-01
9.46160436e-01 5.83328545e-01 2.84931988e-01 4.19993103e-01
-1.15910485e-01 1.34480226e+00 -7.32059062e-01 -1.01647019e+00
1.23876788e-01 -7.17724979e-01 -1.35475326e+00 -3.10114235e-01
6.44879192e-02 -5.84639162e-02 7.37998262e-02 7.80793428e-01
5.59753895e-01 -4.16208565e-01 9.15682316e-01 -1.01359010e+00
-7.24002063e-01 9.16166306e-01 -1.99400321e-01 4.16559368e-01
3.79531354e-01 -2.27735803e-01 1.00604224e+00 -4.27391142e-01
1.08810568e+00 1.28926325e+00 6.75240576e-01 4.43923652e-01
-1.05564511e+00 -7.80264795e-01 -3.95063549e-01 3.88890743e-01
-8.28858256e-01 -6.47339940e-01 4.65018123e-01 -8.50144625e-01
1.08309066e+00 3.48543167e-01 5.30664086e-01 1.30639827e+00
1.16370030e-01 3.59086990e-01 1.51892138e+00 -9.14908648e-01
-2.56656468e-01 4.16481823e-01 -2.42035672e-01 4.93342787e-01
9.45515335e-02 -1.01370057e-02 -5.12840211e-01 -2.24363521e-01
2.62707323e-01 -2.44428232e-01 1.86770186e-01 9.53114480e-02
-1.15423059e+00 1.20186007e+00 1.73686206e-01 8.84147644e-01
-3.83343756e-01 1.08527333e-01 7.29475558e-01 4.45183456e-01
8.96211505e-01 3.69651794e-01 -5.06718695e-01 -5.68928599e-01
-8.37147415e-01 1.21456414e-01 7.32320070e-01 5.80976665e-01
4.02422637e-01 -4.19147491e-01 3.10791973e-02 1.04754508e+00
4.94189262e-01 5.39450169e-01 2.06513703e-01 -9.86946344e-01
7.01768517e-01 8.64781857e-01 -1.46399111e-01 -1.17693353e+00
-4.58922088e-01 -2.15041608e-01 -7.12030351e-01 -3.47315259e-02
4.48457330e-01 5.33536449e-02 -7.36961246e-01 1.45171440e+00
9.92683461e-04 -5.55408001e-01 1.06504306e-01 5.25498390e-01
7.03488648e-01 3.38945776e-01 3.55588555e-01 -2.42144987e-01
1.70871687e+00 -4.72408056e-01 -1.14930081e+00 -2.65022933e-01
9.19729531e-01 -8.77317667e-01 5.69300711e-01 1.19406953e-01
-7.46946096e-01 -1.32393807e-01 -4.58391041e-01 -2.21422106e-01
-5.11000752e-01 -2.18009800e-02 6.40270114e-01 1.03270376e+00
-5.53422570e-01 3.82160276e-01 -6.33269489e-01 -6.83960617e-01
7.20820606e-01 1.98044449e-01 -4.64343995e-01 9.76141244e-02
-1.47885609e+00 1.50724268e+00 4.14360583e-01 2.00003937e-01
-2.42288291e-01 -2.89640874e-01 -9.26523209e-01 -4.49175715e-01
3.63326818e-01 -1.68872371e-01 1.00048673e+00 -1.14866114e+00
-7.49061704e-01 1.58228803e+00 3.54601666e-02 -4.84241784e-01
5.62110722e-01 -8.48503187e-02 -5.43536842e-01 1.53019309e-01
7.71521509e-01 5.42222917e-01 4.35487807e-01 -1.16925764e+00
-9.22377348e-01 -3.42498332e-01 8.85422993e-03 -7.34761031e-03
-1.73995003e-01 8.76626194e-01 4.23411846e-01 -7.45480001e-01
-2.01973349e-01 -8.77085686e-01 1.05656721e-01 -5.67200184e-01
-1.20413959e-01 -3.58687222e-01 5.68012655e-01 -1.03725982e+00
1.41543472e+00 -1.95227051e+00 7.66291320e-02 -2.73058210e-02
1.24517642e-01 2.22213268e-01 3.84584606e-01 9.63979125e-01
7.58315772e-02 4.07384664e-01 -5.77342331e-01 -3.46030667e-02
2.73056000e-01 6.86919808e-01 -3.54219228e-01 6.26176119e-01
1.84021473e-01 8.28411639e-01 -1.09259140e+00 -8.71983290e-01
1.37027189e-01 4.08362567e-01 -2.52243221e-01 -2.47378185e-01
2.95917004e-01 5.97874999e-01 -2.72934258e-01 7.14496672e-01
1.75639436e-01 1.30490914e-01 3.56823474e-01 1.31892279e-01
-3.32025409e-01 6.31165087e-01 -5.82247436e-01 1.29785204e+00
-5.41813195e-01 9.09951091e-01 1.70095414e-02 -1.13703299e+00
9.58025932e-01 5.90523243e-01 2.51994073e-01 -8.93637896e-01
1.66407511e-01 7.57812798e-01 2.00551450e-01 -7.05082178e-01
5.07832110e-01 -5.36559582e-01 -3.20606917e-01 7.48123467e-01
2.48637423e-02 -8.26150030e-02 4.15623933e-01 7.60788023e-02
1.03435361e+00 2.73753315e-01 5.91752648e-01 -3.34450394e-01
5.94538510e-01 1.17400430e-01 5.16700089e-01 5.26992857e-01
-1.62821069e-01 1.32190183e-01 6.55714035e-01 -8.45130026e-01
-1.13196230e+00 -3.50531340e-01 -7.75059760e-01 1.28879297e+00
-3.44401062e-01 -3.68079782e-01 -4.97006804e-01 -8.71162534e-01
-2.40653008e-01 7.07122982e-01 -8.39674473e-01 3.29035968e-01
-7.86928833e-01 -7.35875607e-01 9.90113854e-01 1.31449804e-01
3.31714392e-01 -1.65652120e+00 -1.17781138e+00 3.51004273e-01
-5.52083433e-01 -9.20338333e-01 3.76437247e-01 4.79683012e-01
-4.39217985e-01 -1.30258679e+00 -5.33666968e-01 -7.90791631e-01
5.04003227e-01 -4.34954584e-01 9.67218935e-01 3.76828164e-01
-1.00994997e-01 -1.23192452e-01 -8.18643630e-01 -6.06955290e-01
-1.12029088e+00 3.32638413e-01 -1.59854278e-01 -4.71294612e-01
4.96979445e-01 -3.39633018e-01 -3.39671001e-02 1.98759377e-01
-1.02049839e+00 2.28972033e-01 6.10767365e-01 7.85992146e-01
-6.22698106e-02 -3.17794201e-03 7.73206294e-01 -1.39272213e+00
7.09859610e-01 -6.67951465e-01 -4.96735424e-02 1.27339050e-01
-6.12835288e-01 -1.06771208e-01 7.54217282e-02 -2.39416696e-02
-1.16720402e+00 -2.76653528e-01 -3.26196492e-01 6.49800599e-01
-4.07869458e-01 5.55609643e-01 2.66086072e-01 2.31590182e-01
8.08247268e-01 -3.56566370e-01 -1.39163539e-01 -5.47795117e-01
3.44961554e-01 1.42138016e+00 4.05993819e-01 -4.04428869e-01
6.19602144e-01 3.11753273e-01 -7.48803094e-02 -6.05949759e-01
-8.68474662e-01 -3.81718367e-01 -8.30595911e-01 -3.66500944e-01
9.47137833e-01 -5.27513146e-01 -4.81892765e-01 1.51040599e-01
-1.16420889e+00 -4.20441568e-01 -2.40940556e-01 3.64063084e-01
-5.51628709e-01 1.67263985e-01 -5.40107727e-01 -1.18517435e+00
-3.99674475e-01 -8.28377426e-01 1.02598858e+00 -3.00822347e-01
-8.32079947e-01 -1.11775029e+00 9.63125154e-02 1.02509916e+00
3.92346025e-01 5.66938579e-01 1.13815475e+00 -7.68041313e-01
4.22721565e-01 -2.38456279e-02 -2.08031401e-01 1.43801138e-01
2.20390037e-01 -3.86635870e-01 -9.43179190e-01 1.55941218e-01
1.83303535e-01 -6.45308018e-01 6.76736295e-01 -1.60262242e-01
3.75898749e-01 -7.94511080e-01 -3.35538924e-01 -1.45172343e-01
1.14403236e+00 2.94118941e-01 5.60131788e-01 9.08141553e-01
4.75991845e-01 1.30510223e+00 7.14100420e-01 2.51290649e-01
4.67995673e-01 7.78658807e-01 3.22800487e-01 7.57015646e-02
9.81880538e-03 1.61779717e-01 2.80073196e-01 6.81941211e-01
-5.87906897e-01 -1.86430529e-01 -1.35767341e+00 7.67834187e-01
-1.71039581e+00 -1.28011894e+00 -5.28792560e-01 1.47842562e+00
1.03163397e+00 1.26044214e-01 5.81723861e-02 6.55483544e-01
7.03062952e-01 1.19615592e-01 3.86736810e-01 -9.29782569e-01
-8.94890428e-02 3.31201643e-01 4.20599014e-01 6.02680027e-01
-1.03295159e+00 8.63471329e-01 5.92498446e+00 8.04939270e-01
-3.37809235e-01 4.68111098e-01 4.53406036e-01 3.09191793e-01
-2.75762379e-01 1.30286530e-01 -4.09538925e-01 6.01412117e-01
1.03076124e+00 9.03989077e-02 4.05997455e-01 4.04079705e-01
3.95902060e-03 -2.25977242e-01 -7.52544880e-01 3.73997599e-01
1.83381632e-01 -1.16569400e+00 -4.06772405e-01 4.25149828e-01
6.18463635e-01 8.52153972e-02 -3.16512197e-01 1.38920277e-01
2.03314885e-01 -1.10246515e+00 1.13312638e+00 1.61542118e-01
1.02624059e+00 -4.76392180e-01 1.26767194e+00 5.37992001e-01
-7.74555981e-01 -3.61823916e-01 -2.59141084e-02 -4.38644022e-01
4.25776929e-01 2.55076408e-01 -6.67312205e-01 6.38695955e-01
5.84444404e-01 6.72723353e-01 -6.29577875e-01 3.28324378e-01
-4.75735754e-01 7.00805128e-01 -1.56800210e-01 6.01524822e-02
3.74627084e-01 4.32974100e-03 1.81760862e-01 1.45096040e+00
1.64896950e-01 7.80443177e-02 -3.85234088e-01 5.68925798e-01
8.91704932e-02 8.05089921e-02 -7.48537719e-01 -3.41680557e-01
4.68877196e-01 1.06241012e+00 -1.06578684e+00 -1.51343510e-01
-4.66643155e-01 8.24149728e-01 1.66205317e-01 -1.29531890e-01
-4.47068065e-01 -3.24683100e-01 1.32537976e-01 2.26829112e-01
-9.96155888e-02 2.96842128e-01 -2.56603092e-01 -5.08261144e-01
-2.25691766e-01 -1.03977191e+00 5.53505719e-01 -4.98605251e-01
-1.11997378e+00 5.53182483e-01 2.04807386e-01 -6.33760810e-01
-5.65422833e-01 -4.51033026e-01 1.32845163e-01 7.75976837e-01
-1.19821894e+00 -1.46940482e+00 1.42327383e-01 -1.27192333e-01
4.10260975e-01 -2.28216529e-01 1.28264856e+00 5.07405519e-01
-3.62088494e-02 6.55988464e-04 -1.22286670e-01 2.58975536e-01
4.99861330e-01 -1.21498203e+00 3.41379374e-01 2.76586473e-01
2.27493003e-01 3.99461329e-01 7.36598492e-01 -9.73991573e-01
-5.47921956e-01 -6.84963882e-01 2.00693989e+00 -7.92337775e-01
8.84181678e-01 -2.97897965e-01 -5.38814902e-01 7.98055649e-01
4.15037483e-01 -5.39299846e-01 1.05121231e+00 6.77406639e-02
-4.94236127e-02 3.95146400e-01 -1.33975995e+00 7.19749033e-02
1.10382378e+00 -6.38262749e-01 -1.05539656e+00 6.10233009e-01
2.39657134e-01 -2.11652115e-01 -8.42267454e-01 2.73669839e-01
6.82195842e-01 -8.13859165e-01 5.60562611e-01 -4.56520647e-01
8.35373700e-01 1.23416461e-01 -8.35648775e-02 -9.16642547e-01
-2.96434075e-01 -4.53196615e-01 2.71365732e-01 1.51432848e+00
3.83292139e-01 -5.73553741e-01 4.97828424e-01 3.61127943e-01
-1.53183907e-01 -5.61994493e-01 -1.34684038e+00 -5.17451286e-01
-2.97416537e-03 -6.21681571e-01 4.19246107e-01 1.39737427e+00
2.32132435e-01 4.48919922e-01 -5.54292977e-01 -4.62628394e-01
2.82044858e-01 -1.63823903e-01 4.72111225e-01 -1.49894059e+00
1.28038391e-01 -3.83890361e-01 -5.17050445e-01 -2.55103707e-02
3.14395308e-01 -1.17865372e+00 -2.06953824e-01 -2.04110241e+00
3.42318565e-01 -6.04415119e-01 1.45592302e-01 7.17422664e-01
1.70330226e-01 8.15187216e-01 1.51164994e-01 4.69498277e-01
-2.70315289e-01 6.59003183e-02 8.66367459e-01 -1.69301089e-02
1.05380127e-03 -2.63849735e-01 -8.50034237e-01 7.89997041e-01
9.46661472e-01 -1.03108525e+00 9.98053141e-03 -4.85429883e-01
9.67817783e-01 -3.22158813e-01 2.91066557e-01 -4.74758744e-01
-1.49336532e-01 -3.32316667e-01 2.62162052e-02 -3.95632803e-01
1.00146502e-01 -1.08510554e+00 4.81716245e-01 9.17211413e-01
-5.54910481e-01 -1.66648701e-01 -1.01548448e-01 2.27397263e-01
7.54872803e-03 -7.05601752e-01 3.79233062e-01 -9.56701264e-02
-2.75829256e-01 -4.60166216e-01 -7.69488454e-01 1.49444073e-01
8.64141226e-01 -2.20876455e-01 -5.58973670e-01 -2.73552626e-01
-3.39356989e-01 5.76574802e-02 4.01070237e-01 4.39706296e-01
6.73060492e-02 -1.34235549e+00 -1.03412235e+00 -8.95224586e-02
2.05710426e-01 -4.13739085e-01 -1.93812445e-01 8.57789636e-01
-7.63256788e-01 6.49860322e-01 -3.25292647e-01 2.47115400e-02
-1.26459253e+00 3.23218137e-01 -1.96055532e-01 -3.55423003e-01
-7.60796368e-01 5.11605620e-01 -2.40361676e-01 -5.36470771e-01
4.54965993e-05 1.25774309e-01 -7.25244582e-01 6.21392012e-01
3.16751331e-01 6.88415527e-01 -1.21728048e-01 -1.49209988e+00
-5.74529469e-01 3.07226598e-01 1.99769393e-01 -3.08920890e-01
1.69308507e+00 -2.11157888e-01 -5.45893252e-01 5.35193205e-01
8.89260530e-01 1.15186118e-01 -3.78456354e-01 -2.81980122e-03
5.02019763e-01 -4.87059265e-01 -2.68539578e-01 -1.05916727e+00
-5.88455260e-01 6.40189886e-01 4.43244398e-01 6.40429497e-01
8.50920737e-01 4.00731653e-01 4.83273327e-01 3.39795738e-01
1.84277013e-01 -1.33401835e+00 -3.56661022e-01 3.75703335e-01
1.00750196e+00 -1.14296782e+00 2.35323057e-01 -4.73551333e-01
-7.54999280e-01 9.40414369e-01 -1.32781416e-01 5.08472264e-01
1.82061553e-01 2.06462368e-01 4.94821817e-01 -6.88545167e-01
-3.36137056e-01 -3.05739224e-01 1.13574959e-01 7.66507626e-01
7.53762722e-01 1.24838576e-01 -1.05278039e+00 4.62582588e-01
-4.95278448e-01 -1.22415423e-01 2.80817926e-01 9.91596878e-01
-3.97416294e-01 -1.50979936e+00 -4.20210838e-01 6.76944554e-01
-1.16469252e+00 -1.14647597e-01 -8.63297701e-01 9.37052071e-01
6.88457727e-01 1.26814008e+00 -1.33296460e-01 -1.41236380e-01
1.17799744e-01 1.25583038e-01 4.23552394e-01 -7.16034472e-01
-1.05422401e+00 -2.52791107e-01 7.96639502e-01 -9.45281684e-02
-1.18969226e+00 -7.55700052e-01 -9.48216975e-01 -3.09394032e-01
-4.26480800e-01 3.11787456e-01 8.22358131e-01 1.29013407e+00
-1.05018526e-01 2.35605195e-01 2.21606374e-01 -6.52275741e-01
-7.71312043e-02 -1.26784313e+00 -4.31038767e-01 4.62592065e-01
7.02710869e-03 -7.69998431e-01 -3.33858192e-01 2.05540776e-01] | [9.471138000488281, 9.577008247375488] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.