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, , . , # 2 n , , . , n LM n . 9 4 n . 0123 n . A C @Takarasawa_

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- - , n - - n - , - . : - -, - L C M - - . O 3 CVPR2020 4

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1 9 ) blOi n fc 1 1 ? h blOF Cfc n ,1 9 ? p 1 ? ,1 9 ? V hO I 1 ? n , . SO T ( . OL g a Moed 4 Scene Flow

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. , .,. . 8 CVPR2020 kzykmyzw EPC++ EPC

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, - . + D C LMT PS - E 10 V. Guizilini et. al., “3D Packing for Self-Supervised Monocular Depth Estimation”, CVPR 2020

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, . , + 3, 3 T RCD L M CD D , 3 11 S. Wu et. al., “Unsupervised Learning of Probably Symmetric Deformable 3D Objects From Images in the Wild”, CVPR 2020

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, . , + 3, 3 T RCD L M CD D , 3 12 S. Wu et. al., “Unsupervised Learning of Probably Symmetric Deformable 3D Objects From Images in the Wild”, CVPR 2020 ! scene flow & depth "

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- . ) ( ., f , , CW T N n ) , , , bi h P LO , n , h Pf M ec , lp , , dg n m a . , ., f op n 082 1 21 2 - 2 . , 2 0 13 PWC-Net " ! #$

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, - . - ad P C SL n c - ad . - h O MWTN n - g b e - f 14 PWC-Net optical flow estimator Scene flow Optical flow 2

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, . , , , Tm c c Tb ! "# faDi L M hMl c _ kn {%& , %&() } eTkSgC {+& , +&() } {",- , ".- } Tdn fa 18 Disparity loss Scene Flow loss

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, . - , . 1, 1 . , T P hMd e . 1, L 1 h i M Cb hMag h . 1, M c , 19 Photometric loss Smoothness loss Synthesized left image Occlusion mask ➤ Disparity loss occlusion mask disparity map Left image SSIM L1

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,2 2 -1 2 . 1 2- 1 P lSet ah 1 ➤ . . . 1 i E .2 2 i M m p r sS C l conSd T b L 1 sSgM 20 Photometric loss Smoothness loss Disparity

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+2 2 .,1 2. - ,. . L L Lc d 1 . ,. . 1 . 2, -2 2 ,. . e L bC L b a b L 1 . 2, ,, -.- T S LM 21 Scene flow photometric loss 3D point reconstruction loss Smoothness loss Synthesized t image Occlusion mask ➤ occlusion mask flow t image ➤ Edge-aware 2nd order smoothness Depth Optical flow

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- + .3 2 . 1 L C 3 M T . . aS , c aSD d b , , c . 1 eD 22 Scene flow photometric loss 3D point reconstruction loss Smoothness loss d(t+1)! Occlusion mask d(t) Scene flow ! ➤ Edge-aware 2nd order smoothness ➤ depth map " scene flow

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. , .,. . L C C 23 !" # !" $ !" !"%& '" # ()* '" '"%& '" stereo config ()* Disparity loss t+1 Scene flow loss backward '" ()*

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, . - , L FC M , , S 26 Multi-task methods (Depth, Ego-motion, Optical flow) Energy-optimization (semi-supervised) • D1-allreference frame disparity • D2-allreference frame disparity • F1-alloptical flow end-point • SF-all scene flow

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. , .,. . 27 Semi-supervised fine tuning

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. , . 33 D D L M D T D C D . D Disparity loss Scene Flow loss ><@2! () 4/ 0,><@2! () loss @>1"')+%"C = AB*% - .> :?3 $+$+- disparity loss 875!; 69

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