Optical Flow Estimation
Optical Flow Estimation is the computational task of determining the apparent motion of pixels between consecutive frames in a video sequence by estimating the two-dimensional displacement vectors that correspond to the projection of three-dimensional scene motion onto the image plane.
2K
Publications
154.8K
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4.8K
Authors
1.3K
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Publications per year
2017–2026
608
2K
FlowNet: Learning Optical Flow with Convolutional Networks
Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg et al. · 2015 · 4.2K citations
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
Eddy Ilg, N. Michael Mayer, Tonmoy Saikia et al. · 2017 · 3.3K citations
PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume
Deqing Sun, Xiaodong Yang, Ming-Yu Liu et al. · 2018 · 2.7K citations
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Max Planck Institute for Intelligent Systems, Germany
23 publications · 7.3K citations
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14
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13
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13
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1–5 of 4.8K
1.3K
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
27 h-index
96 publications
13.5K citations
University of Maryland, College Park
College Park, United States
26 h-index
68 publications
4.7K citations

Centre National de la Recherche Scientifique
Paris, France
25 h-index
76 publications
5.7K citations
ETH Zurich
Zurich, Switzerland
23 h-index
58 publications
6.2K citations

Australian National University
Canberra, Australia
22 h-index
61 publications
4.1K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
22 h-index
78 publications
9.5K citations
Massachusetts Institute of Technology
Cambridge, United States
20 h-index
46 publications
25.6K citations
Carnegie Mellon University
Pittsburgh, United States
19 h-index
49 publications
5K citations
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TPAMI · 77 publications · 11.6K citations
47
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75 publications · 4.4K citations
38
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37 publications · 13.6K citations
31
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42 publications · 1.9K citations
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Repository · 83 publications · 3.3K citations
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