Optical Flow Features
Optical Flow Features is a type of motion representation in computer vision that characterizes the apparent motion of pixels between consecutive image frames by encoding the direction and magnitude of displacement vectors derived from temporal intensity changes.
634
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40K
Citations
1.9K
Authors
660
Institutions
Publications per year
2017–2026
346
Parents
634
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
Action recognition by dense trajectories
Heng Wang, Alexander Kläser, Cordelia Schmid et al. · 2011 · 2.2K citations · Full text
Towards Understanding Action Recognition
Hueihan Jhuang, Jüergen Gall, Silvia Zuffi et al. · 2013 · 924 citations
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Chinese Academy of Sciences
Beijing, China
15 h-index
43 publications
7.3K citations

Centre National de la Recherche Scientifique
Paris, France
11 h-index
23 publications
719 citations

Shanghai Jiao Tong University
Shanghai, China
11 h-index
31 publications
3.6K citations
University of Chinese Academy of Sciences
Beijing, China
10 h-index
18 publications
1.8K citations

Harbin Institute of Technology
Harbin, China
10 h-index
26 publications
863 citations
Tsinghua University
Beijing, China
9 h-index
18 publications
1.8K citations

Peking University
Beijing, China
9 h-index
27 publications
772 citations
Institute of Automation
Beijing, China
8 h-index
22 publications
5.3K citations
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Repository · 23 publications · 1.2K citations
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13 publications · 977 citations
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10 publications · 303 citations
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