Self-supervised Action Recognition
Self-Supervised Action Recognition is a machine learning approach within video understanding that belongs to the category of action recognition methods, distinguished by its use of automatically generated supervisory signals from unlabeled video data to learn discriminative action representations without manual annotation.
154
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14.6K
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447
Authors
173
Institutions
Publications per year
2017–2026
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154
A Survey on Contrastive Self-Supervised Learning
Ashish Jaiswal · MDPI (MDPI AG) · 2020 · 1.5K citations · Full text
Actional-Structural Graph Convolutional Networks for Skeleton-Based Action Recognition
Maosen Li, Siheng Chen, Xu Chen et al. · 2019 · 1.2K citations
VideoBERT: A Joint Model for Video and Language Representation Learning
Chen Sun, Austin Myers, Carl Vondrick et al. · 2019 · 1.1K citations
End-to-End Learning of Visual Representations From Uncurated Instructional Videos
Antoine Miech, Jean-Baptiste Alayrac, Lucas Smaira et al. · 2020 · 588 citations
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173
University of Oxford
Oxford, United Kingdom
11 h-index
17 publications
3.2K citations

Chinese Academy of Sciences
Beijing, China
9 h-index
24 publications
1.5K citations
Google (United States)
Mountain View, United States
9 h-index
36 publications
11.4K citations
University of Chinese Academy of Sciences
Beijing, China
8 h-index
17 publications
1.1K citations

South China University of Technology
Guangzhou, China
7 h-index
18 publications
945 citations

Peking University
Beijing, China
7 h-index
16 publications
2.1K citations

University of Central Florida
Orlando, United States
6 h-index
15 publications
1.1K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
5 h-index
9 publications
380 citations
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Repository · 32 publications · 2.2K citations
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Conference · 8 publications · 899 citations
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Conference · 8 publications · 380 citations
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Conference · 8 publications · 331 citations
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3 publications · 101 citations
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