Hierarchical Graph Convolutional Skeleton Transformer for Action Recognition
Author:
Affiliation:
1. Institute of Information Engineering, Chinese Academy of Sciences,Beijing,China
2. Beijing Institute of Technology,Beijing,China
3. School of Cyber Security, University of Chinese Academy of Sciences,Beijing,China
Funder
National Key Research and Development Program of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9859562/9858923/09859781.pdf?arnumber=9859781
Reference16 articles.
1. NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis
2. Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding;liu;IEEE Trans-actions on Pattern Analysis and Machine Intelligence,2019
3. Spatio-Temporal Graph Routing for Skeleton-Based Action Recognition
4. Actional-structural graph convolutional net-works for skeleton-based action recognition;li;Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,0
5. Skeleton-Based Action Recognition With Shift Graph Convolutional Network
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