Constructing Stronger and Faster Baselines for Skeleton-Based Action Recognition
Author:
Affiliation:
1. School of Artificial Intelligence, University of Chinese Academy of Sciences (UCAS), Beijing, China
2. College of Electrical Engineering and Automation, Shandong University of Science and Technology (SDUST), Qingdao, China
Funder
National Key R&D Program of China
National Natural Science Foundation of China
Shandong Provincial Key Research and Development Program
CAS-AIR
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software
Link
http://xplorestaging.ieee.org/ielx7/34/10008914/09729609.pdf?arnumber=9729609
Reference62 articles.
1. Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition
2. A feature-based approach to people re-identification using skeleton keypoints
3. Graph Edge Convolutional Neural Networks for Skeleton-Based Action Recognition
4. One-Shot Person Re-identification with a Consumer Depth Camera
5. NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis
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