AdaSGN: Adapting Joint Number and Model Size for Efficient Skeleton-Based Action Recognition
Author:
Affiliation:
1. Chinese Academy of Sciences,NLPR & AIRIA, Institute of Automation
Funder
Chinese Academy of Sciences
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9709627/9709628/09710612.pdf?arnumber=9710612
Reference42 articles.
1. View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data
2. Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition;yan;AAAI,2018
3. Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group
4. Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition
5. Skeleton-Based Action Recognition with Spatial Reasoning and Temporal Stack Learning;si;the European Conference on Computer Vision (ECCV),2018
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