Lighter and faster: A multi-scale adaptive graph convolutional network for skeleton-based action recognition

Author:

Jiang Yuanjian,Deng Hongmin

Funder

Natural Science Foundation of Sichuan Province

Publisher

Elsevier BV

Reference51 articles.

1. Monitoring activity for recognition of illness in experimentally infected weaned piglets using received signal strength indication ZigBee-based wireless acceleration sensor;Ahmed;Asian-Australasion J. Anim. Sci.,2016

2. JOLO-GCN: Mining Joint-Centered Light-Weight Information for Skeleton-Based Action Recognition;Cai,2021

3. Chen, H., 2022. Research on Key Technologies of Human Action Intelligent Recognition based on Virtual Reality. In: ICCSIE 22: Proceedings of the 7th International Conference on Cyber Security and Information Engineering. ISBN: 978-1-4503-9741-4, pp. 851–4.

4. Channel-wise topology refinement graph convolution for skeleton-based action recognition;Chen,2021

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