Exploring Spatial Temporal Graph Convolution Networks For Skeleton Based Action Recognition
Welcome to our comprehensive guide on Spatial Temporal Graph Convolution Networks For Skeleton Based Action Recognition.
- Title : MULTI SCALE
- Authors: Zhu, Anqi*; Ke, Qiuhong; Gong, Mingming; Bailey, James Description:
- Papers ▭▭▭▭▭▭▭▭▭▭▭▭
- Authors: Zhen Xu, Quanming Yao, Yong Li, Qiang Yang https://2023.automl.cc/program/accepted_papers/
- Authors: Ziyu Liu, Hongwen Zhang, Zhenghao Chen, Zhiyong Wang, Wanli Ouyang Description:
In-Depth Information on Spatial Temporal Graph Convolution Networks For Skeleton Based Action Recognition
ST-GCN is the first GCN-based method for the task of Human Authors: Ke Cheng, Yifan Zhang, Xiangyu He, Weihan Chen, Jian Cheng, Hanqing Lu Description: Test of a
Authors: Xikun Zhang, Chang Xu, Dacheng Tao Description:
In summary, understanding Spatial Temporal Graph Convolution Networks For Skeleton Based Action Recognition gives us a better perspective.