Ange Chen, Chengdong Wu*, Chuanjiang Leng
CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 173-191, 2025, DOI:10.32604/cmc.2024.059284
- 03 January 2025
Abstract Previous multi-view 3D human pose estimation methods neither correlate different human joints in each view nor model learnable correlations between the same joints in different views explicitly, meaning that skeleton structure information is not utilized and multi-view pose information is not completely fused. Moreover, existing graph convolutional operations do not consider the specificity of different joints and different views of pose information when processing skeleton graphs, making the correlation weights between nodes in the graph and their neighborhood nodes shared. Existing Graph Convolutional Networks (GCNs) cannot extract global and deep-level skeleton structure information and view… More >
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