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Open access Sep 2026

JRTE-GCN: A Graph Convolutional Network with Joint Relation Topology Evolution Modeling for Skeleton-Based Action Recognition

Graph convolutional networks (GCNs) have become a mainstream approach for skeleton-based action recognition by modeling spatial dependencies among human joints. However, existing methods mostly rely on learnable adjacency matrices or average relations over the entire action sequence to construct graph structures. Such...

Qun You, Shao-Qi Zhang, Xia Zou et al. · 0 citations

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