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Conference Open access Sep 2026

Riemannian Graph Convolutional Network for Skeleton-Based Two-Person Interaction Recognition

This work model high-order skeletal statistics via Gaussian embedding and propose a Riemannian network to capture inter-subject interactions and global correlations and shows that RGCN provides a competitive and geometrically grounded alternative for skeleton-based interaction recognition.

Rui Wang, Zi-Hao Bi, Chen Hu et al. · 0 citations

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