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Author

Hongwei Chen

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Aug 2026

HPCLR: hierarchical part-aware contrastive learning for skeleton-based action recognition

HPCLR is a hierarchical part-aware contrastive learning framework for skeleton-based action recognition that leverages the consistency among joint, motion, and bone modalities to select more reliable positive samples, thereby contributing to more stable and informative multi-stream skeleton representations.

Hong-Wei Chen, Min Wei, Yuanyuan Zhu et al. · 0 citations
Aug 2026

Self-supervised skeleton action recognition based on graph prototype learning

This work presents a novel self-supervised architecture centered on graph prototype learning that sets a new state-of-the-art on the ARMM dataset with an accuracy of 95.70%, substantiating the efficacy and transferability of prototype-guided self-supervised learning for skeleton-based action representation.

Zhijie Xu, Hong-Wei Chen, Xia Li · 0 citations

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