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Zhijie Xu

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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, Hongwei Chen, Xia Li · 0 citations