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One for All: Generalist Foundation Model for Cross-Sensor Skeleton Representation Learning
For learning generalizable motion representations from large-scale unlabeled data, Self-supervised learning (SSL) has become a widely adopted methodology. However, existing approaches are primarily limited by the inherent heterogeneity of skeleton data---characterized by varying joint counts, indexi
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