Jidong Kuang

GenPrior: Unleashing Text-to-Motion Generative Priors for Zero-Shot Skeleton-based Action Recognition

This work proposes GenPrior, the first framework to exploit generative priors from pre-trained Text-to-Motion (T2M) models for ZSAR, and introduces Dispersion-Gated Feature Fusion, which distills kinematic prototypes and intra-class dispersion from generative motion sequences and employs a learned gating network to adaptively inject reliable structural cues into textual embeddings.