A Transformer-based conditional generative model augments skeleton action datasets by synthesizing high-fidelity sequences, improving recognition accuracy in few-shot and full-data regimes on HumanAct12 and NTU-VIBE.
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Generative Data Augmentation for Skeleton Action Recognition
A Transformer-based conditional generative model augments skeleton action datasets by synthesizing high-fidelity sequences, improving recognition accuracy in few-shot and full-data regimes on HumanAct12 and NTU-VIBE.