Abstract: This study investigates unsupervised anomaly action recognition, which identifies video-level abnormal-human-behavior events in an unsupervised manner without abnormal samples, and ...

Abstract: Skeleton-based human action recognition has gained significant attention due to the increasing accessibility of skeleton data. In this work, we propose a method for skeleton-based action ...