33 citations · 33 across the 4 of their papers we have counts for
4 papers
De-biasing Skeleton-based Action Recognition with Convex Hull Adaptive Shift
Mengyuan Liu, Yuhang Wen, Yi Zhang +4
Skeleton sequences can represent both individual actions and multi-entity interactions, encompassing human bodies, hands, objects, and robots. Existing approaches to recognize skel…
STAR: Skeletal Token Alignment and Rearrangement for Interaction Recognition
Yuhang Wen, Mengyuan Liu, Zixuan Tang +3
Understanding physical human-robot and human-human interactions is a challenging yet emerging topic in 3D vision. While most existing methods rely on skeleton sequences--effective…
CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition
Yuhang Wen, Mengyuan Liu, Songtao Wu +1
Skeleton-based multi-entity action recognition is a challenging task aiming to identify interactive actions or group activities involving multiple diverse entities. Existing models…
Interactive Spatiotemporal Token Attention Network for Skeleton-based General Interactive Action Recognition
Yuhang Wen, Zixuan Tang, Yunsheng Pang +2
Recognizing interactive action plays an important role in human-robot interaction and collaboration. Previous methods use late fusion and co-attention mechanism to capture interact…