1 citations · 1 across the 4 of their papers we have counts for
6 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…
Lens Privacy Sealing: A New Benchmark and Method for Physical Privacy-Preserving Action Recognition
Mengyuan Liu, Ziyi Wang, Peiming Li +1
RGB camera-based surveillance systems enable human action recognition for public safety and healthcare, yet raise serious privacy concerns. Existing methods rely on post-capture al…
Language-Guided Transformer Tokenizer for Human Motion Generation
Sheng Yan, Yong Wang, Xin Du +2
In this paper, we focus on motion discrete tokenization, which converts raw motion into compact discrete tokens--a process proven crucial for efficient motion generation. In this p…
UST-SSM: Unified Spatio-Temporal State Space Models for Point Cloud Video Modeling
Peiming Li, Ziyi Wang, Yulin Yuan +4
Point cloud videos capture dynamic 3D motion while reducing the effects of lighting and viewpoint variations, making them highly effective for recognizing subtle and continuous hum…
Recognizing Actions from Robotic View for Natural Human-Robot Interaction
Ziyi Wang, Peiming Li, Hong Liu +5
Natural Human-Robot Interaction (N-HRI) requires robots to recognize human actions at varying distances and states, regardless of whether the robot itself is in motion or stationar…
3D Skeleton-Based Action Recognition: A Review
Mengyuan Liu, Hong Liu, Qianshuo Hu +4
With the inherent advantages of skeleton representation, 3D skeleton-based action recognition has become a prominent topic in the field of computer vision. However, previous review…