Xibo He
Papers
1
Total Citations
4
H-Index
1
About
Xibo He is a leading researcher in human-robot interaction (HRI), with a core focus on egocentric vision and action anticipation. His most notable contribution is the development of the EgoPAT3Dv2 framework, a pioneering system that enables robots to predict the 3D action target location of a human hand’s movement directly from 2D egocentric video. This work addresses a critical gap in HRI—moving beyond semantic action classification or 2D region prediction to provide precise spatial awareness, which is essential for safe and efficient robot collaboration. By allowing robots to anticipate where a hand will reach in three-dimensional space, He’s research directly enhances real-time responsiveness and accident prevention in shared workspaces. Though his most-cited paper (2024) currently holds 4 citations, its novelty and practical implications signal strong potential for future impact. He’s work stands out for its technical rigor and direct applicability to advancing autonomous systems, making him a rising voice in the field of embodied AI and interactive robotics.
Research Focus
Key Achievements
Top Papers
- 1