Weibo Gao
Papers
1
Total Citations
4
H-Index
1
About
Weibo Gao is a leading researcher at the intersection of computer vision, robotics, and human-robot interaction (HRI). His work centers on enabling machines to perceive and anticipate human actions from egocentric perspectives, a critical capability for safe and intuitive collaboration between humans and robots. Gao’s major contribution is the development of the EgoPAT3Dv2 framework, which advances beyond traditional semantic action classification or 2D target prediction. Instead, his research tackles the challenging problem of predicting the precise 3D action target location of a hand’s movement directly from 2D egocentric video. This work, published in 2024, has already garnered 4 citations, signaling its immediate relevance to the robotics community. By bridging the gap between visual perception and spatial reasoning, Gao’s research directly addresses a fundamental bottleneck in HRI: the robot’s ability to anticipate where a human intends to act. His approach promises to enhance both safety and efficiency in shared workspaces, making him a notable emerging voice in the field of embodied AI and interactive robotics.
Research Focus
Key Achievements
Top Papers
- 1