Boxiao Pan
Papers
1
Total Citations
5
H-Index
1
About
Boxiao Pan is an emerging researcher at the intersection of computer vision, egocentric perception, and human-centric AI systems. His work focuses on enabling machines to understand and anticipate human behavior within physical environments, with particular emphasis on safety-critical applications in augmented reality, virtual reality, and assistive robotics. His most notable contribution, **COPILOT** (2023), tackles the challenging problem of predicting and localizing human-environment collisions from egocentric video streams — a capability with profound implications for wearable technology and real-time collision avoidance systems. By approaching this problem from a multi-view egocentric perspective, Pan's research pushes the boundaries of what AI systems can infer about spatial awareness and physical risk from first-person observations. With early citation momentum building around his work, Pan represents a promising voice in the embodied AI and egocentric vision communities. His research sits at a timely convergence of computer vision and human safety, addressing problems that grow increasingly relevant as immersive and assistive technologies become mainstream in everyday life.
Research Focus
Key Achievements
Top Papers
- 1