Zhanbo Xu
Papers
1
Total Citations
4
H-Index
1
About
Zhanbo Xu is a rising researcher in computer vision and intelligent systems, with a primary focus on pedestrian trajectory prediction for human-centric applications such as autonomous vehicles, intelligent surveillance, and social robotics. His most-cited work introduces a novel **Hierarchical Multi-Supervision Multi-Interaction Graph Attention Network**, which advances the field by addressing the limitations of single-camera trajectory prediction (SCTP) and enabling robust multi-camera pedestrian forecasting. This contribution is particularly significant for real-world deployments where multiple sensors must collaborate to anticipate human motion in complex environments. Xu’s research integrates graph neural networks with multi-level supervision, improving both prediction accuracy and interaction modeling among pedestrians. With 4 citations on this key paper, his work is gaining traction as a foundational approach for next-generation autonomous systems. By tackling the underexplored challenge of multi-camera coordination, Xu is helping to bridge the gap between controlled laboratory settings and dynamic, real-world applications, making his contributions highly relevant for students and researchers working at the intersection of AI, robotics, and safety-critical systems.
Research Focus
Key Achievements
Top Papers
- 1