Xian Zhong

Wuhan University of Technology, Peking University

Papers

Total Citations

H-Index

About

Xian Zhong is a leading researcher in computer vision and robotics, with key contributions in underwater 3D reconstruction and human behavior prediction. Their most notable work introduces a groundbreaking Cross-Grained Photometric Stereo Transformer for underwater surface normal reconstruction, enabling high-precision 3D data acquisition of textureless objects like seabeds and pipelines—a critical capability for modern ocean exploration and underwater robots. This 2024 paper has already garnered 23 citations, reflecting its immediate impact on the field. Zhong also advances autonomous systems through their work on Global Temporal Attention Optimization for Human Trajectory Prediction (2022, 6 citations), which leverages Transformer networks to model social behaviors for autonomous driving and social robots. By emphasizing the essential role of global trajectory information, this research enhances predictive accuracy in dynamic environments. Zhong’s work bridges fundamental computer vision techniques with real-world robotic applications, demonstrating a clear trajectory from theoretical innovation to practical deployment. Their research is essential reading for anyone interested in the intersection of deep learning, robotics, and environmental sensing.