Wuyang Zhou

Nanjing University of Posts and Telecommunications

Papers

Total Citations

H-Index

About

Wuyang Zhou is a rising researcher in computer vision and autonomous driving, with a focused expertise in 3D single object tracking (SOT) using LiDAR point cloud data. His work addresses a critical challenge in robotics and autonomous systems: accurately tracking objects in three-dimensional space from sparse sensor data. Zhou’s major contributions include pioneering the integration of transformer architectures into 3D point cloud tracking, as demonstrated in his paper "Accurate 3D Single Object Tracker in Point Clouds with Transformer" (2022). This work adapts the success of 2D transformer-based trackers to the 3D domain, introducing novel designs that improve tracking robustness. He further advanced the field with "Integrating Scaling Strategy and Central Guided Voting for 3D Point Cloud Object Tracking" (2024), which tackles the limitations of hierarchical feature structures in existing trackers. While his citation counts are still growing—reflecting the recency of his publications—his research is positioned at the forefront of a rapidly evolving area. Zhou’s work is particularly notable for addressing the non-linearities and structural challenges that have hindered previous PointNet++-based approaches, making his contributions valuable for students and researchers seeking to understand the next generation of 3D tracking algorithms.