Weixun Zuo
Papers
1
Total Citations
14
H-Index
1
About
Weixun Zuo is a researcher advancing the field of 3D data compression and autonomous driving perception. His primary research areas include point cloud processing, coding schemes, and large-scale spatial data management. Zuo’s most notable contribution is a novel compression scheme for large-scale point cloud sequences, inspired by the high-efficiency video coding (HEVC) framework. This work addresses the critical challenge of storing and transmitting massive point cloud data—a bottleneck in autonomous driving systems—by integrating clustering and registration techniques to achieve efficient, high-fidelity compression. With 14 citations, this paper has already gained recognition for tackling a pressing industry problem. Zuo’s research is pivotal for enabling scalable, real-time processing of LiDAR and 3D sensor data, directly impacting the development of safer and more efficient autonomous vehicles. His work stands out for its practical approach to reducing data volume without compromising quality, making him a key contributor to the intersection of computer vision, data compression, and intelligent transportation systems.
Research Focus
Key Achievements
Top Papers
- 1