Xuebin Sun
Papers
2
Total Citations
45
H-Index
2
About
Dr. Xuebin Sun is a leading researcher in autonomous vehicle perception and 3D data compression, whose work directly addresses critical bandwidth and storage bottlenecks in self-driving technology. His primary research focuses on LiDAR point cloud processing, efficient coding frameworks, and scene-aware data transmission for autonomous systems. Dr. Sun’s most impactful contribution is the development of a task-driven, scene-aware LiDAR point cloud coding framework (2022, 31 citations), which intelligently prioritizes data transmission based on driving context, significantly reducing bandwidth demands for unstable networks. He also pioneered a novel compression scheme for large-scale point cloud sequences (2021, 14 citations), adapting HEVC principles through clustering and registration techniques to dramatically lower storage and transmission costs. With a combined citation count exceeding 45 for these foundational works, Dr. Sun’s innovations are shaping the next generation of efficient, real-time perception systems. His research is particularly notable for bridging the gap between high-fidelity environmental sensing and practical communication constraints, making autonomous driving more viable in bandwidth-limited scenarios.
Research Focus
Key Achievements
Top Papers
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- 2