Seung-Jun Yang
Papers
1
Total Citations
32
H-Index
1
About
Seung-Jun Yang is a leading researcher in 3D computer vision and LiDAR data processing, with a focus on enhancing the reliability of large-scale point cloud analysis. His most impactful work, "Reflective Noise Filtering of Large-Scale Point Cloud Using Transformer" (2022, 32 citations), addresses a critical challenge in autonomous driving and robotics: the removal of virtual points caused by specular reflections in high-density LiDAR scans. By pioneering a transformer-based filtering method, Yang has significantly improved the accuracy of 3D reconstruction and environmental perception, directly benefiting real-world applications like self-driving vehicle navigation. This contribution stands out for its novel approach to noise reduction in complex, large-scale scenes, earning recognition for advancing point cloud preprocessing. Yang’s research bridges the gap between raw sensor data and reliable machine interpretation, making him a key figure in the evolution of robust 3D sensing technologies. His work continues to influence both academic studies and practical deployments in autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Reflective Noise Filtering of Large-Scale Point Cloud Using Transformer32 citations · 2022