Hanyu Shi
Papers
1
Total Citations
108
H-Index
1
About
Hanyu Shi is a leading researcher in 3D and 4D computer vision, with a focus on point cloud understanding for autonomous driving and robotics. His most-cited work, "SpSequenceNet: Semantic Segmentation Network on 4D Point Clouds" (2020, 108 citations), pioneers the challenging task of semantic segmentation on 4D point clouds—sequences of consecutive 3D frames. This contribution is critical for enabling machines to perceive dynamic environments over time, moving beyond static 3D analysis. Shi’s research addresses the core problem of capturing spatiotemporal features from irregular, unordered point cloud sequences, offering novel architectures that improve both accuracy and efficiency. His work has been widely recognized for advancing scene understanding in real-world applications, where temporal consistency is key. With over 100 citations on his flagship paper, Shi’s impact is evident in the growing adoption of 4D point cloud methods in autonomous systems. His achievements position him as a rising authority in spatial-temporal deep learning, bridging the gap between static perception and dynamic, real-time reasoning.
Research Focus
Key Achievements
Top Papers
- 1SpSequenceNet: Semantic Segmentation Network on 4D Point Clouds108 citations · 2020