Qingyong Hu
Papers
3
Total Citations
2,284
H-Index
3
About
Qingyong Hu is a leading researcher in 3D computer vision, with a primary focus on deep learning for point cloud analysis. His most significant contribution is the comprehensive survey "Deep Learning for 3D Point Clouds: A Survey" (2020), which has amassed over 2,200 citations, establishing itself as a foundational reference in the field. This work systematically reviews deep learning techniques for processing 3D point clouds, addressing challenges in autonomous driving, robotics, and computer vision. Hu's research also advances panoptic segmentation of 3D point clouds in outdoor scenes, as demonstrated in his 2024 work using Gaussian mixture models to improve instance differentiation. His contributions are critical for enabling accurate scene understanding in autonomous systems. With a citation count exceeding 2,200, Hu's work has profoundly influenced the trajectory of 3D deep learning, providing essential frameworks for both academic research and real-world applications.
Research Focus
Key Achievements
Top Papers
- 1Deep Learning for 3D Point Clouds: A Survey2,225 citations · 2020
- 2Deep Learning for 3D Point Clouds: A Survey48 citations · 2019
- 3