Papers
1
Total Citations
21
H-Index
1
About
Zhibo Rao is a leading researcher in computer vision, with a primary focus on stereo matching for autonomous driving, robotics, and 3D scene reconstruction. His most influential work, the "Multi-scale Cross-form Pyramid Network for Stereo Matching" (CFP-Net), introduced a novel deep learning architecture that significantly advanced disparity regression from rectified stereo image pairs. By designing a cross-form pyramid structure, Rao’s approach effectively captures multi-scale contextual information, improving accuracy and robustness in complex real-world environments. This seminal paper has garnered 21 citations, underscoring its impact on the field. Rao’s contributions are pivotal for enabling precise depth perception in autonomous systems, and his work continues to inspire further innovations in 3D vision and spatial understanding.
Research Focus
Key Achievements
Top Papers
- 1Multi-scale Cross-form Pyramid Network for Stereo Matching21 citations · 2019