Papers
3
Total Citations
163
H-Index
3
About
Haiyang Mei is a pioneering researcher in computer vision, with a primary focus on the challenging task of glass detection in real-world scenes. His work addresses a critical blind spot in existing vision systems, which often fail to perceive transparent surfaces, leading to potential hazards for autonomous robots and other intelligent agents. Mei’s foundational paper, “Don’t Hit Me! Glass Detection in Real-World Scenes” (2020), has garnered 131 citations, establishing a new benchmark in the field. He further advanced this area with “Large-Field Contextual Feature Learning for Glass Detection” (2022, 20 citations), introducing innovative methods to capture the complex contextual cues essential for identifying glass. Beyond computer vision, Mei has also contributed to materials science, exploring variable-angle trajectory structures in CF/PEEK laminates made by robotic fiber placement (2022, 12 citations), demonstrating his interdisciplinary versatility. His work not only pushes the boundaries of perception but also has practical implications for robotics and autonomous navigation, making him a notable figure in both applied and theoretical research.
Research Focus
Key Achievements
Top Papers
- 1Don’t Hit Me! Glass Detection in Real-World Scenes131 citations · 2020
- 2Large-Field Contextual Feature Learning for Glass Detection20 citations · 2022
- 3