Papers
1
Total Citations
11
H-Index
1
About
Anlong Ming is a leading researcher in computer vision and robotics, with a particular focus on visual perception for autonomous systems. His work addresses critical challenges in environment understanding, especially in complex indoor settings. Ming’s most-cited paper, "Indoor Obstacle Discovery on Reflective Ground via Monocular Camera" (2023, 11 citations), introduces a novel approach to detecting obstacles on reflective surfaces—a notoriously difficult problem for standard vision algorithms. By leveraging monocular camera data, his method enables safer navigation for robots and assistive technologies in environments like warehouses or homes. This contribution is pivotal for advancing real-world deployment of autonomous systems, where robust perception under non-ideal conditions is essential. Ming’s research bridges the gap between theoretical computer vision and practical robotic applications, earning recognition for its ingenuity and impact. His work continues to inspire new directions in obstacle detection and scene understanding, making him a notable figure in the field.
Research Focus
Key Achievements
Top Papers
- 1Indoor Obstacle Discovery on Reflective Ground via Monocular Camera11 citations · 2023