Alan Li
Papers
1
Total Citations
12
H-Index
1
About
Alan Li is a rising researcher in computer vision and robotics, whose work focuses on advancing 6D object pose estimation—a critical capability for enabling robots to interact reliably with their surroundings. His most-cited paper, "Multi-View Keypoints for Reliable 6D Object Pose Estimation" (2023, 12 citations), tackles the notoriously difficult problem of bin-picking, where objects are often low-feature, reflective, and prone to self-occlusion. Li’s key contribution lies in developing a multi-view keypoint approach that improves pose estimation accuracy under these challenging conditions, directly addressing a bottleneck in industrial automation. Despite being early in his career, his work has already garnered attention for its practical relevance to robotics and manufacturing. Li’s research stands out for its focus on real-world robustness, offering a pathway to more reliable robotic manipulation in cluttered environments. As he continues to build on these foundations, his contributions are poised to influence both academic research and applied robotics, making him a promising voice in the field of 3D vision and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Multi-View Keypoints for Reliable 6D Object Pose Estimation12 citations · 2023