Lichao Huang
Papers
2
Total Citations
132
H-Index
2
About
Lichao Huang is a leading researcher in computer vision and robotics, with a primary focus on monocular depth estimation and sensor fusion. His most impactful work, "Parse Geometry from a Line: Monocular Depth Estimation with Partial Laser Observation" (2017), has garnered 126 citations, addressing a critical challenge in robotics: how to infer 3D depth from platforms equipped only with a monocular camera and a fixed 2D laser range finder. Huang’s key contribution lies in developing methods that leverage sparse laser data to guide and enhance depth prediction from a single image, effectively bridging the gap between limited sensor hardware and the need for rich spatial understanding. This approach has significant implications for autonomous navigation and manipulation in resource-constrained robotic systems. By enabling depth perception without expensive 3D sensors, Huang’s work has made advanced robotic capabilities more accessible. His research continues to influence the design of cost-effective perception systems, demonstrating how partial geometric cues can be intelligently parsed to achieve robust, real-world performance.
Research Focus
Key Achievements
Top Papers
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