Chengyang Cao

University of Science and Technology Beijing

Papers

Total Citations

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About

Chengyang Cao is a rising researcher in computer vision and robotics, whose work centers on advancing visual localization for autonomous systems. His primary research areas include camera pose estimation, lightweight mapping, and robust localization techniques for real-world applications like autonomous driving and augmented reality. Cao’s major contribution is the development of efficient, structured representations that replace traditional, heavy point cloud maps—such as those from Structure-from-Motion—with lighter, line-based maps. His most-cited paper, "Lightweight Structured Line Map Based Visual Localization" (2024), has already garnered 6 citations, demonstrating early impact in a field where speed and accuracy are critical. This work addresses a key bottleneck: enabling reliable localization without the computational burden of dense 3D models. By focusing on line features, Cao’s approach improves both memory efficiency and robustness in challenging environments. His research promises to make autonomous navigation more practical and scalable, marking him as a promising voice in the next generation of visual localization innovation.