Papers
2
Total Citations
4
H-Index
1
About
Fulong Ma is a rising researcher at the forefront of robotic perception and 3D computer vision, with a sharp focus on solving real-world challenges in sensor fusion and geometric deep learning. His primary research areas span self-supervised depth estimation, fisheye camera geometry, and novel attitude estimation frameworks for autonomous systems. Ma’s most impactful contribution is the development of **FisheyeDepth**, a pioneering self-supervised model that achieves real-scale depth estimation directly from fisheye imagery—a notoriously difficult task due to severe image distortions and the scarcity of ground-truth data. By leveraging the wide field-of-view inherent to fisheye cameras, this work addresses a critical bottleneck in 3D scene comprehension for robotics and autonomous vehicles. In parallel, Ma has made a notable theoretical contribution to **biquaternion algebra**, discovering a novel evolution of complex quaternions for attitude estimation using single-vector sensor measurements (e.g., accelerometers and magnetometers). This work offers a fresh mathematical framework for robust orientation tracking in resource-constrained robotic platforms. With his papers already garnering citations and addressing fundamental gaps in perception, Fulong Ma is establishing himself as a creative and technically rigorous voice in the next generation of robotics researchers.
Research Focus
Key Achievements
Top Papers
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- 2