Ben Fei

Fudan University, Chinese University of Hong Kong

Papers

Total Citations

154

H-Index

About

Ben Fei is a researcher working at the forefront of 3D computer vision and scene representation, with a particular focus on point cloud processing, novel view synthesis, and autonomous systems. His most influential contribution to date is his comprehensive survey on 3D Gaussian Splatting (3DGS), which has rapidly accumulated 144 citations since its 2024 publication — a testament to the field's explosive growth and the community's appetite for rigorous synthesis of this emerging paradigm. By mapping the landscape of 3DGS across applications spanning robotics, urban modeling, and beyond, Fei has helped establish a critical reference point for researchers entering this space. His broader interest in self-supervised learning for 3D point clouds further reflects a commitment to reducing reliance on expensive labeled data, addressing a fundamental bottleneck in 3D understanding. More applied work, such as GeeNet — a robust and efficient architecture for ground elevation estimation in autonomous vehicles — demonstrates his ability to translate theoretical insights into practical systems. Across these contributions, Fei consistently bridges foundational representation learning with real-world deployment challenges, making his work valuable both to researchers advancing 3D vision theory and engineers building next-generation autonomous and intelligent systems.