About

Fuxun Liang is a leading researcher in 3D computer vision and autonomous navigation, with a focus on large-scale point cloud registration, LiDAR-inertial SLAM, and cross-modality data fusion. His work addresses critical challenges in enabling robots and autonomous vehicles to perceive and localize within complex environments. Liang’s most influential contribution is his comprehensive review and benchmark on the registration of large-scale terrestrial laser scanner point clouds, which has garnered over 410 citations and serves as a foundational resource for the field. He has also pioneered innovative methods such as CoFiI2P, a coarse-to-fine correspondence framework for image-to-point cloud registration that improves global alignment, and DALI-SLAM, a degeneracy-aware LiDAR-inertial SLAM system featuring novel distortion correction and multi-constraint pose graph optimization. Additionally, his PatchAugNet enhances heterogeneous point cloud place recognition in street scenes through patch feature augmentation. With over 460 total citations across his most-cited works, Liang’s research continues to push the boundaries of robust, real-time perception for autonomous systems.

Research Focus

Key Achievements

4
H-Index
4
Papers
463
Total Citations
116
Avg Citations/Paper
🏆 Most Cited Paper
Registration of large-scale terrestrial laser scanner point clouds: A review and benchmark
410 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago