Lixin Fan
Papers
2
Total Citations
90
H-Index
2
About
Lixin Fan is a leading researcher in 3D computer vision and urban scene understanding, with a focus on autonomous systems and augmented reality. His work bridges the gap between raw sensor data and actionable spatial intelligence, particularly through the integration of street-view imagery and LiDAR point clouds. His most-cited paper, "Urban 3D segmentation and modelling from street view images and LiDAR point clouds" (2017, 62 citations), tackles the critical challenge of generating semantically labeled, metric-accurate 3D urban maps—a foundational technology for autonomous vehicles, city drones, and mobile AR applications. Fan further advanced the field with his coarse-to-fine registration algorithm for cross-source point clouds (2016, 28 citations), addressing the complex variations that arise when fusing data from different sensors. This work is pivotal for robust object registration in real-world, multi-sensor environments. By enabling precise, automated 3D reconstruction of cities, Fan’s contributions directly support the next generation of intelligent navigation and spatial computing. His research continues to shape how machines perceive and interact with complex urban landscapes.
Research Focus
Key Achievements
Top Papers
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- 2