Jiaye Lin
Papers
2
Total Citations
9
H-Index
1
About
Jiaye Lin is a rising researcher in robotics and 3D computer vision, whose work centers on advancing neural implicit representations for large-scale 3D mapping. His primary contributions lie in developing non-projective signed distance fields (SDFs) that overcome the limitations of traditional projective distance supervision, enabling more accurate and geometrically consistent dense mapping for autonomous robots. His landmark paper, “N³-Mapping: Normal Guided Neural Non-Projective Signed Distance Fields for Large-Scale 3D Mapping” (2024), has already garnered 8 citations, establishing a new paradigm for high-fidelity reconstruction in complex environments. Building on this, his most recent work, “UN³-Mapping: Uncertainty-Aware Neural Non-Projective Signed Distance Fields for 3D Mapping” (2025), integrates uncertainty estimation into the mapping pipeline, a critical step toward reliable and safe autonomous navigation. By addressing fundamental challenges in sensor noise and spatial ambiguity, Lin’s research directly impacts real-world applications from autonomous driving to robotic exploration. His innovative hybrid representations and focus on robustness mark him as a promising voice in the next generation of 3D mapping technologies.
Research Focus
Key Achievements
Top Papers
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- 2