Yan Xia

Technical University of Munich

Papers

1

Total Citations

19

H-Index

1

About

Yan Xia is an emerging researcher making significant strides in the field of 3D computer vision and point cloud processing. His work centers on the challenging problem of point set registration — the process of aligning three-dimensional data captured from real-world environments — with particular emphasis on developing fast, deterministic algorithms that leverage physical priors to improve accuracy and efficiency. His most notable contribution, the 2023 paper "Fast and Deterministic (3+1)DOF Point Set Registration with Gravity Prior," has already garnered 19 citations within a short period, a testament to the immediate relevance and practicality of his approach. By incorporating gravitational constraints into the registration pipeline, Xia's method reduces the complexity of the alignment problem while maintaining robustness, offering meaningful advantages for applications in robotics, autonomous driving, and LiDAR-based mapping. This work stands out for its combination of theoretical rigor and real-world applicability, addressing longstanding computational bottlenecks in the field. As a researcher, Xia represents a promising voice in the 3D perception community, with early work that already demonstrates both technical depth and practical impact.

Research Focus

Key Achievements

1
H-Index
1
Papers
19
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
Fast and deterministic (3+1)DOF point set registration with gravity prior
19 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Technical University of Munich

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago