Papers

2

Total Citations

49

H-Index

2

About

Yaxu Xie is a researcher pushing the boundaries of autonomous navigation and 3D spatial understanding, with a focus on challenging, unstructured environments. His key research areas include visual SLAM (Simultaneous Localization and Mapping), 3D scene graph alignment, and multi-view stereo reconstruction. Xie’s most cited work, “SLAM in the Field” (2021, 44 citations), makes a major contribution by demonstrating a robust monocular SLAM system that integrates sparse, indirect visual SLAM with both offline and real-time Multi-View Stereo algorithms. This combination successfully overcomes critical obstacles for autonomous vehicles and robots operating in dynamic agricultural settings, where traditional methods often fail. More recently, Xie introduced SG-PGM (2024), a novel partial graph matching network that fuses semantic and geometric features for 3D scene graph alignment. This work is foundational for downstream tasks like point cloud registration, mosaicking, and robot navigation, offering a comprehensive representation of 3D scenes. Through these contributions, Xie is advancing the reliability and intelligence of autonomous systems in complex, real-world environments.

Research Focus

Key Achievements

2
H-Index
2
Papers
49
Total Citations
25
Avg Citations/Paper
🏆 Most Cited Paper
SLAM in the Field: An Evaluation of Monocular Mapping and Localization on Challenging Dynamic Agricultural Environment
44 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: German Research Centre for Artificial Intelligence

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago