3D Localization in Urban Environments (Xia, USTC)

Abstract

Localization is a critical capability for self-driving vehicles, allowing them to pinpoint their location on a map. The well-known technique for localization is to use global navigation satellite system (GNSS). However, the signals of satellites are bound to fail among tall buildings and vegetation. As a result, sensor-based solutions can be decisive in improving the localization. In this talk, I will introduce a series of our 3D localization methods, aiming to enhance localization accuracy and generalizability in GNSS-denied urban environments. These include studies on point cloud-based place recognition and cross-model localization methods.

Prof. Yan Xia is an Associate Professor at the University of Science and Technology of China (USTC). He was a senior researcher in the Chair of Computer Vision & Artificial Intelligence at Technical University of Munich (TUM) working with Prof. Daniel Cremers. He obtained his PhD degree from TUM in 2023 and was a visiting scholar in the Visual Geometry Group (VGG) at the University of Oxford. His research interests include 3D vision, robotics, and autonomous driving. He has published near 40 academic papers at top-tier conferences and journals such as CVPR, ICCV and ECCV. He received the Best Paper Award at the ISPRS Geospatial Week 2023 and ICCV 2025 Workshop E2E3D.

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