Efficient relocalization is essential for intelligent vehicles when GPS reception is insufficient
or sensor-based localization fails. Recent advances in Bird's-Eye-View (BEV) segmentation …

We present a novel framework for global localization and guided relocalization of a vehicle
in an unstructured environment. Compared to existing methods, our pipeline does not rely …

Accurate and reliable ego-localization is critical for autonomous driving. In this paper, we
present EgoVM, an end-to-end localization network that achieves comparable localization …

This paper proposes a novel framework for real-time localization and egomotion tracking of
a vehicle in a reference map. The core idea is to map the semantic objects observed by the …

In the process of urban environment mapping, the sequential accumulations of dynamic
objects will leave a large number of traces in the map. These traces will usually have bad …

Localization using a monocular camera in the pre-built LiDAR point cloud map has drawn
increasing attention in the field of autonomous driving and mobile robotics. However, there …

This thesis presents a novel framework for global localization and guided relocalization of a
vehicle in an unstructured environment. Compared to existing methods, this pipeline does …

The semantic map plays an essential role in unmanned tasks with limited resources for
urban road scenes, especially for precise localization in the GNSS-blocked area. With the …

Relocalization is the basis of map-based localization algorithms. Camera and LiDAR map-
based methods are pervasive since their robustness under different scenarios. Generally …