This paper presents EdgeLoc, an infrastructure-assisted, real-time localization system for
autonomous driving that addresses the incompatibility between traditional localization …

We present a visual localization framework based on novel deep attention aware features
for autonomous driving that achieves centimeter level localization accuracy. Conventional …

Accurate localization is a foundational capacity, required for autonomous vehicles to
accomplish other tasks such as navigation or path planning. It is a common practice for …

Recent deep learning frameworks draw strong research interest in application of ego-motion
estimation as they demonstrate a superior result compared to geometric approaches …

Over the last few years, we have witnessed tremendous progress on many subtasks of
autonomous driving including perception, motion forecasting, and motion planning …

In this paper we investigate the impact of federated learning on deep learning-based feature
extraction used for self-localization in autonomous vehicles. The accurate and reliable …

High-accurate localization is crucial for the safety and reliability of autonomous driving,
especially for the information fusion of collective perception that aims to further improve road …

An accurate and robust localization system is crucial for autonomous vehicles (AVs) to
enable safe driving in urban scenes. While existing global navigation satellite system …

Vehicle localization is essential for autonomous vehicle (AV) navigation and Advanced
Driver Assistance Systems (ADAS). Accurate vehicle localization is often achieved via …

Accurate ego-centric localization assumes a paramount significance in the domain of
autonomous driving. However, traditional methods for camera-LiDAR map localization rely …