Jiafeng Cui — accepted AI-conference papers

2023

CCL: Continual Contrastive Learning for LiDAR Place Recognition

RA-L 2023

Place recognition is an essential and challenging task in loop closing and global localization for robotics and autonomous driving applications. Benefiting from the recent advances in deep learning techniques, the performance of LiDAR place recognition (LPR) has been greatly improved. However, curre

Cited by 17 Source ↗code ↗Scholar ↗

2022

LIO-Vehicle: A Tightly-Coupled Vehicle Dynamics Extension of LiDAR Inertial Odometry

Hongru Xiao, Yanqun Han, Junqiao Zhao, Jiafeng Cui, Lu Xiong, Zhuoping Yu

RA-L 2022

We propose LIO-Vehicle, a new tightly-coupled vehicle dynamics extension of LiDAR inertial odometry (LIO) method that provides highly accurate, robust, and real-time vehicle trajectory estimation. Since most existing LiDAR-based localization methods are not specifically proposed for vehicles, they d

Cited by 20 Source ↗Scholar ↗