3 papers
cs.CV2025
S-BEVLoc: BEV-based Self-supervised Framework for Large-scale LiDAR Global Localization
Chenghao Zhang, Lun Luo, Si-Yuan Cao +6
LiDAR-based global localization is an essential component of simultaneous localization and mapping (SLAM), which helps loop closure and re-localization. Current approaches rely on…
cs.RO2025
BEVPlace++: Fast, Robust, and Lightweight LiDAR Global Localization for Unmanned Ground Vehicles
Lun Luo, Si-Yuan Cao, Xiaorui Li +4
This article introduces BEVPlace++, a novel, fast, and robust LiDAR global localization method for unmanned ground vehicles. It uses lightweight convolutional neural networks (CNNs…
cs.GR2025
VoxDet: Rethinking 3D Semantic Occupancy Prediction as Dense Object Detection
Wuyang Li, Zhu Yu, Alexandre Alahi
3D semantic occupancy prediction aims to reconstruct the 3D geometry and semantics of the surrounding environment. With dense voxel labels, prior works typically formulate it as a…