BEVCar: Camera-Radar Fusion for BEV Map and Object Segmentation

arXiv:2403.11761v1 Announce Type: cross
Abstract: Semantic scene segmentation from a bird's-eye-view (BEV) perspective plays a crucial role in facilitating planning and decision-making for mobile robots. Although recent vision-only methods have demonstrated notable advancements in performance, they often struggle under adverse illumination conditions such as rain or nighttime. While active sensors offer a solution to this challenge, the prohibitively high cost of LiDARs remains a limiting factor. Fusing camera data with automotive radars poses a more inexpensive alternative but has received …

arxiv cs.cv cs.ro fusion map object radar segmentation type