Tootfinder

BEVCar: Camera-Radar Fusion for BEV Map and Object Segmentation
Jonas Schramm, Niclas V\"odisch, K\"ursat Petek, B Ravi Kiran, Senthil Yogamani, Wolfram Burgard, Abhinav Valada
https://arxiv.org/abs/2403.11761

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

BEVCar: Camera-Radar Fusion for BEV Map and Object Segmentation
Jonas Schramm, Niclas V\"odisch, K\"ursat Petek, B Ravi Kiran, Senthil Yogamani, Wolfram Burgard, Abhinav Valada
https://arxiv.org/abs/2403.11761

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