March 29, 2024, 4:44 a.m. | Lingjun Zhao, Jingyu Song, Katherine A. Skinner

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.19104v1 Announce Type: new
Abstract: In the field of 3D object detection for autonomous driving, LiDAR-Camera (LC) fusion is the top-performing sensor configuration. Still, LiDAR is relatively high cost, which hinders adoption of this technology for consumer automobiles. Alternatively, camera and radar are commonly deployed on vehicles already on the road today, but performance of Camera-Radar (CR) fusion falls behind LC fusion. In this work, we propose Camera-Radar Knowledge Distillation (CRKD) to bridge the performance gap between LC and CR …

arxiv cs.cv cs.ro detection distillation knowledge object radar type

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