RadarCam-Depth: Radar-Camera Fusion for Depth Estimation with Learned Metric Scale

arXiv:2401.04325v2 Announce Type: replace
Abstract: We present a novel approach for metric dense depth estimation based on the fusion of a single-view image and a sparse, noisy Radar point cloud. The direct fusion of heterogeneous Radar and image data, or their encodings, tends to yield dense depth maps with significant artifacts, blurred boundaries, and suboptimal accuracy. To circumvent this issue, we learn to augment versatile and robust monocular depth prediction with the dense metric scale induced from sparse and noisy …

arxiv cs.cv fusion radar scale type