A Concise but High-performing Network for Image Guided Depth Completion in Autonomous Driving

arXiv:2401.15902v2 Announce Type: replace
Abstract: Depth completion is a crucial task in autonomous driving, aiming to convert a sparse depth map into a dense depth prediction. Due to its potentially rich semantic information, RGB image is commonly fused to enhance the completion effect. Image-guided depth completion involves three key challenges: 1) how to effectively fuse the two modalities; 2) how to better recover depth information; and 3) how to achieve real-time prediction for practical autonomous driving. To solve the above …

arxiv autonomous autonomous driving cs.cv driving image network type