Jan. 31, 2024, 3:43 p.m. | Runkai Zhao Yuwen Heng Yuanda Gao Shilei Liu Heng Wang Changhao Yao Jiawen Chen Weidong Cai

cs.CV updates on arXiv.org arxiv.org

Advanced Driver-Assistance Systems (ADAS) have successfully integrated learning-based techniques into vehicle perception and decision-making. However, their application in 3D lane detection for effective driving environment perception is hindered by the lack of comprehensive LiDAR datasets. The sparse nature of LiDAR point cloud data prevents an efficient manual annotation process. To solve this problem, we present LiSV-3DLane, a large-scale 3D lane dataset that comprises 20k frames of surround-view LiDAR point clouds with enriched semantic annotation. Unlike existing datasets confined to a …

adas advanced application cloud cloud data collection cs.cv data data collection datasets decision detection development driver driving environment lane detection lidar making model development nature perception systems

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