Advancements in 3D Lane Detection Using LiDAR Point Clouds: From Data Collection to Model Development. (arXiv:2309.13596v2 [cs.CV] UPDATED)

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