3D Lane Detection

3D lane detection aims to accurately identify and represent lane markings in three-dimensional space, crucial for autonomous driving and high-definition map creation. Current research heavily utilizes deep learning, focusing on end-to-end models that leverage both image and LiDAR data, often employing transformer architectures and Bézier curve representations to capture lane geometry. These advancements improve accuracy and robustness compared to previous methods, particularly in challenging conditions, leading to safer and more efficient autonomous navigation systems.