Ultra Fast Structure-aware Deep Lane Detection

Understand

Modern methods mainly regard lane detection as a problem of pixel-wise segmentation, which is struggling to address the problem of challenging scenarios and speed.

• Inspired by human perception, the recognition of lanes under severe occlusion and extreme lighting conditions is mainly based on contextual and global information.
• Motivated by this observation, we propose a novel, simple, yet effective formulation aiming at extremely fast speed and challenging scenarios.
• Specifically, we treat the process of lane detection as a row-based selecting problem using global features.