FENet: Focusing Enhanced Network for Lane Detection. (arXiv:2312.17163v4 [cs.CV] UPDATED)

Inspired by human driving focus, this research pioneers networks augmented
with Focusing Sampling, Partial Field of View Evaluation, Enhanced FPN
architecture and Directional IoU Loss - targeted innovations addressing
obstacles to precise lane detection for autonomous driving. Experiments
demonstrate our Focusing Sampling strategy, emphasizing vital distant details
unlike uniform approaches, significantly boosts both benchmark and practical
curved/distant lane recognition accuracy essential for safety. While FENetV1
achieves state-of-the-art conventional metric performance via enhancements
isolating perspective-aware contexts mimicking driver vision, FENetV2 proves …

architecture arxiv autonomous autonomous driving cs.cv detection driving evaluation focus human innovations iou lane detection loss network networks obstacles research sampling strategy uniform view vital