Multi Lane Detection
This addresses lane detection for autonomous driving systems, but appears incremental as it builds on existing methods like CNNs and Affinity Fields.
The paper tackles robust lane detection for autonomous driving without assuming the number of lanes, achieving results with a CNN backbone and Affinity Fields, but no concrete performance numbers are provided.
Lane detection is a long-standing task and a basic module in autonomous driving. The task is to detect the lane of the current driving road, and provide relevant information such as the ID, direction, curvature, width, length, with visualization. Our work is based on CNN backbone DLA-34, along with Affinity Fields, aims to achieve robust detection of various lanes without assuming the number of lanes. Besides, we investigate novel decoding methods to achieve more efficient lane detection algorithm.