CULane Dataset

CULane is a large scale challenging dataset for academic research on traffic lane detection. It is collected by cameras mounted on six different vehicles driven by different drivers in Beijing. More than 55 hours of videos were collected and 133,235 frames were extracted. Dataset is divided into 88880 for training set, 9675 for validation set, and 34680 for test set. The test set is divided into normal and 8 challenging categories.

For each frame, the traffic lanes with cubic splines are manually annotated. For cases where lane markings are occluded by vehicles or are unseen, lanes according to the context were annotated, as shown in (2)(4). The algorithms could distinguish barriers on the road, like the one in (1). Thus the lanes on the other side of the barrier are not annotated. In this dataset, the focus of attention is on the detection of four lane markings, which are paid most attention to in real applications. Other lane markings are not annotated. White paper - https://arxiv.org/abs/1712.06080