We present the 1st-place solution of OpenLane Topology in Autonomous Driving Challenge. Considering that topology reasoning is based on centerline detection and traffic element detection, we develop a multi-stage framework for high performance. Specifically, the centerline is detected by the powerful PETRv2 detector and the popular YOLOv8 is employed to detect the traffic elements. Further, we design a simple yet effective MLP-based head for topology prediction. Our method achieves 55\% OLS on the OpenLaneV2 test set, surpassing the 2nd solution by 8 points.
@article{arxiv.2306.09590,
title = {The 1st-place Solution for CVPR 2023 OpenLane Topology in Autonomous Driving Challenge},
author = {Dongming Wu and Fan Jia and Jiahao Chang and Zhuoling Li and Jianjian Sun and Chunrui Han and Shuailin Li and Yingfei Liu and Zheng Ge and Tiancai Wang},
journal= {arXiv preprint arXiv:2306.09590},
year = {2023}
}
Comments
Accepted by CVPR2023 Workshop (https://opendrivelab.com/AD23Challenge.html#openlane_topology)