{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/the-1st-place-solution-for-cvpr-2023-openlane","title":"The 1st-place Solution for CVPR 2023 OpenLane Topology in Autonomous Driving Challenge","arxiv_id":"2306.09590","date":"2023-06-16","proceeding":null,"authors":["Dongming Wu","Fan Jia","Jiahao Chang","Zhuoling Li","Jianjian Sun","Chunrui Han","Shuailin Li","Yingfei Liu","Zheng Ge","Tiancai Wang"],"abstract":"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.","url_abs":"https://arxiv.org/abs/2306.09590v1","url_pdf":"https://arxiv.org/pdf/2306.09590v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"the-1st-place-solution-for-cvpr-2023-openlane","repo_url":"https://github.com/wudongming97/topomlp","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"autonomous-driving","task_name":"Autonomous Driving"}],"methods":[{"method_slug":"yolov8","method_name":"YOLOv8"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2306.09590","atlas_url":"https://app.syntology.ai/?focus=2306.09590","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}