The 1st-place Solution for CVPR 2023 OpenLane Topology in Autonomous Driving Challenge
Autor: | Wu, Dongming, Jia, Fan, Chang, Jiahao, Li, Zhuoling, Sun, Jianjian, Han, Chunrui, Li, Shuailin, Liu, Yingfei, Ge, Zheng, Wang, Tiancai |
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Rok vydání: | 2023 |
Předmět: | |
Druh dokumentu: | Working Paper |
Popis: | 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. Comment: Accepted by CVPR2023 Workshop (https://opendrivelab.com/AD23Challenge.html#openlane_topology) |
Databáze: | arXiv |
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