2022/03/23 by Jun Xie, Jiacheng Han, Xie, Jun +9
Computer Science · Engineering · #Advanced Neural Network Applications #Autonomous Vehicle Technology and Safety #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Vehicle License Plate Recognition #cs.CV
paper · pdf · doi:10.48550/arxiv.2203.12301
arxiv created 2022/03/23 · openalex publication_date 2022/03/23 · arxiv updated 2022/03/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Recently, lane detection has made great progress in autonomous driving. RESA (REcurrent Feature-Shift Aggregator) is based on image segmentation. It presents a novel module to enrich lane feature after preliminary feature extraction with an ordinary CNN. For Tusimple dataset, there is not too complicated scene and lane has more prominent spatial features. On the basis of RESA, we introduce the method of position embedding to enhance the spatial features. The experimental results show that this method has achieved the best accuracy 96.93% on Tusimple dataset.