文献类型：会议论文

英文题名：Improvement of panoptic segmentation method for urban road

作者：Ye, Zhao[1]; Dai, Songyin[1]; Li, Xuewei[1]; Xu, Cheng[1]

机构：[1] Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing, China

第一机构：北京联合大学北京市信息服务工程重点实验室

会议论文集：ICCDE 2022 - 8th International Conference on Computing and Data Engineering

会议日期：January 11, 2022 - January 13, 2022

会议地点：Virtual, Online, Thailand

语种：英文

外文关键词：intelligent driving; panoptic segmentation; recursive feature pyramid network; upsnet

摘要：When learning and studying the panoptic segmentation method upsnet, in order to better apply it in the intelligent driving scene, the following improvements are made to the algorithm: 1. Aiming at the problem that the scale difference of different types of targets in the traffic scene is too large, the feature extraction network of the network is improved, and the upsnet panoptic segmentation network combined with recursive feature pyramid is proposed. 2. Aiming at the occlusion problem between different categories in panoptic segmentation task, an occlusion processing model is added to upsnet to solve the occlusion problem. The improved algorithm is compared with upsnet and other excellent panoptic segmentation networks on cityscapes data set and the panoptic segmentation data set labeled in this paper. The experimental results show that the evaluation index PQ (panoptic quality) has been greatly improved, and the improved network is more suitable for intelligent driving scenes. ? 2022 ACM.