June 11, 2024, 4:50 a.m. | Jun Yu, Yunxiang Zhang, Fengzhao Sun, Leilei Wang, Renjie Lu

cs.CV updates on arXiv.org arxiv.org

arXiv:2406.05837v1 Announce Type: new
Abstract: In this report, we present our solution for the semantic segmentation in adverse weather, in UG2+ Challenge at CVPR 2024. To achieve robust and accurate segmentation results across various weather conditions, we initialize the InternImage-H backbone with pre-trained weights from the large-scale joint dataset and enhance it with the state-of-the-art Upernet segmentation method. Specifically, we utilize offline and online data augmentation approaches to extend the train set, which helps us to further improve the performance …

abstract arxiv challenge cs.ai cs.cv cvpr report results robust scale segmentation semantic solution type weather

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