May 14, 2024, 4:47 a.m. | Zhanwen Liu, Yuhang Li, Yang Wang, Bolin Gao, Yisheng An, Xiangmo Zhao

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.01703v2 Announce Type: replace
Abstract: The environmental perception of autonomous vehicles in normal conditions have achieved considerable success in the past decade. However, various unfavourable conditions such as fog, low-light, and motion blur will degrade image quality and pose tremendous threats to the safety of autonomous driving. That is, when applied to degraded images, state-of-the-art visual models often suffer performance decline due to the feature content loss and artifact interference caused by statistical and structural properties disruption of captured images. …

arxiv boosting cs.cv feature prior recognition replace type unsupervised via visual world

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