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UVEB: A Large-scale Benchmark and Baseline Towards Real-World Underwater Video Enhancement
April 24, 2024, 4:44 a.m. | Yaofeng Xie, Lingwei Kong, Kai Chen, Ziqiang Zheng, Xiao Yu, Zhibin Yu, Bing Zheng
cs.CV updates on arXiv.org arxiv.org
Abstract: Learning-based underwater image enhancement (UIE) methods have made great progress. However, the lack of large-scale and high-quality paired training samples has become the main bottleneck hindering the development of UIE. The inter-frame information in underwater videos can accelerate or optimize the UIE process. Thus, we constructed the first large-scale high-resolution underwater video enhancement benchmark (UVEB) to promote the development of underwater vision.It contains 1,308 pairs of video sequences and more than 453,000 high-resolution with 38\% …
abstract arxiv become benchmark cs.cv development however image information process progress quality samples scale training type underwater video videos world
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