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Osmosis: RGBD Diffusion Prior for Underwater Image Restoration
March 25, 2024, 4:44 a.m. | Opher Bar Nathan, Deborah Levy, Tali Treibitz, Dan Rosenbaum
cs.CV updates on arXiv.org arxiv.org
Abstract: Underwater image restoration is a challenging task because of strong water effects that increase dramatically with distance. This is worsened by lack of ground truth data of clean scenes without water. Diffusion priors have emerged as strong image restoration priors. However, they are often trained with a dataset of the desired restored output, which is not available in our case. To overcome this critical issue, we show how to leverage in-air images to train diffusion …
abstract arxiv cs.cv data diffusion effects however image image restoration prior truth type underwater water
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