Underwater Light Field Retention : Neural Rendering for Underwater Imaging

@article{Ye2022UnderwaterLF,
  title={Underwater Light Field Retention : Neural Rendering for Underwater Imaging},
  author={Tian Ye and Sixiang Chen and Yunzhuo Liu and Erkang Chen and Yi Ye and Yuche Li},
  journal={2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2022},
  pages={487-496}
}
  • Tian YeSixiang Chen Yuche Li
  • Published 21 March 2022
  • Computer Science
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Underwater Image Rendering aims to generate a true-to-life underwater image from a given clean one, which could be applied to various practical applications such as underwater image enhancement, camera filter, and virtual gaming. We explore two less-touched but challenging problems in underwater image rendering, namely, i) how to render diverse underwater scenes by a single neural network? ii) how to adaptively learn the underwater light fields from natural exemplars, i,e., realistic underwater… 

WaterNeRF: Neural Radiance Fields for Underwater Scenes

—Underwater imaging is a critical task performed by marine robots for a wide range of applications including aquaculture, marine infrastructure inspection, and environ- mental monitoring. However,

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