Neural Underwater Scene Representation

Yunkai Tang; Chengxuan Zhu; Renjie Wan; Chao Xu; Boxin Shi

CVPR 2024poster11 citations

Neural Underwater Scene Representation

Yunkai Tang, Chengxuan Zhu, Renjie Wan, Chao Xu, Boxin Shi

Abstract

Among the numerous efforts towards digitally recovering the physical world Neural Radiance Fields (NeRFs) have proved effective in most cases. However underwater scene introduces unique challenges due to the absorbing water medium the local change in lighting and the dynamic contents in the scene. We aim at developing a neural underwater scene representation for these challenges modeling the complex process of attenuation unstable in-scattering and moving objects during light transport. The proposed method can reconstruct the scenes from both established datasets and in-the-wild videos with outstanding fidelity.

BibTeX

@inproceedings{cvpr2024_neuralunderwater,
  title = {Neural Underwater Scene Representation},
  author = {Yunkai Tang and Chengxuan Zhu and Renjie Wan and Chao Xu and Boxin Shi},
  booktitle = {CVPR 2024},
  year = {2024}
}