Relative Illumination Fields: Learning Medium and Light Independent Underwater Scenes

We address the challenge of constructing a consistent and photorealistic Neural Radiance Field in inhomogeneously illuminated, scattering environments with unknown, co-moving light sources. While most existing works on underwater scene representation focus on a static homogeneous illumination, limited attention has been paid to scenarios such as when a robot explores water deeper than a few tens of meters, where sunlight becomes insufficient. To address this, we propose a novel illumination field locally attached to the camera, enabling the capture of uneven lighting effects within the viewing frustum. We combine this with a volumetric medium representation to an overall method that effectively handles interaction between dynamic illumination field and static scattering medium. Evaluation results demonstrate the effectiveness and flexibility of our approach.

@article{she2025_2504.10024,
  title={ Relative Illumination Fields: Learning Medium and Light Independent Underwater Scenes },
  author={ Mengkun She and Felix Seegräber and David Nakath and Patricia Schöntag and Kevin Köser },
  journal={arXiv preprint arXiv:2504.10024},
  year={ 2025 }
}