Relative Illumination Fields: Learning Medium and Light Independent Underwater Scenes

• URL: http://arxiv.org/abs/2504.10024v1
• Date: Mon, 14 Apr 2025 09:28:04 GMT
• Title: Relative Illumination Fields: Learning Medium and Light Independent Underwater Scenes
• Authors: Mengkun She, Felix Seegräber, David Nakath, Patricia Schöntag, Kevin Köser,
• Abstract summary: We address the challenge of constructing a consistent and photorealistic Neural Radiance Field in inhomogeneously illuminated, scattering environments.<n>We propose a novel illumination field locally attached to the camera, enabling the capture of uneven lighting effects within the viewing frustum.<n>We combine this with a volumetric medium representation to an overall method that effectively handles interaction between dynamic illumination field and static scattering medium.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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