Through the Water: Refractive Gaussian Splatting for Water Surface Scenes

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Authors: Association for Artificial Intelligence 2026, 영훈 윤, 호준 정, Jongwon Choi, Taegwan Kim, Gyuhyun Kim, Jaeyoon Lee
Cited by: 0

Abstract

Scenes with water surfaces present a significant challenge for Gaussian Splatting due to the simultaneous presence of refraction and reflection, as well as the difficulty of accurately estimating the geometry of transparent water surfaces. To address this, we propose a novel framework for reconstructing scenes involving both reflection and refraction caused by water surfaces. The water surface is modeled as a trainable plane, and 2D Gaussian ray tracing is applied to account for refraction through the water. We extend 2D Gaussian Splatting by introducing a soft mask parameter and a dual set of Gaussian primitives, which handle both reflected and refracted effects. Our method achieves state-of-the-art performance on newly constructed water surface datasets, including both synthetic and real scenes, and significantly outperforms prior approaches in water-interacting regions. Furthermore, we demonstrate the editability of our model by manipulating the index of refraction to suppress or modify refractive effects, enabling scene transformations into different liquids.

Fields of Study & Subjects

3D Shape Modeling and Analysis Computer Graphics and Visualization Techniques Advanced Vision and Imaging

Publication details

Journal / source
Underline Science Inc.
Publication date
7 January 2026
Language
EN