Representing underwater 3D scenes is a valuable yet complex task, as attenuation and scattering effects during underwater imaging significantly couple the information of the objects and the water. This coupling presents a significant challenge for existing methods in effectively representing both the objects and the water medium simultaneously. To address this challenge, we propose Aquatic-GS, a hybrid 3D representation approach for underwater scenes that effectively represents both the objects and the water medium. Specifically, we construct a Neural Water Field (NWF) to implicitly model the water parameters, while extending the latest 3D Gaussian Splatting (3DGS) to model the objects explicitly. Both components are integrated through a physics-based underwater image formation model to represent complex underwater scenes. Moreover, to construct more precise scene geometry and details, we design a Depth-Guided Optimization (DGO) mechanism that uses a pseudo-depth map as auxiliary guidance. After optimization, Aquatic-GS enables the rendering of novel underwater viewpoints and supports restoring the true appearance of underwater scenes, as if the water medium were absent. Extensive experiments on both simulated and real-world datasets demonstrate that Aquatic-GS surpasses state-of-the-art underwater 3D representation methods, achieving better rendering quality and real-time rendering performance with a 410x increase in speed. Furthermore, regarding underwater image restoration, Aquatic-GS outperforms representative dewatering methods in color correction, detail recovery, and stability.
表示水下3D场景是一项既有价值又复杂的任务，因为在水下成像过程中，衰减和散射效应显著耦合了物体和水体的信息。这种耦合为现有方法带来了巨大挑战，难以同时有效表示物体和水介质。为了解决这一问题，我们提出了Aquatic-GS，一种用于水下场景的混合3D表示方法，可以有效地同时表示物体和水体介质。具体而言，我们构建了一个神经水域场（Neural Water Field, NWF），用于隐式建模水体参数，同时扩展了最新的3D高斯散点（3DGS）方法来显式建模物体。这两个组件通过基于物理的水下图像生成模型相结合，以表现复杂的水下场景。此外，为了构建更精确的场景几何和细节，我们设计了一个深度引导优化（Depth-Guided Optimization, DGO）机制，使用伪深度图作为辅助指导。在优化后，Aquatic-GS能够渲染新的水下视点，并支持还原水下场景的真实外观，就像水体介质不存在一样。大量的模拟和真实数据集实验表明，Aquatic-GS优于最先进的水下3D表示方法，提供了更好的渲染质量和实时渲染性能，速度提升了410倍。此外，在水下图像还原方面，Aquatic-GS在色彩校正、细节恢复和稳定性上也优于代表性去水方法。