The underwater 3D scene reconstruction is a challenging, yet interesting problem with applications ranging from naval robots to VR experiences. The problem was successfully tackled by fully volumetric NeRF-based methods which can model both the geometry and the medium (water). Unfortunately, these methods are slow to train and do not offer real-time rendering. More recently, 3D Gaussian Splatting (3DGS) method offered a fast alternative to NeRFs. However, because it is an explicit method that renders only the geometry, it cannot render the medium and is therefore unsuited for underwater reconstruction. Therefore, we propose a novel approach that fuses volumetric rendering with 3DGS to handle underwater data effectively. Our method employs 3DGS for explicit geometry representation and a separate volumetric field (queried once per pixel) for capturing the scattering medium. This dual representation further allows the restoration of the scenes by removing the scattering medium. Our method outperforms state-of-the-art NeRF-based methods in rendering quality on the underwater SeaThru-NeRF dataset. Furthermore, it does so while offering real-time rendering performance, addressing the efficiency limitations of existing methods.
水下3D场景重建是一个充满挑战但极具趣味的问题，应用领域广泛，包括海军机器人和虚拟现实体验。之前的研究成功地利用基于全体积NeRF的方法解决了这个问题，这些方法能够同时建模几何结构和介质（水）。然而，这些方法的训练速度较慢，无法实现实时渲染。近期，3D高斯点绘（3DGS）方法为NeRF提供了一种快速替代方案。然而，由于3DGS是一种显式方法，仅渲染几何结构，无法渲染介质，因此不适用于水下重建。 为此，我们提出了一种新颖的方法，将体积渲染与3DGS融合，以有效处理水下数据。我们的方法利用3DGS进行显式几何表示，同时使用一个单独的体积场（每像素查询一次）来捕捉散射介质。这种双重表示还允许通过去除散射介质来恢复场景。我们的方法在渲染质量上优于最先进的基于NeRF的方法，特别是在水下SeaThru-NeRF数据集上表现突出。此外，该方法提供了实时渲染性能，有效解决了现有方法在效率上的局限性。