RUSplatting：面向稀疏视角水下场景重建的鲁棒三维高斯溅射
RUSplatting: Robust 3D Gaussian Splatting for Sparse-View Underwater Scene Reconstruction
AI总结：
针对水下场景重建受光线特性和稀疏视角限制的难题，提出基于高斯溅射的RUSplatting框架，通过解耦色彩学习、自适应加权帧插值和新型损失函数提升重建效果，还发布深海数据集Submerged3D，性能优于现有最优方法。
摘要：
由于水生环境固有的光线吸收、散射和能见度有限，重建高保真水下场景仍是一项具有挑战性的任务。本文提出一种增强型的基于高斯溅射（Gaussian Splatting）的框架，可同时提升深水渲染的视觉质量和几何精度。我们受水下衰减物理规律启发，提出对RGB通道进行解耦学习，以实现更准确的色彩恢复。为解决稀疏视角的局限性并提升视角一致性，我们引入了一种带有新型自适应加权方案的帧插值策略。此外，我们提出了一种新的损失函数，旨在在保留边缘的同时降低噪声，这对深海内容至关重要。我们还发布了一个新收集的数据集Submerged3D，该数据集专门在深海环境中采集。实验结果表明，我们的框架始终优于现有最优方法，PSNR提升最高达1.90dB，具备更优的感知质量和鲁棒性，为海洋机器人和水下视觉分析提供了有前景的方向。RUSplatting的代码可在https://github.com/theflash987/RUSplatting获取，数据集Submerged3D可在https://zenodo.org/records/15482420下载。
英文摘要：
Reconstructing high-fidelity underwater scenes remains a challenging task due to light absorption, scattering, and limited visibility inherent in aquatic environments. This paper presents an enhanced Gaussian Splatting-based framework that improves both the visual quality and geometric accuracy of deep underwater rendering. We propose decoupled learning for RGB channels, guided by the physics of underwater attenuation, to enable more accurate colour restoration. To address sparse-view limitations and improve view consistency, we introduce a frame interpolation strategy with a novel adaptive weighting scheme. Additionally, we introduce a new loss function aimed at reducing noise while preserving edges, which is essential for deep-sea content. We also release a newly collected dataset, Submerged3D, captured specifically in deep-sea environments. Experimental results demonstrate that our framework consistently outperforms state-of-the-art methods with PSNR gains up to 1.90dB, delivering superior perceptual quality and robustness, and offering promising directions for marine robotics and underwater visual analytics. The code of RUSplatting is available at https://github.com/theflash987/RUSplatting and the dataset Submerged3D can be downloaded at https://zenodo.org/records/15482420.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
