用物理模型分离水下光影干扰,提升3D场景重建质量
3D-UIR: 3D Gaussian for Underwater 3D Scene Reconstruction via Physics Based Appearance-Medium Decoupling
- 通过显式建模水体散射与衰减,解耦物体外观与介质影响
- 引入伪深度监督与尺度惩罚,显著提升几何精度
- 适合水下三维重建、光学成像修复等应用
水下新视角合成面临复杂光-介质相互作用的挑战。水中光学散射与吸收导致非均匀介质衰减,破坏传统体渲染对均匀传播介质的假设。尽管3D高斯泼溅(3DGS)具备实时渲染能力,但在存在散射介质的水下非均匀环境中仍会产生伪影且外观不一致。本文提出一种基于物理的框架,通过定制化高斯建模将物体外观与水体介质效应解耦。方法引入外观嵌入,作为后向散射和衰减的显式介质表征,增强场景一致性。此外,提出基于深度引导的优化策略,利用伪深度图作为监督信号,并加入深度正则化与尺度惩罚项,以提升几何保真度。通过结合所提出的外观与介质建模组件,构建水下成像模型,实现高质量的新视角合成与物理准确的场景还原。实验表明,本方法在渲染质量和恢复精度上均显著优于现有方法。
原文摘要 · Abstract (English)
Novel view synthesis for underwater scene reconstruction presents unique challenges due to complex light-media interactions. Optical scattering and absorption in water body bring inhomogeneous medium attenuation interference that disrupts conventional volume rendering assumptions of uniform propagation medium. While 3D Gaussian Splatting (3DGS) offers real-time rendering capabilities, it struggles with underwater inhomogeneous environments where scattering media introduces artifacts and inconsistent appearance. In this study, we propose a physics-based framework that disentangles object appearance from water medium effects through tailored Gaussian modeling. Our approach introduces appearance embeddings, which are explicit medium representations for backscatter and attenuation, enhancing scene consistency. In addition, we propose a depth-guided optimization strategy that leverages pseudo-depth maps as supervision with depth regularization and scale penalty terms to improve geometric fidelity. By integrating the proposed appearance and medium modeling components via an underwater imaging model, our approach achieves both high-quality novel view synthesis and physically accurate scene restoration. Experiments demonstrate our significant improvements in rendering quality and restoration accuracy over existing methods. The project page is available at https://bilityniu.github.io/3D-UIR.
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