In recent years, 3D Gaussian splatting (3DGS) has achieved remarkable progress in novel view synthesis. However, accurately reconstructing glossy surfaces under complex illumination remains challenging, particularly in scenes with strong specular reflections and multi-surface interreflections. To address this issue, we propose SSR-GS, a specular reflection modeling framework for glossy surface reconstruction. Specifically, we introduce a prefiltered Mip-Cubemap to model direct specular reflections efficiently, and propose an IndiASG module to capture indirect specular reflections. Furthermore, we design Visual Geometry Priors (VGP) that couple a reflection-aware visual prior via a reflection score (RS) to downweight the photometric loss contribution of reflection-dominated regions, with geometry priors derived from VGGT, including progressively decayed depth supervision and transformed normal constraints. Extensive experiments on both synthetic and real-world datasets demonstrate that SSR-GS achieves state-of-the-art performance in glossy surface reconstruction.

翻译：近年来，三维高斯泼溅（3DGS）在新视角合成方面取得了显著进展。然而，在复杂光照条件下精确重建光泽表面仍然具有挑战性，尤其是在存在强镜面反射和多表面相互反射的场景中。为解决此问题，我们提出了SSR-GS，一个用于光泽表面重建的镜面反射建模框架。具体而言，我们引入了一个预滤波的Mip-Cubemap来高效建模直接镜面反射，并提出了一个IndiASG模块来捕捉间接镜面反射。此外，我们设计了视觉几何先验（VGP），它通过反射分数（RS）耦合了一个反射感知的视觉先验，以降低反射主导区域对光度损失的贡献，同时结合了源自VGGT的几何先验，包括渐进衰减的深度监督和变换后的法向约束。在合成数据集和真实世界数据集上进行的大量实验表明，SSR-GS在光泽表面重建方面达到了最先进的性能。