用高斯表面元实现反照率与光照的精确分离，提升光泽物体重建质量。
GOGS: High-Fidelity Geometry and Relighting for Glossy Objects via Gaussian Surfels
- 基于2D高斯表面元，结合物理渲染与几何先验重建表面
- 通过重要性采样与方向编码，还原高频镜面高光和间接光照
- 适合需要真实光照重演的三维建模与材质分析场景
从RGB图像逆向渲染光泽物体仍受本质模糊性制约。尽管基于NeRF的方法通过密集采样实现高保真重建，但计算成本过高；近期3D高斯泼溅虽效率更高，但在镜面反射下表现受限，多视角不一致性导致高频表面噪声与结构伪影，简化渲染方程也掩盖了材料属性，造成不真实的光照重演。为此，我们提出GOGS，一种基于2D高斯表面元的两阶段框架：首先利用物理渲染与分段求和近似建立鲁棒表面重建，并引入基础模型的几何先验；其次通过蒙特卡洛重要性采样完整渲染方程，借助可微2D高斯射线追踪建模间接照明，并采用球形mipmap方向编码捕捉各向异性高光，精细修复高频镜面细节。大量实验表明，该方法在几何重建、材质分离与新光照下的照片级重演方面达到当前最优性能，优于现有逆向渲染方法。
原文摘要 · Abstract (English)
Inverse rendering of glossy objects from RGB imagery remains fundamentally limited by inherent ambiguity. Although NeRF-based methods achieve high-fidelity reconstruction via dense-ray sampling, their computational cost is prohibitive. Recent 3D Gaussian Splatting achieves high reconstruction efficiency but exhibits limitations under specular reflections. Multi-view inconsistencies introduce high-frequency surface noise and structural artifacts, while simplified rendering equations obscure material properties, leading to implausible relighting results. To address these issues, we propose GOGS, a novel two-stage framework based on 2D Gaussian surfels. First, we establish robust surface reconstruction through physics-based rendering with split-sum approximation, enhanced by geometric priors from foundation models. Second, we perform material decomposition by leveraging Monte Carlo importance sampling of the full rendering equation, modeling indirect illumination via differentiable 2D Gaussian ray tracing and refining high-frequency specular details through spherical mipmap-based directional encoding that captures anisotropic highlights. Extensive experiments demonstrate state-of-the-art performance in geometry reconstruction, material separation, and photorealistic relighting under novel illuminations, outperforming existing inverse rendering approaches.
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