Recovering the intrinsic physical attributes of a scene from images, generally termed as the inverse rendering problem, has been a central and challenging task in computer vision and computer graphics. In this paper, we present GUS-IR, a novel framework designed to address the inverse rendering problem for complicated scenes featuring rough and glossy surfaces. This paper starts by analyzing and comparing two prominent shading techniques popularly used for inverse rendering, forward shading and deferred shading, effectiveness in handling complex materials. More importantly, we propose a unified shading solution that combines the advantages of both techniques for better decomposition. In addition, we analyze the normal modeling in 3D Gaussian Splatting (3DGS) and utilize the shortest axis as normal for each particle in GUS-IR, along with a depth-related regularization, resulting in improved geometric representation and better shape reconstruction. Furthermore, we enhance the probe-based baking scheme proposed by GS-IR to achieve more accurate ambient occlusion modeling to better handle indirect illumination. Extensive experiments have demonstrated the superior performance of GUS-IR in achieving precise intrinsic decomposition and geometric representation, supporting many downstream tasks (such as relighting, retouching) in computer vision, graphics, and extended reality.
从图像中恢复场景的内在物理属性（通常称为反向渲染问题）一直是计算机视觉和计算机图形学中的核心挑战性任务。在本文中，我们提出了 GUS-IR，一个用于解决复杂场景（包括粗糙和光滑表面）反向渲染问题的新框架。本文首先分析并比较了反向渲染中常用的两种主要着色技术——正向着色 (forward shading) 和延迟着色 (deferred shading)——在处理复杂材质时的效果。更重要的是，我们提出了一种结合两种技术优势的统一着色解决方案，从而实现更优的分解。 此外，我们分析了 3D Gaussian Splatting (3DGS) 的法线建模，并在 GUS-IR 中利用每个粒子的最短轴作为法线，同时引入深度相关的正则化，提升了几何表示能力并改善了形状重建效果。此外，我们改进了 GS-IR 提出的基于探针的烘焙方案，以更精确地模拟环境光遮蔽（ambient occlusion），从而更好地处理间接光照。 大量实验表明，GUS-IR 在实现精确的内在分解和几何表示方面表现优越，支持包括重光照（relighting）和图像修饰（retouching）在内的众多下游任务，对计算机视觉、图形学和扩展现实领域具有广泛的应用价值。