This paper presents a 3D Gaussian Inverse Rendering (GIR) method, employing 3D Gaussian representations to effectively factorize the scene into material properties, light, and geometry. The key contributions lie in three-fold. We compute the normal of each 3D Gaussian using the shortest eigenvector, with a directional masking scheme forcing accurate normal estimation without external supervision. We adopt an efficient voxel-based indirect illumination tracing scheme that stores direction-aware outgoing radiance in each 3D Gaussian to disentangle secondary illumination for approximating multi-bounce light transport. To further enhance the illumination disentanglement, we represent a high-resolution environmental map with a learnable low-resolution map and a lightweight, fully convolutional network. Our method achieves state-of-the-art performance in both relighting and novel view synthesis tasks among the recently proposed inverse rendering methods while achieving real-time rendering. This substantiates our proposed method's efficacy and broad applicability, highlighting its potential as an influential tool in various real-time interactive graphics applications such as material editing and relighting. The code will be released at https://github.com/guduxiaolang/GIR.

翻译：本文提出了一种三维高斯逆渲染（GIR）方法，利用三维高斯表示将场景有效地分解为材质属性、光照与几何结构。其主要贡献体现在三个方面。我们采用最短特征向量计算每个三维高斯的法向量，并通过方向掩蔽方案在无需外部监督的情况下实现精确的法向估计。我们采用了一种高效的基于体素的间接光照追踪方案，在每个三维高斯中存储方向感知的出射辐射度，以解耦二次光照并近似多弹射光传输。为进一步增强光照解耦能力，我们使用可学习的低分辨率环境贴图与一个轻量级全卷积网络来表示高分辨率环境贴图。在近期提出的逆渲染方法中，我们的方法在重光照与新视角合成任务上均达到了最先进的性能，同时实现了实时渲染。这验证了所提方法的有效性与广泛适用性，突显了其在材质编辑与重光照等多种实时交互图形应用中的潜力。代码将在 https://github.com/guduxiaolang/GIR 发布。