We develop a method that recovers the surface, materials, and illumination of a scene from its posed multi-view images. In contrast to prior work, it does not require any additional data and can handle glossy objects or bright lighting. It is a progressive inverse rendering approach, which consists of three stages. First, we reconstruct the scene radiance and signed distance function (SDF) with our novel regularization strategy for specular reflections. Our approach considers both the diffuse and specular colors, which allows for handling complex view-dependent lighting effects for surface reconstruction. Second, we distill light visibility and indirect illumination from the learned SDF and radiance field using learnable mapping functions. Third, we design a method for estimating the ratio of incoming direct light represented via Spherical Gaussians reflected in a specular manner and then reconstruct the materials and direct illumination of the scene. Experimental results demonstrate that the proposed method outperforms the current state-of-the-art in recovering surfaces, materials, and lighting without relying on any additional data.

翻译：我们提出了一种方法，能够从已标定姿态的多视角图像中恢复场景的表面、材质与光照。与先前工作不同，该方法无需任何额外数据，且可处理光泽物体或强光照场景。这是一种渐进式逆渲染方法，包含三个阶段。首先，我们通过针对镜面反射的新型正则化策略重建场景辐射度与符号距离函数（SDF）。该方法同时考虑漫反射与镜面反射颜色，能够处理复杂的视角相关光照效应以实现表面重建。其次，我们利用可学习映射函数从已学习的SDF与辐射场中提炼光可见性与间接光照信息。最后，我们设计了一种估计以球面高斯函数表示的镜面反射入射直接光比例的方法，进而重建场景的材质与直接光照。实验结果表明，所提方法在无需依赖任何额外数据的情况下，在表面、材质与光照恢复任务中均优于当前最优方法。