Decomposing an object's appearance into representations of its materials and the surrounding illumination is difficult, even when the object's 3D shape is known beforehand. This problem is especially challenging for diffuse objects: it is ill-conditioned because diffuse materials severely blur incoming light, and it is ill-posed because diffuse materials under high-frequency lighting can be indistinguishable from shiny materials under low-frequency lighting. We show that it is possible to recover precise materials and illumination -- even from diffuse objects -- by exploiting unintended shadows, like the ones cast onto an object by the photographer who moves around it. These shadows are a nuisance in most previous inverse rendering pipelines, but here we exploit them as signals that improve conditioning and help resolve material-lighting ambiguities. We present a method based on differentiable Monte Carlo ray tracing that uses images of an object to jointly recover its spatially-varying materials, the surrounding illumination environment, and the shapes of the unseen light occluders who inadvertently cast shadows upon it.

翻译：即使预先已知物体的三维形状，将其外观分解为材质表征与周围光照仍十分困难。这一问题对漫反射物体尤为棘手：由于漫反射材质会严重模糊入射光，问题呈现病态性；同时高频光照下的漫反射材质与低频光照下的光泽材质难以区分，导致问题具有不适定性。研究表明，通过利用意外阴影（例如摄影师围绕物体移动时投射在其上的阴影），即便是漫反射物体也能恢复精确的材质与光照信息。尽管这些阴影在以往的逆向渲染管线中被视为干扰，但我们将其作为改善问题适定性与解决材质-光照歧义的信号加以利用。本文提出基于可微分蒙特卡洛光线追踪的方法，通过物体图像联合恢复其空间变化的材质属性、周围光照环境，以及无意中为其投下阴影的不可见遮光体形状。