Physically Controllable Relighting of Photographs

Physically Controllable Relighting of Photographs We present a photograph relighting method that enables explicit control over light sources akin to CG pipelines. Users can insert different types of light sources, such as spot lights, point lights, or environmental illumination into the scene. We achieve this in a pipeline involving mid-level computer vision, physically-based rendering, and neural rendering. We introduce a self-supervised training methodology using differentiable rendering to train our neural renderer with real-world photograph collections for in-the-wild generalization. Abstract We present a self-supervised approach to in-the-wild image relighting that enables fully controllable, physically based illumination editing. We achieve this by combining the physical accuracy of traditional rendering with the photorealistic appearance made possible by neural rendering. Our pipeline works by inferring a colored mesh representation of a given scene using monocular estimates of geometry and intrinsic components. This representation allows users to define their desired illumination configuration in 3D. The scene under the new lighting can then be rendered using a path-tracing engine. We send this approximate rendering of the scene through a feed-forward neural renderer to predict the final photorealistic relighting result. We develop a differentiable rendering process to reconstruct in-the-wild scene illumination, enabling self-supervised training of our neural renderer on raw image collections. Our method represents a significant step in bringing the explicit physical control over lights available in typical 3D computer graphics tools, such as Blender, to in-the-wild relighting. Video Paper Media Release Poster BibTeX License The methodology presented in this work is safeguarded under intellectual property protection. For inquiries regarding licensing opportunities, kindly reach out to SFU Technology Licensing Office and Dr. Yağız Aksoy . Related Publications