PSDR-Room: Single Photo to Scene using Differentiable Rendering

July 06, 2023 Β· Declared Dead Β· πŸ› ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia

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Authors Kai Yan, Fujun Luan, MiloΕ  HaΕ An, Thibault Groueix, Valentin Deschaintre, Shuang Zhao arXiv ID 2307.03244 Category cs.CV: Computer Vision Cross-listed cs.GR Citations 26 Venue ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia Last Checked 5 months ago
Abstract
A 3D digital scene contains many components: lights, materials and geometries, interacting to reach the desired appearance. Staging such a scene is time-consuming and requires both artistic and technical skills. In this work, we propose PSDR-Room, a system allowing to optimize lighting as well as the pose and materials of individual objects to match a target image of a room scene, with minimal user input. To this end, we leverage a recent path-space differentiable rendering approach that provides unbiased gradients of the rendering with respect to geometry, lighting, and procedural materials, allowing us to optimize all of these components using gradient descent to visually match the input photo appearance. We use recent single-image scene understanding methods to initialize the optimization and search for appropriate 3D models and materials. We evaluate our method on real photographs of indoor scenes and demonstrate the editability of the resulting scene components.
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