PhotoScene: Photorealistic Material and Lighting Transfer for Indoor Scenes

Yu-Ying Yeh, Zhengqin Li, Yannick Hold-Geoffroy, Rui Zhu, Zexiang Xu +3 more
7/2/2022
cs.CV

No official code found. Best implementation: ViLab-UCSD/PhotoScene (103 stars, MIT, last commit 2023-10-24).

Abstract

Most indoor 3D scene reconstruction methods focus on recovering 3D geometry and scene layout. In this work, we go beyond this to propose PhotoScene, a framework that takes input image(s) of a scene along with approximately aligned CAD geometry (either reconstructed automatically or manually specified) and builds a photorealistic digital twin with high-quality materials and similar lighting. We model scene materials using procedural material graphs; such graphs represent photorealistic and resolution-independent materials. We optimize the parameters of these graphs and their texture scale and rotation, as well as the scene lighting to best match the input image via a differentiable rendering layer. We evaluate our technique on objects and layout reconstructions from ScanNet, SUN RGB-D and stock photographs, and demonstrate that our method reconstructs high-quality, fully relightable 3D scenes that can be re-rendered under arbitrary viewpoints, zooms and lighting.

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Code Implementations(1)

MIT

[CVPR2022] Official implementation of PhotoScene, a framework to transfer photorealistic material and lighting for indoor scene from photo.

10311Shell, PythonMar 28, 20222 years agoMIT

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Cite this paper

@article{yeh2022photoscene,
  title  = {PhotoScene: Photorealistic Material and Lighting Transfer for Indoor Scenes},
  author = {Yu-Ying Yeh and Zhengqin Li and Yannick Hold-Geoffroy and Rui Zhu and Zexiang Xu and Miloš Hašan and Kalyan Sunkavalli and Manmohan Chandraker},
  year   = {2022},
  eprint = {2207.00757},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2207.00757v1}
}

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