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Physically-Based Editing of Indoor Scene Lighting from a Single Image. (arXiv:2205.09343v1 [cs.CV])
May 20, 2022, 1:10 a.m. | Zhengqin Li, Jia Shi, Sai Bi, Rui Zhu, Kalyan Sunkavalli, Miloš Hašan, Zexiang Xu, Ravi Ramamoorthi, Manmohan Chandraker
cs.CV updates on arXiv.org arxiv.org
We present a method to edit complex indoor lighting from a single image with
its predicted depth and light source segmentation masks. This is an extremely
challenging problem that requires modeling complex light transport, and
disentangling HDR lighting from material and geometry with only a partial LDR
observation of the scene. We tackle this problem using two novel components: 1)
a holistic scene reconstruction method that estimates scene reflectance and
parametric 3D lighting, and 2) a neural rendering framework that …
More from arxiv.org / cs.CV updates on arXiv.org
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