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Multi-view Inverse Rendering for Large-scale Real-world Indoor Scenes

2022-11-18 12:53:10
Zhen Li, Lingli Wang, Mofang Cheng, Cihui Pan, Jiaqi Yang

Abstract

We present a multi-view inverse rendering method for large-scale real-world indoor scenes that reconstructs global illumination and physically-reasonable SVBRDFs. Unlike previous representations, where the global illumination of large scenes is simplified as multiple environment maps, we propose a compact representation called Texture-based Lighting (TBL). It consists of 3D meshs and HDR textures, and efficiently models direct and infinite-bounce indirect lighting of the entire large scene. Based on TBL, we further propose a hybrid lighting representation with precomputed irradiance, which significantly improves the efficiency and alleviate the rendering noise in the material optimization. To physically disentangle the ambiguity between materials, we propose a three-stage material optimization strategy based on the priors of semantic segmentation and room segmentation. Extensive experiments show that the proposed method outperforms the state-of-the-arts quantitatively and qualitatively, and enables physically-reasonable mixed-reality applications such as material editing, editable novel view synthesis and relighting. The project page is at this https URL.

Abstract (translated)

URL

https://arxiv.org/abs/2211.10206

PDF

https://arxiv.org/pdf/2211.10206.pdf


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