CVNov 18, 2022

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

arXiv:2211.10206v435 citationsh-index: 6
Originality Incremental advance
AI Analysis

This addresses the challenge of realistic material editing and relighting in mixed-reality applications for indoor scenes, representing a strong domain-specific advancement.

The paper tackles the problem of inverse rendering for large-scale indoor scenes by proposing a Texture-based Lighting representation and hybrid lighting approach, achieving state-of-the-art performance in reconstructing global illumination and materials with physically-reasonable results.

We present a efficient 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 mesh 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 alleviates 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-art 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 https://lzleejean.github.io/TexIR.

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