LuxRemix: Lighting Decomposition and Remixing for Indoor Scenes
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866917535460360192 |
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| author | Liang, Ruofan Müller, Norman Weber, Ethan Zauss, Duncan Vijaykumar, Nandita Kontschieder, Peter Richardt, Christian |
| author_facet | Liang, Ruofan Müller, Norman Weber, Ethan Zauss, Duncan Vijaykumar, Nandita Kontschieder, Peter Richardt, Christian |
| contents | We present a novel approach for interactive light editing in indoor scenes from a single multi-view scene capture. Our method leverages a generative image-based light decomposition model that factorizes complex indoor scene illumination into its constituent light sources. This factorization enables independent manipulation of individual light sources, specifically allowing control over their state (on/off), chromaticity, and intensity. We further introduce multi-view lighting harmonization to ensure consistent propagation of the lighting decomposition across all scene views. This is integrated into a relightable 3D Gaussian splatting representation, providing real-time interactive control over the individual light sources. Our results demonstrate highly photorealistic lighting decomposition and relighting outcomes across diverse indoor scenes. We evaluate our method on both synthetic and real-world datasets and provide a quantitative and qualitative comparison to state-of-the-art techniques. For video results and interactive demos, see https://luxremix.github.io. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_15283 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | LuxRemix: Lighting Decomposition and Remixing for Indoor Scenes Liang, Ruofan Müller, Norman Weber, Ethan Zauss, Duncan Vijaykumar, Nandita Kontschieder, Peter Richardt, Christian Computer Vision and Pattern Recognition Graphics We present a novel approach for interactive light editing in indoor scenes from a single multi-view scene capture. Our method leverages a generative image-based light decomposition model that factorizes complex indoor scene illumination into its constituent light sources. This factorization enables independent manipulation of individual light sources, specifically allowing control over their state (on/off), chromaticity, and intensity. We further introduce multi-view lighting harmonization to ensure consistent propagation of the lighting decomposition across all scene views. This is integrated into a relightable 3D Gaussian splatting representation, providing real-time interactive control over the individual light sources. Our results demonstrate highly photorealistic lighting decomposition and relighting outcomes across diverse indoor scenes. We evaluate our method on both synthetic and real-world datasets and provide a quantitative and qualitative comparison to state-of-the-art techniques. For video results and interactive demos, see https://luxremix.github.io. |
| title | LuxRemix: Lighting Decomposition and Remixing for Indoor Scenes |
| topic | Computer Vision and Pattern Recognition Graphics |
| url | https://arxiv.org/abs/2601.15283 |