PRTGS: Precomputed Radiance Transfer of Gaussian Splats for Real-Time High-Quality Relighting
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arXiv
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| Autori principali: | , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866911980536725504 |
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| author | Guo, Yijia Bai, Yuanxi Hu, Liwen Guo, Ziyi Liu, Mianzhi Cai, Yu Huang, Tiejun Ma, Lei |
| author_facet | Guo, Yijia Bai, Yuanxi Hu, Liwen Guo, Ziyi Liu, Mianzhi Cai, Yu Huang, Tiejun Ma, Lei |
| contents | We proposed Precomputed RadianceTransfer of GaussianSplats (PRTGS), a real-time high-quality relighting method for Gaussian splats in low-frequency lighting environments that captures soft shadows and interreflections by precomputing 3D Gaussian splats' radiance transfer. Existing studies have demonstrated that 3D Gaussian splatting (3DGS) outperforms neural fields' efficiency for dynamic lighting scenarios. However, the current relighting method based on 3DGS still struggles to compute high-quality shadow and indirect illumination in real time for dynamic light, leading to unrealistic rendering results. We solve this problem by precomputing the expensive transport simulations required for complex transfer functions like shadowing, the resulting transfer functions are represented as dense sets of vectors or matrices for every Gaussian splat. We introduce distinct precomputing methods tailored for training and rendering stages, along with unique ray tracing and indirect lighting precomputation techniques for 3D Gaussian splats to accelerate training speed and compute accurate indirect lighting related to environment light. Experimental analyses demonstrate that our approach achieves state-of-the-art visual quality while maintaining competitive training times and allows high-quality real-time (30+ fps) relighting for dynamic light and relatively complex scenes at 1080p resolution. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_03538 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | PRTGS: Precomputed Radiance Transfer of Gaussian Splats for Real-Time High-Quality Relighting Guo, Yijia Bai, Yuanxi Hu, Liwen Guo, Ziyi Liu, Mianzhi Cai, Yu Huang, Tiejun Ma, Lei Computer Vision and Pattern Recognition We proposed Precomputed RadianceTransfer of GaussianSplats (PRTGS), a real-time high-quality relighting method for Gaussian splats in low-frequency lighting environments that captures soft shadows and interreflections by precomputing 3D Gaussian splats' radiance transfer. Existing studies have demonstrated that 3D Gaussian splatting (3DGS) outperforms neural fields' efficiency for dynamic lighting scenarios. However, the current relighting method based on 3DGS still struggles to compute high-quality shadow and indirect illumination in real time for dynamic light, leading to unrealistic rendering results. We solve this problem by precomputing the expensive transport simulations required for complex transfer functions like shadowing, the resulting transfer functions are represented as dense sets of vectors or matrices for every Gaussian splat. We introduce distinct precomputing methods tailored for training and rendering stages, along with unique ray tracing and indirect lighting precomputation techniques for 3D Gaussian splats to accelerate training speed and compute accurate indirect lighting related to environment light. Experimental analyses demonstrate that our approach achieves state-of-the-art visual quality while maintaining competitive training times and allows high-quality real-time (30+ fps) relighting for dynamic light and relatively complex scenes at 1080p resolution. |
| title | PRTGS: Precomputed Radiance Transfer of Gaussian Splats for Real-Time High-Quality Relighting |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2408.03538 |