WishGI: Lightweight Static Global Illumination Baking via Spherical Harmonics Fitting
Junke Zhu, Zehan Wu, Qixing Zhang, Cheng Liao, Zhangjin Huang
摘要
Global illumination combines direct and indirect lighting to create realistic lighting effects, bringing virtual scenes closer to reality. Static global illumination is a crucial component of virtual scene rendering, leveraging precomputation and baking techniques to significantly reduce runtime computational costs. Unfortunately, many existing works prioritize visual quality by relying on extensive texture storage and massive pixel-level texture sampling, leading to large performance overhead. In this paper, we introduce an illumination reconstruction method that effectively reduces sampling in fragment shader and avoids additional render passes, making it well-suited for low-end platforms. To achieve high-quality global illumination with reduced memory usage, we adopt a spherical harmonics fitting approach for baking effective illumination information and propose an inverse probe distribution method that generates unique probe associations for each mesh. This association, which can be generated offline in the local space, ensures consistent lighting quality across all instances of the same mesh. As a consequence, our method delivers highly competitive lighting effects while using only approximately 5% of the memory required by mainstream industry techniques.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
它引用的顶会 Paper5
- 3D Gaussian Splatting for Real-Time Radiance Field RenderingBernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George DrettakisSIGGRAPH 2023 · 被引用 5,687 次
- EMLight: Lighting Estimation via Spherical Distribution ApproximationFangneng Zhan, Changgong Zhang, Yingchen Yu, Yuan Chang 等AAAI 2021 · 被引用 73 次
- Compositional neural scene representations for shading inferenceJonathan Granskog, Fabrice Rousselle, Marios Papas, Jan NovákSIGGRAPH 2020 · 被引用 31 次
- NeLF-Pro: Neural Light Field Probes for Multi-Scale Novel View SynthesisZinuo You, Andreas Geiger, Anpei ChenCVPR 2024 · 被引用 6 次
- Scaffold-GS: Structured 3D Gaussians for View-Adaptive RenderingTao Lu, Mulin Yu, Linning Xu, Yuanbo Xiangli 等CVPR 2024
相关 Paper
- Multi-view Inverse Rendering for Large-scale Real-world Indoor ScenesZhen Li, Lingli Wang, Mofang Cheng, Cihui Pan 等CVPR 2023
- Neural 3D Reconstruction in the WildJiaming Sun, Xi Chen, Qianqian Wang, Zhengqi Li 等SIGGRAPH 2022 · 被引用 107 次
- GI-GS: Global Illumination Decomposition on Gaussian Splatting for Inverse RenderingHongze Chen, Zehong Lin, Jun ZhangICLR 2025
- ComGS: Efficient 3D Object-Scene Composition via Surface Octahedral ProbesJian Gao, Mengqi Yuan, Yifei Zeng, Chang Zeng 等ICLR 2026 · 被引用 1 次
- GauUpdate: New Object Insertion in 3D Gaussian Fields with Consistent Global IlluminationChengwei Ren, Fan Zhang, Liangchao Xu, Liang Pan 等ICCV 2025 · 被引用 1 次
