Vlad Erium ๐ฏ๐ต (@ssh4net)
2025-06-03 | โค๏ธ 100 | ๐ 18
WishGI: Lightweight Static Global Illumination Baking via Spherical Harmonics Fitting Junke Zhu, Zehan Wu, Qixing Zhang, Cheng Liao, Zhangjin Huang
https://arxiv.org/abs/2506.01288
Abstract: 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.
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