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MixLight: Borrowing the Best of both Spherical Harmonics and Gaussian Models
April 22, 2024, 4:45 a.m. | Xinlong Ji, Fangneng Zhan, Shijian Lu, Shi-Sheng Huang, Hua Huang
cs.CV updates on arXiv.org arxiv.org
Abstract: Accurately estimating scene lighting is critical for applications such as mixed reality. Existing works estimate illumination by generating illumination maps or regressing illumination parameters. However, the method of generating illumination maps has poor generalization performance and parametric models such as Spherical Harmonic (SH) and Spherical Gaussian (SG) fall short in capturing high-frequency or low-frequency components. This paper presents MixLight, a joint model that utilizes the complementary characteristics of SH and SG to achieve a more …
abstract applications arxiv best of cs.ai cs.cv cs.gr however lighting maps mixed mixed reality parameters parametric performance reality type
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