This article was first published in arXiv*.
Our method optimizes N-dimensional Gaussians to approximate high-dimensional anisotropic functions in a few minutes. Our parameterization, culling, and optimization-controlled refinement allow us to quickly estimate Gaussian parameters to represent various complex functions. We show two applications:
- 10D+ Application (top): Synthetic scenes for which we can render G-buffers, such as world position, albedo, and roughness, can be shaded with global illumination through our 10D+ Gaussian mixture. Even though the Gaussians are evaluated on the surfaces, their representation power can efficiently estimate the appearance of reflections and transmittance with correct parallax effects. Apart from the G-buffers, we support the variability of moving objects and light sources as extra dimensions.
- 6D Application (bottom): Real-world scenes with complex, view-dependent effects can be modeled efficiently through our six-dimensional Gaussian mixture. The six dimensions of world position and view direction give the parameterization the same representation power for both diffuse and view-dependent effects, reconstructing complex effects like the one through the magnifying glass.