Gaussian Compression for Precomputed Indirect Illumination

gradient propagation process to replace conventional inference frameworks, like PyTorch, ensuring an exceptional compression speed.

At the same time, by constructing a cascaded light field texture in realtime, we avoid the need for baking and storing a large number of redundant light field probes arranged in the form of 3D textures. This approach allows us to achieve further compression of the memory while maintaining high visual quality and rendering speed. Compared to traditional methods based on Principal Component Analysis (PCA), our approach consistently yields superb results across various test scenarios, achieving compression ratios of up to 1:50.