Nvidia Uses Neural Network for Innovative Texture Compression Method

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Nvidia this week introduced its new texture compression method that provides four times higher resolution than traditional Block Truncation Coding (BTC, BC) methods while having similar storage requirements. The core concept of the proposed approach is to compress multiple material textures and their mipmap chains collectively and then decompress them using a neural network that is trained for a particular pattern it decompresses. In theory, the method can even impact future GPU architectures. However, for now the method has limitations.

(Image credit: Nvidia)

New Requirements

Recent advancements in real-time rendering for video games have advanced the visual quality of movies due to the use of such techniques as physically-based shading for photorealistic modeling of materials, ray tracing, path tracing, and denoising for accurate global illumination. Meanwhile, texturing techniques have not really advanced at a similar pace mostly because texture compression methods essentially remained the same as in the late 1990s, which is why in some cases many objects look blurry in close proximity.

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