# Neural Texture Block Compression

arXiv: https://arxiv.org/abs/2407.09543 · HTML: https://mlsanity.com/paper/2407.09543/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Jun 2024.

## Built on by (most cited first, 2 of 2)

- [Collaborative Texture Filtering](https://mlsanity.com/paper/2506.17770/) (2025)
- [PEPS: Positional Encoding Projected Sampling -- Extended](https://mlsanity.com/paper/2604.24167/) (2026)

## Abstract (arXiv)

Block compression is a widely used technique to compress textures in real-time graphics applications, offering a reduction in storage size. However, their storage efficiency is constrained by the fixed compression ratio, which substantially increases storage size when hundreds of high-quality textures are required. In this paper, we propose a novel block texture compression method with neural networks, Neural Texture Block Compression (NTBC). NTBC learns the mapping from uncompressed textures to block-compressed textures, which allows for significantly reduced storage costs without any change in the shaders.Our experiments show that NTBC can achieve reasonable-quality results with up to about 70% less storage footprint, preserving real-time performance with a modest computational overhead at the texture loading phase in the graphics pipeline.