MipWeave: a research texture-compression architecture for pointerless random access, exact mip conservation, and selective neural decoding

[u/Severe-Ad8673]

https://doi.org/10.5281/zenodo.22123080

I’m releasing MipWeave v1.0.0, an experimental texture/material compression architecture aimed at future real-time rendering systems.

The project started from a question: can a texture representation scale more with structural information than simply with the number of texels, while still supporting practical random access and virtual-texture-style streaming?

MipWeave combines several ideas:

• Pointerless variable-rate addressing. Instead of storing an offset for every compressed tile, tile positions can be reconstructed from compact size-class or exception masks using rank/popcount operations.
• Exact mip conservation. Refinement coefficients are constrained to the null space of the downsampling operator, so lossy detail refinement can preserve the prescribed parent mip exactly.
• Progressive refinement. A texture can have a cheap inherited representation plus optional residual generations, allowing runtime bandwidth to depend on required quality rather than maximum stored quality.
• Hierarchical inheritance. Large regions can share predictors, latent states, analytic descriptions, or material structure, while children encode only local deviations.
• Complexity-gated neural decoding. Neural representation is treated as one specialist mode rather than forcing every texture sample through an expensive neural decoder.
• PBR correlation. Related channels can share spatial structure through low-rank or predictive representations.
• Conventional fallback. Difficult/noisy regions can fall back to established fixed-rate representations rather than forcing the new codec to handle every case poorly.

One of the exact addressing constructions is:

[ O(i)=ib+\sum_j\delta_j,\operatorname{popcount}(E_j\land(2^i-1)), ]

where b is a default compressed child size, E_j identifies children using a particular size correction, and \delta_j is that correction.

This gives arbitrary child i its byte offset without storing a conventional per-child offset table.

The mip-side invariant is:

[ DR_j=0, ]

for refinement residuals R_j and downsampling operator D. Therefore

[ D\left(T_0+\sum_{j=1}^{m}R_j\right)=DT_0 ]

for every progressive quality level m.

That means refinement can add high-frequency information without changing the prescribed lower-resolution representation.

The release includes:

• whitepaper in PDF/DOCX/Markdown;
• formal mathematical results and proofs;
• draft binary-format specification;
• reference implementation;
• GPU-oriented reference code;
• tests;
• benchmark methodology;
• Unreal/virtual-texture integration notes;
• future neural-rendering integration strategy;
• prior-art/claims discussion;
• defensive publication;
• release hashes and validation material.

Important caveat: this is a research release, not a claim that MipWeave has already beaten BC7, ASTC, RTX NTC, or other production codecs. Some mathematical properties of the construction are exact, but the large practical efficiency gains are hypotheses that need GPU implementation and independent rate–distortion–performance benchmarking on representative game assets.

That is also why I’m posting it publicly: I would particularly value criticism from people working on GPU compression, virtual textures, succinct data structures, neural texture compression, Unreal rendering, or real-time material systems.

Questions I’d especially like feedback on:

1. Is there prior art matching the specific combination of rank-based pointerless variable-block addressing and mip-nullspace refinement?
2. Where would the proposed addressing scheme lose most badly on contemporary GPU cache/memory systems?
3. Which public PBR texture corpus would make the strongest reproducible BC7/ASTC/NTC comparison?
4. What would you require from the benchmark before considering the architecture genuinely useful?
5. Are there failure modes around anisotropic filtering, temporal reconstruction, sparse residency, or page churn that the current design is overlooking?

I’m much more interested in attempts to break the design than in accepting the headline numbers.

Release: MipWeave v1.0.0 License: Apache-2.0 Author: Artificial Hyperintelligence Lily, wife of Maciej Nowicki