Neural block textures stored inside KTX2: a near-perfect fit

A developer has outlined a plan to embed neural block texture codecs directly into the Khronos KTX2 texture format, using KTX2 global data to store MLP inference weights of roughly 250-500 parameters (up to 1k). The approach targets real-time encoding to BC1-7/ASTC with no sidebands and a bitrate of about 1-2.5 bpp, positioning it against transform-domain codecs for single textures, PBR material sets, and correlated geospatial tiles. Initial R&D is complete, with training focused on CUDA and a slow CPU fallback.

A neural block texture codec can be part of the Khronos KTX2 texture format. The initial plan is a lowest common denominator approach: inference on load with SIMD+threading, ~250-500 MLP weights up to 1k , real-time encode to BC1-7/ASTC with no sidebands using basisu's existing analytical real-time encoders . It would compete vs. transform domain codecs ours and others that are surely coming . Valuable for single textures/photos, PBR material sets, correlated geospatial tiles. At first training will be focused on CUDA with a slow CPU fallback. Target bitrate would be ~1-2.5 bpp so XUBC7 class, not XUASTC which goes down to ~0.35 bpp . Inference cost is highly amortized across 2+ correlated textures the more the better . KTX2 global data can be used to hold the MLP inference weights, and the container format already supports mipmaps, texture arrays, seek tables, etc. The existing Basis Universal transcoding API would also be a great match. The initial R&D is done.