v1.2 — Diffusart-retrain models, later natural-image checkpoints, ImageNet hint maps

v1.2 — Diffusart-retrain models, later natural-image (ImageNet) models and the ImageNet hint maps

Assets (SHA-256 in SHA256SUMS.txt and checkpoints/README.md)

File	Size	What it is
diffusart_retrain_scribble_dethint_200ep_ema.pth	373 MB	Diffusart (our re-implementation, reproduce/paper_experiments/diffusart_retrain/code/) retrained with the deterministic scribble hints, 200 epochs, EMA weights — the Diffusart-retrain scribble row of the supplementary "additional training comparisons" table (PSNR 19.457 / LPIPS 0.177 reproduced from its per-ratio record).
diffusart_retrain_dot_dethint_200ep_ema.pth	373 MB	Same for dot hints (the dot row of that table).
detfill_scribble_imagenet_96ch_200ep.pth	1.08 GB	DetFill scribble model on the natural-image (ImageNet subset) split, 96 base channels, 200 epochs (detfill/configs/scribble_real.yaml with model_channels: 96). A later training generation: not the model behind the printed ImageNet tables (those are the 64-channel models of v1.4).
detfill_dot_imagenet_96ch_200ep.pth	1.08 GB	Same for dot hints (96 base channels, later generation).
test_split_hint_maps_64_imagenet.tar.gz	40 MB	The stored 64×64 deterministic hint maps (Felzenszwalb regions; scribble/dot colour + mask) and region maps of 2,999 of the 3,000 ImageNet test images (detfill/configs/real/test.txt; n02667379_7324 has no stored map), i.e. the evaluation inputs of the supplementary ImageNet tables; layout as the Danbooru maps of v1.0.

Notes. The Diffusart-retrain models take the 64 × 64 hint maps of v1.0, upsampled to 256 × 256 with nearest-neighbour
interpolation inside infer_det_proposed.py (this is how the paper's record was produced). Our re-evaluation on 24 ImageNet
test images reproduces the printed ImageNet values with the 64-channel models (v1.4) and not with the 96-channel models
released here, which score 2–3 dB higher at every hint ratio. The ImageNet images themselves are not redistributed; the
split lists are in detfill/configs/real/ (relative paths).

Repository changes since v1.1: THIRD_PARTY_NOTICES.md (ColorizeDiffusion-derived inference wrappers stay under
CC BY-NC-SA 4.0; sketchKeras Apache-2.0), the Diffusart re-implementation code, the article DOI
(10.1109/TVCG.2026.3738401) in the README citation.