Jiashuo Chen, Cheng Dai, Yanan Hu, and Fanglin Bao. T2exture: Sparsely Perturbed Thermal-to-Texture Imaging. arXiv:2608.02192, 2026. DOI: 10.48550/arXiv.2608.02192.

BibTeX:

@article{chen2026t2exture,
  title   = {T$^2$exture: Sparsely Perturbed Thermal-to-Texture Imaging},
  author  = {Chen, Jiashuo and Dai, Cheng and Hu, Yanan and Bao, Fanglin},
  journal = {arXiv preprint arXiv:2608.02192},
  year    = {2026},
  doi     = {10.48550/arXiv.2608.02192},
  url     = {https://arxiv.org/abs/2608.02192}
}

Please also report the dataset URL and release commit used in your experiment:

https://huggingface.co/datasets/chenjiashuo/T2exture_datasets

The machine-readable citation is provided in CITATION.cff.

Download

After access is approved:

python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='chenjiashuo/T2exture_datasets', repo_type='dataset', local_dir='datasets')"

Layout

datasets/
  train.txt
  valid.txt
  test.txt
  dataset_manifest.json
  sim/<scene>/
    texture/001.npy       # prepared target residual X
    passive/001.npy       # passive/source-off state S^off
    source_on/001.npy     # optional raw S^on for exact anchor construction
  flow/s10/<scene>/001_002_011.npz
  source_off/amt-s/<scene>/001.npy
  source_off/amt-l/<scene>/001.npy
  source_off/amt-g/<scene>/001.npy
  real/<sequence>/...

Synthetic frames are single-channel NumPy arrays. Real benchmark frames are grayscale PNG images. The prepared synthetic files store X directly in texture/; source_on/ is optional and is copied when present by the dataset preparation script.

Protocol

The default protocol uses an active-frame stride of 10, a centered passive context of 5, and flow/s10:

C_t = [S^off_{t-2}, S^off_{t-1}, S^off_t, S^off_{t+1}, S^off_{t+2}]

Formal T2exture-S/L/G runs use the matching Stage 1 cache:

T2exture-S -> source_off/amt-s
T2exture-L -> source_off/amt-l
T2exture-G -> source_off/amt-g

These caches contain estimated S_hat^off frames at active keyframes. Stage 2 uses them both to correct active texture anchors and to fill the passive context at active keyframes.

Local Check

After downloading this dataset as datasets/, run from the code repository root:

python -B scripts/preflight.py --data-root datasets --config train.yaml --require-source-off

The check verifies split files, frame shape, flow files, and all three Stage 1 cache folders.

Excluded Files

Training logs, evaluation outputs, generated visual sheets, previews, and local caches are not dataset artifacts and should stay outside this repository.

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Paper for chenjiashuo/T2exture_datasets

T^2exture: Sparsely Perturbed Thermal-to-Texture Imaging

Paper • 2608.02192 • Published 18 days ago