---
pretty_name: SignSparK checkpoints
license: other
language:
  - zh
  - en
tags:
  - sign-language
  - sign-language-production
  - pose
  - smpl-x
  - flow-matching
---

# SignSparK checkpoints

Pretrained flow-matching checkpoints for **SignSparK: Efficient Multilingual
Sign Language Production via Sparse Keyframe Learning** (ECCV 2026). One EMA
checkpoint per body stream (`unet_large`, ~1.4B params each), trained on
CSL-Daily, How2Sign and BOBSL.

- 💻 Code: https://github.com/JianHe0628/SignSparK
- 🗂️ Data: https://huggingface.co/datasets/LionelLow/SignSparK_data
- 📄 Paper: https://arxiv.org/abs/2603.10446 · 🌐 https://cogvis-cvssp.github.io/papers/signspark/

## Files

```
hand/ema_0.9999_200000.pt
body/ema_0.9999_200000.pt
face/ema_0.9999_200000.pt
```

## Usage

```bash
# fetch into $SIGNSPARK_CKPT_DIR
python tools/download_models.py --streams hand body face --dest ./checkpoints
export SIGNSPARK_CKPT_DIR=$(pwd)/checkpoints

# sample all three streams
python sample_all.py eval.note=CSLDaily eval.ode_stepnum=50 test_data='[CSL-Daily]'
```

See the [code repo](https://github.com/JianHe0628/SignSparK) for training,
sampling, and visualization.

## License

Released for non-commercial research use, under the terms of the datasets the
model was trained on (CSL-Daily, How2Sign, BOBSL).

## Citation

```bibtex
@inproceedings{low2026signspark,
  title     = {SignSparK: Efficient Multilingual Sign Language Production via Sparse Keyframe Learning},
  author    = {Low, Jianhe and Symeonidis-Herzig, Alexandre and Ivashechkin, Maksym and Sincan, {\"O}zge Mercano{\u{g}}lu and Bowden, Richard},
  booktitle = {European Conference on Computer Vision (ECCV)},
  year      = {2026}
}
```