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- license: cc-by-nc-sa-4.0
 
 
 
 
 
 
 
 
 
 
 
 
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+ pretty_name: SignSparK Data (CSL-Daily & How2Sign SMPL-X pose features)
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+ license: other
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+ language:
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+ - zh
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+ - en
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+ tags:
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+ - sign-language
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+ - sign-language-production
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+ - pose
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+ - smpl-x
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+ - flow-matching
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+ size_categories:
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+ - 1K<n<10K
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  ---
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+
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+ # SignSparK Data
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+
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+ Prebuilt LMDB datasets for **SignSparK: Efficient Multilingual Sign Language
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+ Production via Sparse Keyframe Learning** (ECCV 2026). Contains SMPL-X 6D pose
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+ features, spoken-language translations, glosses, and per-frame segment
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+ annotations for **CSL-Daily** and **How2Sign**, ready to train/sample with the
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+ [SignSparK code](https://github.com/JianHe0628/SignSparK).
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+
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+ - 📄 Paper: https://arxiv.org/abs/2603.10446
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+ - 🌐 Project page: https://cogvis-cvssp.github.io/papers/signspark/
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+
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+ ## Contents
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+
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+ ```
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+ train/ CSL-Daily_reopt_train.lmdb How2Sign_reopt_train.lmdb
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+ dev/ CSL-Daily_reopt_dev.lmdb How2Sign_reopt_dev.lmdb
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+ test/ CSL-Daily_reopt_test.lmdb How2Sign_reopt_test.lmdb
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+ ```
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+
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+ Each `.lmdb` holds one `__meta__` key (clip index) plus one in-memory `.npz`
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+ blob per clip with: `language`, `translation`, `gloss`, `segment` (per-frame
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+ {0,1,2}), and `left/right/body/face_features` (6D rotations). Full schema in the
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+ repo's [`DATA.md`](https://github.com/JianHe0628/SignSparK/blob/main/DATA.md).
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+
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+ ## Usage
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+
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+ ```bash
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+ python tools/download_data.py --datasets CSL-Daily How2Sign --dest ./data
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+ export DATA_ROOT=$(pwd)/data
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+ python tools/inspect_lmdb.py ${DATA_ROOT}/lmdb/train/CSL-Daily_reopt_train.lmdb
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+ ```
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+
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+ ## License & terms
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+
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+ These are SMPL-X pose features **derived from** the CSL-Daily and How2Sign
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+ corpora and are released for **non-commercial research use** under the terms of
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+ the original datasets. Obtain and comply with each source dataset's license:
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+
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+ - CSL-Daily: https://ustc-slr.github.io/datasets/2021_csl_daily/
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+ - How2Sign: https://how2sign.github.io/
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @inproceedings{low2026signspark,
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+ title = {SignSparK: Efficient Multilingual Sign Language Production via Sparse Keyframe Learning},
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+ author = {Low, Jianhe and Symeonidis-Herzig, Alexandre and Ivashechkin, Maksym and Sincan, {\"O}zge Mercano{\u{g}}lu and Bowden, Richard},
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+ booktitle = {European Conference on Computer Vision (ECCV)},
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+ year = {2026}
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+ }
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+ ```