zyyy12138/motion-smd-data
Motion-SMD Data Data release for "Encoder-Free Human Motion Understanding via Structured Motion Descriptions". π Project page: https://yaozhang182.github.io/motion-smd/ π» Code: https://github.com/yaozhang182/motion-smd π€ LoRA adapters: https://huggingface.co/zyyy12138/motion-smd-lora π Paper (arXiv): https://arxiv.org/abs/2604.21668 What's here Four subdirectories, each with its own README.md describing files, provenance, and license: Subdir Contentsβ¦ See the full description on the dataset page: https://huggingface.co/datasets/zyyy12138/motion-smd-data.
Motion-SMD Data
Data release for "Encoder-Free Human Motion Understanding via Structured Motion Descriptions".
- π Project page: https://yaozhang182.github.io/motion-smd/
- π» Code: https://github.com/yaozhang182/motion-smd
- π€ LoRA adapters: https://huggingface.co/zyyy12138/motion-smd-lora
- π Paper (arXiv): https://arxiv.org/abs/2604.21668
What's here
Four subdirectories, each with its own README.md describing files, provenance, and license:
Why this repo
The main repository (github.com/yaozhang182/motion-smd) ships only code. Reproducing the paper requires ~5 GB of preprocessed data, including SMDs computed from the three upstream datasets. This HF repo bundles all of that so git clone + huggingface-cli download is enough to reach the training step.
Quick start
pip install huggingface_hub
# Option 1: download the entire dataset (~5 GB)
huggingface-cli download zyyy12138/motion-smd-data --repo-type dataset --local-dir motion-smd-data
# Option 2: download just one subdir (e.g., SMDs only, if you already have the
# upstream data locally)
huggingface-cli download zyyy12138/motion-smd-data --repo-type dataset \
--include "smd_texts/*" --local-dir motion-smd-dataThen symlink or move the subdirectories into the paths the code expects:
motion_smd/
βββ data/babel_qa/{joints,questions,questions_10opt,angle_texts_v5*.json}
βββ data/humman_qa/{joints,questions,questions_10opt,angle_texts_v5*.json}
βββ captioning/data/humanml3d/{new_joints,texts,Mean.npy,Std.npy,train.txt,val.txt,test.txt,angle_texts_v5*.json}See the root README.md of the code repo for the exact expected layout.
License
This release combines several sources under different licenses:
- Our derivatives (
smd_texts/*,*_qa/questions_10opt/*) are released under the MIT License. - Upstream data mirrored here (
*_qa/joints/,*_qa/questions/,humanml3d/*) retains its original license. See each subdir README.
If in doubt for a given file, consult the subdir README and the upstream source linked from it.
Citation
If you use this data, please cite the paper and the upstream sources listed in each subdir.
@article{zhang2026smd,
title = {Encoder-Free Human Motion Understanding via Structured Motion Descriptions},
author = {Zhang, Yao and Liu, Zhuchenyang and Ploetz, Thomas and Xiao, Yu},
journal = {arXiv preprint arXiv:2604.21668},
year = {2026}
}Contact
Yao Zhang β yao.1.zhang@aalto.fi
