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amuse-beat

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speech-driven-gesture-generation
3d-motion
emotion
smplx
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Request access to the AMUSE research artifacts

Access is manually reviewed. For questions, contact amuse@tue.mpg.de or chhatre@kth.se.

By requesting access you agree to use these artifacts only under the AMUSE non-commercial research license.

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AMUSE-BEAT

Paper page: Hugging Face Papers 2312.04466
ArXiv: 2312.04466

This gated dataset repo hosts the released AMUSE-BEAT processed artifacts used for AMUSE.

What is included

  • BEAT-processed/eng_data_processed/
  • BEAT-processed/processed-all-modalities/aligned-dtw/
  • BEAT-processed/processed-all-modalities/fbanks/disentagler_loader.npz
  • beat_annotations_english/beat_cut_sem/
  • lmdb/data.mdb
  • train.csv: a lightweight manifest loadable with datasets

Quick start 

from datasets import load_dataset

ds = load_dataset("kiranchhatre/amuse-beat", split="train")
print(ds[0])

The root train.csv is a manifest for discovery and inspection. The full processed artifacts are also stored in this repo and can be downloaded with snapshot_download(...) after access is granted.

Redistribution notes

  • Third-party assets such as SMPL-X and Blender resources are not redistributed here.
  • This repo contains AMUSE-BEAT processed artifacts and annotations only.

Scope clarification

  • If you want to use the released prebuilt AMUSE training artifacts, this repo contains the processed data plus the LMDB path used by AMUSE.
  • If you want to reconstruct everything from original raw BEAT and SMPL-X-style sources, this HF dataset repo is not the full raw-data release; follow the full setup and data instructions in the AMUSE GitHub repository: https://github.com/kiranchhatre/amuse

Citation

If you use these artifacts, please cite AMUSE:

If you use AMUSE-BEAT as well, please also cite the original BEAT dataset and the EMAGE project as noted in the AMUSE release materials.

@InProceedings{Chhatre_2024_CVPR,
    author    = {Chhatre, Kiran and Daněček, Radek and Athanasiou, Nikos and Becherini, Giorgio and Peters, Christopher and Black, Michael J. and Bolkart, Timo},
    title     = {{AMUSE}: Emotional Speech-driven {3D} Body Animation via Disentangled Latent Diffusion},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2024},
    pages     = {1942-1953},
    url       = {https://amuse.is.tue.mpg.de},
}
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