StyleGestures

This repository contains code for reproducing the papers "Moglow: Probabilistic and controllable motion synthesis using normalising flows" and "Style-Controllable Speech-Driven Gesture Synthesis Using Normalising Flows"

Please watch the following videos for an introduction: Moglow: (https://youtu.be/ozVldUcFjZg) Style Gestures: (https://youtu.be/egf3tjbWBQE)

Prerequisites

The 'environment.yml' contains the required dependencies.

Data

Our preprocessed version of the human locomotion data is available at https://kth.app.box.com/folder/116440954250. Download it to the 'data/locomotion' folder. The data is pooled from the Edinburgh Locomotion, CMU and HDM05 datasets. Please see the included README file for licenses and citations.

The gesture data is available at http://trinityspeechgesture.scss.tcd.ie/. Trinity College Dublin require interested parties to sign a license agreement and receive approval before gaining access the material, so we cannot host it here. We are looking to provide preprocessing guidelines and code in the near future.

Training

Edit the 'hparams/xxx.json' file to modify network and traning parameters. Start training by running the following command:

python train_moglow.py <hparams> <dataset>

Example 1. For locomotion synthesis:

python train_moglow.py 'hparams/locomotion.json' locomotion

Example 2. For gesture synthesis:

python train_moglow.py 'hparams/style_gestures.json' trinity

Inference

Output samples are generated at specified intervals during training. Inference from a pre-trained model is done by specifying the path in the 'hparams/xxx.json' file and then running python train_moglow.py <hparams> <dataset>.

References

@article{henter2019moglow,
  title={{M}o{G}low: {P}robabilistic and controllable motion synthesis using normalising flows},
  author={Henter, Gustav Eje and Alexanderson, Simon and Beskow, Jonas},
  journal={arXiv preprint arXiv:1905.06598},
  year={2019}
}

@article{alexanderson2020style,
  title={Style-controllable speech-driven gesture synthesis using normalising flows},
  author={Alexanderson, Simon and Henter, Gustav Eje and Kucherenko, Taras and Beskow, Jonas},
  journal={Computer Graphics Forum},
  volume={39},
  number={2},
  pages={487--496},
  year={2020},
  url={https://diglib.eg.org/handle/10.1111/cgf13946},
  publisher={John Wiley & Sons}
}