# FLAME: Articulated Expressive 3D Head Model (PyTorch)
This is an implementation of the [FLAME](http://flame.is.tue.mpg.de/) 3D head model in PyTorch.
We also provide [Tensorflow FLAME](https://github.com/TimoBolkart/TF_FLAME), a [Chumpy](https://github.com/mattloper/chumpy)-based [FLAME-fitting repository](https://github.com/Rubikplayer/flame-fitting), and code to [convert from Basel Face Model to FLAME](https://github.com/TimoBolkart/BFM_to_FLAME).
<p align="center">
<img src="gifs/model_variations.gif">
</p>
FLAME is a lightweight and expressive generic head model learned from over 33,000 of accurately aligned 3D scans. FLAME combines a linear identity shape space (trained from head scans of 3800 subjects) with an articulated neck, jaw, and eyeballs, pose-dependent corrective blendshapes, and additional global expression blendshapes. For details please see the following [scientific publication](https://ps.is.tuebingen.mpg.de/uploads_file/attachment/attachment/400/paper.pdf)
```bibtex
Learning a model of facial shape and expression from 4D scans
Tianye Li*, Timo Bolkart*, Michael J. Black, Hao Li, and Javier Romero
ACM Transactions on Graphics (Proc. SIGGRAPH Asia) 2017
```
and the [supplementary video](https://youtu.be/36rPTkhiJTM).
## Installation
The code uses **Python 3.7** and it is tested on PyTorch 1.4.
### Setup FLAME PyTorch Virtual Environment
```shell
python3.7 -m venv <your_home_dir>/.virtualenvs/FLAME_PyTorch
source <your_home_dir>/.virtualenvs/FLAME_PyTorch/bin/activate
```
### Clone the project and install requirements
```shell
git clone https://github.com/soubhiksanyal/FLAME_PyTorch
cd FLAME_PyTorch
python setup.py install
mkdir model
```
## Download models
* Download FLAME model from [here](http://flame.is.tue.mpg.de/). You need to sign up and agree to the model license for access to the model. Copy the downloaded model inside the **model** folder.
* Download Landmark embedings from [RingNet Project](https://github.com/soubhiksanyal/RingNet/tree/master/flame_model). Copy it inside the **model** folder.
## Demo
### Loading FLAME and visualising the 3D landmarks on the face
Please note we used the pose dependent conture for the face as introduced by [RingNet Project](https://github.com/soubhiksanyal/RingNet/tree/master/flame_model).
Run the following command from the terminal
```shell
python main.py
```
## License
FLAME is available under [Creative Commons Attribution license](https://creativecommons.org/licenses/by/4.0/). By using the model or the code code, you acknowledge that you have read the license terms (https://flame.is.tue.mpg.de/modellicense.html), understand them, and agree to be bound by them. If you do not agree with these terms and conditions, you must not use the code.
## Referencing FLAME
When using this code in a scientific publication, please cite
```bibtex
@article{FLAME:SiggraphAsia2017,
title = {Learning a model of facial shape and expression from {4D} scans},
author = {Li, Tianye and Bolkart, Timo and Black, Michael. J. and Li, Hao and Romero, Javier},
journal = {ACM Transactions on Graphics, (Proc. SIGGRAPH Asia)},
volume = {36},
number = {6},
year = {2017},
url = {https://doi.org/10.1145/3130800.3130813}
}
```
Additionally if you use the pose dependent dynamic landmarks from this codebase, please cite
```bibtex
@inproceedings{RingNet:CVPR:2019,
title = {Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision},
author = {Sanyal, Soubhik and Bolkart, Timo and Feng, Haiwen and Black, Michael},
booktitle = {Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)},
month = jun,
year = {2019},
month_numeric = {6}
}
```
## Supported Projects
FLAME supports several projects such as
* [CoMA: Convolutional Mesh Autoencoders](https://github.com/anuragranj/coma)
* [RingNet: 3D Face Shape and Expression Reconstruction from an Image without 3D Supervision](https://github.com/soubhiksanyal/RingNet)
* [VOCA: Voice Operated Character Animation](https://github.com/TimoBolkart/voca)
* [Expressive Body Capture: 3D Hands, Face, and Body from a Single Image](https://github.com/vchoutas/smplify-x)
* [ExPose: Monocular Expressive Body Regression through Body-Driven Attention](https://github.com/vchoutas/expose)
* [GIF: Generative Interpretable Faces](https://github.com/ParthaEth/GIF)
* [DECA: Detailed Expression Capture and Animation](https://github.com/YadiraF/DECA)
FLAME is part of [SMPL-X: : A new joint 3D model of the human body, face and hands together](https://github.com/vchoutas/smplx)
## Contact
If you have any questions regarding the PyTorch implementation then you can contact us at soubhik.sanyal@tuebingen.mpg.de and timo.bolkart@tuebingen.mpg.de.
## Acknowledgements
This repository is build with modifications from [SMPLX](https://github.com/vchoutas/smplx).
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"description": "# FLAME: Articulated Expressive 3D Head Model (PyTorch)\n\nThis is an implementation of the [FLAME](http://flame.is.tue.mpg.de/) 3D head model in PyTorch.\n\nWe also provide [Tensorflow FLAME](https://github.com/TimoBolkart/TF_FLAME), a [Chumpy](https://github.com/mattloper/chumpy)-based [FLAME-fitting repository](https://github.com/Rubikplayer/flame-fitting), and code to [convert from Basel Face Model to FLAME](https://github.com/TimoBolkart/BFM_to_FLAME).\n\n<p align=\"center\"> \n<img src=\"gifs/model_variations.gif\">\n</p>\n\nFLAME is a lightweight and expressive generic head model learned from over 33,000 of accurately aligned 3D scans. FLAME combines a linear identity shape space (trained from head scans of 3800 subjects) with an articulated neck, jaw, and eyeballs, pose-dependent corrective blendshapes, and additional global expression blendshapes. 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You need to sign up and agree to the model license for access to the model. Copy the downloaded model inside the **model** folder. \n* Download Landmark embedings from [RingNet Project](https://github.com/soubhiksanyal/RingNet/tree/master/flame_model). Copy it inside the **model** folder. \n\n## Demo\n\n### Loading FLAME and visualising the 3D landmarks on the face\n\nPlease note we used the pose dependent conture for the face as introduced by [RingNet Project](https://github.com/soubhiksanyal/RingNet/tree/master/flame_model).\n\nRun the following command from the terminal\n\n```shell\npython main.py\n```\n\n## License\n\nFLAME is available under [Creative Commons Attribution license](https://creativecommons.org/licenses/by/4.0/). By using the model or the code code, you acknowledge that you have read the license terms (https://flame.is.tue.mpg.de/modellicense.html), understand them, and agree to be bound by them. 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