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I M Avatar: Implicit Morphable Head Avatars from Videos

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<img src="assets/imavatar_real.gif" width="400" height="200"/> <img src="assets/makehuman.gif" width="400" height="200"/>

Official Repository for CVPR 2022 oral paper I M Avatar: Implicit Morphable Head Avatars from Videos.

Getting Started

Preparing dataset

Download a preprocessed dataset from the ETH Zurich server (subject1 and subject2). You can run download_data.bash.

Or prepare your own dataset following intructions in ./preprocess/README.md.

Link the dataset folder to ./data/datasets. Link the experiment output folder to ./data/experiments.

Training

python scripts/exp_runner.py --conf ./confs/IMavatar_supervised.conf [--wandb_workspace IMavatar] [--is_continue]

Evaluation

Set the is_eval flag for evaluation, optionally set checkpoint (if not, the latest checkpoint will be used) and load_path

python scripts/exp_runner.py --conf ./confs/IMavatar_supervised.conf --is_eval [--checkpoint 60] [--load_path ...]

Pre-trained model

Download a pretrained model from the ETH Zurich server (subject1, subject2). See download_data.bash.

Additional features

The following features are not used in the main paper, but helpful for training.

Warning

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Acknowledgement

Yufeng Zheng and Xu Chen were supported by the Max Planck ETH Center for Learning Systems. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program grant agreement No 717054. This work was partly supported by the German Federal Ministry of Education and Research (BMBF): Tuebingen AI Center, FKZ: 01IS18039B. MJB has received research gift funds from Adobe, Intel, Nvidia, Meta/Facebook, and Amazon. MJB has financial interests in Amazon, Datagen Technologies, and Meshcapade GmbH. While MJB is a consultant for Meshcapade, his research in this project was performed solely at, and funded solely by, the Max Planck Society.

Citation

If you find our code or paper useful, please cite as:

@inproceedings{zheng2022imavatar,
  title={{I} {M} {Avatar}: Implicit Morphable Head Avatars from Videos},
  author={Zheng, Yufeng and Abrevaya, Victoria Fernández and Bühler, Marcel C. and Chen, Xu and Black, Michael J. and Hilliges, Otmar},
  booktitle = {Computer Vision and Pattern Recognition (CVPR)},
  year = {2022}
}