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# FExGAN-Meta: Facial Expression Generation with Meta-Humans |
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![FExGAN-Meta GIF Demo](https://github.com/azadlab/FExGAN-Meta/blob/master/FExGAN-Meta.gif?raw=true) |
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This is the demo of the FExGAN-Meta proposed in the following article: |
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[FExGAN-Meta: Facial Expression Generation with Meta-Humans](https://www.arxiv.com) |
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FExGAN-Meta is the extension of [FExGAN](http://arxiv.org/abs/2201.09061). It takes input an image of Meta-Human and a vector of desired affect (e.g. angry,disgust,sad,surprise,joy,neutral and fear) and converts the input image to the desired emotion while keeping the identity of the original image. |
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![FExGAN-Meta GIF Demo](https://github.com/azadlab/FExGAN-Meta/blob/master/results.png?raw=true) |
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# Requirements |
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In order to run this you need following: |
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* Python >= 3.7 |
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* Tensorflow >= 2.6 |
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* CUDA enabled GPU with memory >=8GB (e.g. GTX1070/GTX1080) |
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# Usage |
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You can either run this on google colab or run it on your local system |
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* Install the pre-requisites |
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* Download the models (if any link fails in the notebook due to google drive restriction, try downloading them manually) |
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* Execute the rest of the notebook |
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# Citation |
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If you use any part of this code or use ideas mentioned in the paper, please cite the following article. |
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``` |
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@article{Siddiqui_FExGAN-Meta_2022, |
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author = {{Siddiqui}, J. Rafid}, |
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title = {{FExGAN-Meta: Facial Expression Generation with Meta-Humans}}, |
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journal = {ArXiv e-prints}, |
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archivePrefix = "arXiv", |
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keywords = {Deep Learning, GAN, Facial Expressions}, |
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year = {2022} |
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url = {http://arxiv.org/abs/2201.09061}, |
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} |
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``` |
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