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| language: en | |
| tags: | |
| - Computer Vision | |
| - Machine Learning | |
| - Deep Learning | |
| # FExGAN-Meta: Facial Expression Generation with Meta-Humans | |
|  | |
| This is the demo of the FExGAN-Meta proposed in the following article: | |
| [FExGAN-Meta: Facial Expression Generation with Meta-Humans](https://www.arxiv.com) | |
| 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. | |
|  | |
| # Requirements | |
| In order to run this you need following: | |
| * Python >= 3.7 | |
| * Tensorflow >= 2.6 | |
| * CUDA enabled GPU with memory >=8GB (e.g. GTX1070/GTX1080) | |
| # Usage Code | |
| https://www.github.com/azadlab/FExGAN-Meta | |
| # Citation | |
| If you use any part of this code or use ideas mentioned in the paper, please cite the following article. | |
| ``` | |
| @article{Siddiqui_FExGAN-Meta_2022, | |
| author = {{Siddiqui}, J. Rafid}, | |
| title = {{FExGAN-Meta: Facial Expression Generation with Meta-Humans}}, | |
| journal = {ArXiv e-prints}, | |
| archivePrefix = "arXiv", | |
| keywords = {Deep Learning, GAN, Facial Expressions}, | |
| year = {2022} | |
| url = {http://arxiv.org/abs/2201.09061}, | |
| } | |
| ``` | |