readme: ---
  language: en
  tags:
  - Computer Vision
  - Machine Learning
  - Deep Learning
  ---
  
  # FExGAN-Meta: Facial Expression Generation with Meta-Humans
  
  ![FExGAN-Meta GIF Demo](https://github.com/azadlab/FExGAN-Meta/blob/master/FExGAN-Meta.gif?raw=true)
  
  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.
  
  ![FExGAN-Meta GIF Demo](https://github.com/azadlab/FExGAN-Meta/blob/master/results.png?raw=true)
  
  # 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},
  }
  
  ```
  