Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network

This is the implementation of the FExGAN proposed in the following article:

FExGAN takes input an image 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 (e.g. GTX1070/GTX1080)

Usage Code

https://www.github.com/azadlab/FExGAN

Citation

If you use any part of this code or use ideas mentioned in the paper, please cite the following article.

@article{Siddiqui_FExGAN_2022,
  author = {{Siddiqui}, J. Rafid},
  title = {{Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network}},
  journal = {ArXiv e-prints},
  archivePrefix = "arXiv",
  keywords = {Deep Learning, GAN, Facial Expressions},
  year = {2022}
  url = {http://arxiv.org/abs/2201.09061},
}