Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network
This is the official 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.
In order to run this you need following:
- Python >= 3.7
- Tensorflow >= 2.6
- CUDA enabled GPU (e.g. GTX1070/GTX1080)
You can either run this on google colab or run it on your local system
- Install the pre-requisites
- Download the models (if any link fails in the notebook due to google drive restriction, try downloading them manually)
- Execute the rest of the notebook
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:2201.09061},
keywords = {Deep Learning, GAN, Facial Expressions},
year = {2022},
url = {http://arxiv.org/abs/2201.09061},
}