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metadata
language: en
tags:
  - Computer Vision
  - Machine Learning
  - Deep Learning

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

FExGAN GIF Demo

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

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

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.

FExGAN GIF Demo

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},
}