Corpus ID: 6144520

Generate Identity-Preserving Faces by Generative Adversarial Networks

@article{Li2017GenerateIF,
  title={Generate Identity-Preserving Faces by Generative Adversarial Networks},
  author={Z. Li and Y. Luo},
  journal={ArXiv},
  year={2017},
  volume={abs/1706.03227}
}

Z. Li, Y. Luo

Published 2017

Computer Science

ArXiv

Generating identity-preserving faces aims to generate various face images keeping the same identity given a target face image. Although considerable generative models have been developed in recent years, it is still challenging to simultaneously acquire high quality of facial images and preserve the identity. Here we propose a compelling method using generative adversarial networks (GAN). Concretely, we leverage the generator of trained GAN to generate plausible faces and FaceNet as an identity… CONTINUE READING

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