  We propose a generative framework based on generative adversarial network
(GAN) to enhance facial attractiveness while preserving facial identity and
high-fidelity. Given a portrait image as input, having applied gradient descent
to recover a latent vector that this generative framework can use to synthesize
an image resemble to the input image, beauty semantic editing manipulation on
the corresponding recovered latent vector based on InterFaceGAN enables this
framework to achieve facial image beautification. This paper compared our
system with Beholder-GAN and our proposed result-enhanced version of
Beholder-GAN. It turns out that our framework obtained state-of-art
attractiveness enhancement results. The code is available at
https://github.com/zoezhou1999/BeautifyBasedOnGAN.
