A survey of image synthesis and editing with generative adversarial networks

Xian Wu, Kun Xu, Peter Hall

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

This paper presents a survey of image synthesis and editing with Generative Adversarial Networks (GANs). GANs consist of two deep networks, a generator and a discriminator, which are trained in a competitive way. Due to the power of deep networks and the competitive training manner, GANs are capable of producing reasonable and realistic images, and have shown great capability in many image synthesis and editing applications. This paper surveys recent GAN papers regarding topics including, but not limited to, texture synthesis, image inpainting, image-to-image translation, and image editing.

Original languageEnglish
Article number8195348
Pages (from-to)660-674
Number of pages15
JournalTsinghua Science and Technology
Volume22
Issue number6
DOIs
Publication statusPublished - 1 Dec 2017

Keywords

  • constrained image synthesis
  • generative adversarial networks
  • image editing
  • image synthesis
  • image-to-image translation

ASJC Scopus subject areas

  • General

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