articleIEEE AccessJan 1, 2019GOLD OA

Recent Progress on Generative Adversarial Networks (GANs): A Survey

ZPZhaoqing PanWYWeijie YuXYXiaokai YiAKAsifullah KhanFYFeng Yuan

Nanjing University of Information Science and Technology · Pakistan Institute of Engineering and Applied Sciences

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Abstract

Generative adversarial network (GANs) is one of the most important research avenues in the field of artificial intelligence, and its outstanding data generation capacity has received wide attention. In this paper, we present the recent progress on GANs. First, the basic theory of GANs and the differences among different generative models in recent years were analyzed and summarized. Then, the derived models of GANs are classified and introduced one by one. Third, the training tricks and evaluation metrics were given. Fourth, the applications of GANs were introduced. Finally, the problem, we need to address, and future directions were discussed.

Citation impact

675
total citations
FWCI
32.66
Percentile
100%
References
123
Citations per year

Authors

6

Topics & keywords

Topics
Keywords
  • Generative grammar
  • Computer science
  • Adversarial system
  • Artificial intelligence
  • Field (mathematics)
  • Generative adversarial network
  • Machine learning
  • Data science
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