Skip to search formSkip to main content
You are currently offline. Some features of the site may not work correctly.

Generative adversarial networks

Generative adversarial networks are a neural network framework where a generative model is estimated via an adversarial process. Initially developed… Expand
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2019
Review
2019
Deep convolutional neural networks have performed remarkably well on many Computer Vision tasks. However, these networks are… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • table 1
Is this relevant?
Review
2019
Review
2019
Generative adversarial networks (GANs) have been extensively studied in the past few years. Arguably the revolutionary techniques… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 6
Is this relevant?
Review
2019
Review
2019
This survey paper describes a literature review of deep learning (DL) methods for cyber security applications. A short tutorial… Expand
  • figure 2
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
Review
2019
Review
2019
Generative adversarial network (GANs) is one of the most important research avenues in the field of artificial intelligence, and… Expand
  • figure 1
  • figure 2
  • table 1
  • figure 3
  • figure 4
Is this relevant?
Review
2019
Review
2019
The appearance of generative adversarial networks (GAN) provides a new approach and framework for computer vision. Compared with… Expand
  • table 1
  • figure 1
  • figure 2
  • figure 3
  • figure 4
Is this relevant?
Review
2019
Review
2019
Deep learning, which is especially formidable in handling big data, has achieved great success in various fields, including… Expand
Is this relevant?
Review
2017
Review
2017
This paper presents a survey of image synthesis and editing with Generative Adversarial Networks (GANs). GANs consist of two deep… Expand
  • figure 2
  • figure 3
  • figure 4
  • figure 5
  • figure 6
Is this relevant?
Highly Cited
2017
Highly Cited
2017
We introduce a new algorithm named WGAN, an alternative to traditional GAN training. In this new model, we show that we can… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
Highly Cited
2016
Highly Cited
2016
In recent years, supervised learning with convolutional networks (CNNs) has seen huge adoption in computer vision applications… Expand
  • figure 1
  • figure 2
  • figure 3
  • table 1
  • figure 4
Is this relevant?
Highly Cited
2014
Highly Cited
2014
For many AI projects, deep learning techniques are increasingly being used as the building blocks for innovative solutions… Expand
  • figure 1
  • table 1
  • figure 2
  • figure 3
Is this relevant?