几个重要的GAN及论文
 1.C-GAN 条件GAN 2014 CGAN 《Conditional Generative Adversarial Nets》- Mehdi Mirza, arXiv:1411.1784v1

 论文 https://arxiv.org/pdf/1411.1784.pdf

 
 2.DCGAN 深度卷积对抗生成网络

 2015 DCGAN《Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks》

  Alec Radford & Luke Metz, arxiv:1511.06434

 
 3.Semi-Supervised 半监督GAN

 2016 Semi-Supervised Learning with Generative Adversarial Networks
 https://arxiv.org/abs/1606.01583

 
 4.InfoGAN

 2016 InfoGAN《InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial NetsI》

  Xi Chen, arxiv: 1606.03657

 
 5.W GAN

 2017 WGAN 《Wasserstein GAN》- Martin Arjovsky ,arXiv:1701.07875v1

 
 6.BEGAN：边界平衡生成对抗网络

 2017 BEGAN BoundaryEquilibriumGenerative AdversarialNetworks

 https://arxiv.org/pdf/1703.10717.pdf

 
 TP GAN TWO pathway Geanerator Network

 2017 Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis

 Huang_Beyond_Face_Rotation_ICCV_2017_paper.pdf

 
 7.MSG-GAN (Multi-Scale Gradients GAN) 度尺度GAN

 2019 MSG-GAN: Multi-Scale Gradient GAN for Stable Image Synthesis

 https://arxiv.org/abs/1903.06048


原文链接：https://blog.csdn.net/hemro/article/details/99682387