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