GAN生成对抗网络发展史-文章整理

2014 GAN 《Generative Adversarial Networks》-Ian Goodfellow, arXiv:1406.2661v1
2014 CGAN 《Conditional Generative Adversarial Nets》- Mehdi Mirza, arXiv:1411.1784v1
2015 LAPGAN 《Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks》- Emily Denton & Soumith Chintala, arxiv: 1506.05751
2015 SRGAN《super-resolution generative adversarial network》- Joan Bruna, Pablo Sprechmann, Yann LeCun , arXiv:1511.05666
2015《Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks》- Jost Tobias Springenberg ,arXiv:1511.06390
2015 DCGAN《Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks》 - Alec Radford & Luke Metz, arxiv:1511.06434
2015 VAEGAN 《Autoencoding beyond pixels using a learned similarity metric》 - Anders Boesen Lindbo Larsen, arxiv: 1512.09300
2016《Generating Images with Recurrent Adversarial Networks》- Daniel Jiwoong Im, Chris Dongjoo Kim ,arXiv:1602.05110
2016《Generative Adversarial Text to Image Synthesis》（“GANs 文字到图像的合成”）- Scott Reed ，arXiv:1605.05396
2016 InfoGAN《InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial NetsI》- Xi Chen, arxiv: 1606.03657
2016 COGAN《Coupled Generative Adversarial Networks》Ming-Yu Liu, Oncel Tuzel - arXiv:1606.07536
2016 EBGAN《Energy-based Generative Adversarial Network》- Junbo Zhao ， arXiv:1609.03126v2
2016 《Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network》 - Christian Ledig, Lucas Theis , arXiv:1609.04802
2016 SeqGAN《SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient》- Lantao Yu, arxiv: 1609.05473
2016《 Contextual RNN-GANs for Abstract Reasoning Diagram Generation》 - Arnab Ghosh, Viveka Kulharia ,arXiv:1609.09444
2016《Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling》- Jiajun Wu, Chengkai Zhang ,arXiv:1610.07584
2016 TGAN《Temporal Generative Adversarial Nets》- Masaki Saito, Eiichi Matsumoto，arXiv:1611.06624
2016 SAD-GAN《SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networks》- Arna Ghosh, Biswarup Bhattacharya, Somnath Basu Roy Chowdhury ，arXiv:1611.08788
2016 PPGAN 《Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space》 - Anh Nguyen , arXiv:1612.00005v1
2016 《StackGAN:Text to Photo realistic Image Synthesis with Stacked Generative Adversarial Network》- Han Zhang,arXiv:1612.03242
2017 《NIPS 2016 Tutorial: Generative Adversarial Networks 》- Ian Goodfellow , arXiv:1701.00160
2017 LS-GAN《 Loss-Sensitive Generative Adversarial Networks onLipschitz Densities》- Guo-Jun Qi ，arXiv:1701.06264
2017 WGAN 《Wasserstein GAN》- Martin Arjovsky ,arXiv:1701.07875v1
2017《Maximum-Likelihood Augmented Discrete Generative Adversarial Networks》-Tong Che, Yanran Li, Ruixiang Zhang, R Devon Hjelm, Wenjie Li, Yangqiu Song, Yoshua Bengio，arXiv:1702.07983v1
2017《Boundary-Seeking Generative Adversarial Networks》- R Devon Hjelm, Athul Paul Jacob, Tong Che, Kyunghyun Cho, Yoshua Bengio ,arXiv:1702.08431
2017《Mode Regularized Generative Adversarial Networks》- Tong Che, Yanran Li, Athul Paul Jacob, Yoshua Bengio, Wenjie Li， ICLR 2017

2017《 Adversarial examples for generative models》- Jernej Kos, Ian Fischer, Dawn Song ， arXiv:1702.06832
2017《 Learning to Draw Dynamic Agent Goals with Generative Adversarial Networks》- Shariq Iqbal, John Pearson ，arXiv:1702.07319
2017 《WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images》- Jie Li, Katherine A. Skinner, Ryan M. Eustice, Matthew Johnson-Roberson ，arXiv:1702.07392
2017《Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning》- Briland Hitaj, Giuseppe Ateniese, Fernando Perez-Cruz ，arXiv:1702.07464
2017 《Generative Adversarial Active Learning》- Jia-Jie Zhu, José Bento ，arXiv:1702.07956
2017 《Maximum-Likelihood Augmented Discrete Generative Adversarial Networks》
- Tong Che, Yanran Li, Ruixiang Zhang, R Devon Hjelm, Wenjie Li, Yangqiu Song, Yoshua Bengio ， arXiv:1702.07983
2017 《 Adversarial Networks for the Detection of Aggressive Prostate Cancer》-
Simon Kohl, David Bonekamp, arXiv:1702.08014
2017《McGan: Mean and Covariance Feature Matching GAN》- Youssef Mroueh, Tom Sercu, Vaibhava Goel ，arXiv:1702.08398
2017 《 Age Progression/Regression by Conditional Adversarial Autoencoder》-
Zhifei Zhang, Yang Song, Hairong Qi ，arXiv:1702.08423
2017 《ste-GAN-ography: Generating Steganographic Images via Adversarial Training 》- Jamie Hayes, George Danezis， arXiv:1703.00371
2017 《Generalization and Equilibrium in Generative Adversarial Nets (GANs) 》- Sanjeev Arora, Rong Ge, Yingyu Liang, Tengyu Ma, Yi Zhang， arXiv:1703.00573