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https://github.com/ChanChiChoi/awesome-GAN-papers
papers and codes about GAN
https://github.com/ChanChiChoi/awesome-GAN-papers
List: awesome-GAN-papers
gan generative-adversarial-networks
Last synced: 1 day ago
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papers and codes about GAN
- Host: GitHub
- URL: https://github.com/ChanChiChoi/awesome-GAN-papers
- Owner: ChanChiChoi
- Created: 2018-12-26T07:16:51.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2019-04-03T06:07:23.000Z (over 5 years ago)
- Last Synced: 2024-05-21T08:33:51.509Z (6 months ago)
- Topics: gan, generative-adversarial-networks
- Homepage:
- Size: 3.2 MB
- Stars: 61
- Watchers: 8
- Forks: 10
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-of-awesome-ml - awesome-GAN-papers (by ChanChiChoi)
- ultimate-awesome - awesome-GAN-papers - Papers and codes about GAN. (Other Lists / PowerShell Lists)
README
# awesome-GAN-papers
this collecting the papers (main from arxiv.org) about Generative Adversarial Networks (GAN)
also, some papers and links collected from below, they are all awesome resources:
- [1] [nightrome/really-awesome-gan](https://github.com/nightrome/really-awesome-gan)
- [2] [zhangqianhui/AdversarialNetsPapers](https://github.com/zhangqianhui/AdversarialNetsPapers)
- [3] [dongb5/GAN-Timeline](https://github.com/dongb5/GAN-Timeline)
- [4] [hollobit/All-About-the-GAN](https://github.com/hollobit/All-About-the-GAN)
- [5] [LynnHo/GAN-Papers](https://github.com/LynnHo/GAN-Papers)
- [6] [shawnyuen/GANsPaperCollection](https://github.com/shawnyuen/GANsPaperCollection)
- [7] [hindupuravinash/the-gan-zoo](https://github.com/hindupuravinash/the-gan-zoo); [the-gan-zoo-4-tsv](https://github.com/hindupuravinash/the-gan-zoo/blob/master/gans.tsv)
- [8] [code][wiseodd/generative-models](https://github.com/wiseodd/generative-models)
- [9] [code][hwalsuklee/tensorflow-generative-model-collections](https://github.com/hwalsuklee/tensorflow-generative-model-collections)
- [10] [code][znxlwm/pytorch-generative-model-collections](https://github.com/znxlwm/pytorch-generative-model-collections)
- [11] [*code&paper][kozistr/Awesome-GANs](https://github.com/kozistr/Awesome-GANs)
- [12] [*code][eriklindernoren/Keras-GAN](https://github.com/eriklindernoren/Keras-GAN)
- [13] [savan77/The-GAN-World](https://github.com/savan77/The-GAN-World)
- [14] [nashory/gans-awesome-applications](https://github.com/nashory/gans-awesome-applications)
- [15] [code][nisace/gan-lib](https://github.com/nisace/gan-lib)
- [16] [code][sanghoon/tf-exercise-gan](https://github.com/sanghoon/tf-exercise-gan)
- [17] [xinario/awesome-gan-for-medical-imaging](https://github.com/xinario/awesome-gan-for-medical-imaging)
- [18] [code][nashory/gans-collection.torch](https://github.com/nashory/gans-collection.torch)
- [19] [code][YadiraF/GAN](https://github.com/YadiraF/GAN)
- [20] [code¬ebook][shayneobrien/generative-models](https://github.com/shayneobrien/generative-models)
- [21] [paper][lzhbrian/image-to-image-papers](https://github.com/lzhbrian/image-to-image-papers)
- [22] [code¬ebook][shayneobrien/generative-models](https://github.com/shayneobrien/generative-models)
- [23] [code][MingtaoGuo/\*GAN](https://github.com/MingtaoGuo/DCGAN_WGAN_WGAN-GP_LSGAN_SNGAN_RSGAN_RaSGAN_BEGAN_TensorFlow)---
### 2014
- 【GAN】Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio .[Generative Adversarial Networks](https://arxiv.org/pdf/1406.02661) .[J] arXiv preprint arXiv:1406.02661.
- 【CGAN】Mehdi Mirza, Simon Osindero .[Conditional Generative Adversarial Nets](https://arxiv.org/pdf/1411.01784) .[J] arXiv preprint arXiv:1411.01784.### 2015
- Malte Probst .[Generative Adversarial Networks in Estimation of Distribution Algorithms for Combinatorial Optimization](https://arxiv.org/pdf/1509.09235) .[J] arXiv preprint arXiv:1509.09235.
- 【Theory】Michael Mathieu et al. [Deep multi-scale video prediction beyond mean square error](https://arxiv.org/abs/1511.05440) .[J] arXiv preprint arXiv:1511.05440.
[code:[dyelax/Adversarial_Video_Generation](https://github.com/dyelax/Adversarial_Video_Generation)]
- 【AAE】Alireza Makhzani et al. [Adversarial Autoencoders](https://arxiv.org/abs/1511.05644).[J] arXiv preprint arXiv:1511.05644.
[code:
|[musyoku/adversarial-autoencoder&chainer](https://github.com/musyoku/adversarial-autoencoder)|;
|[fducau/AAE_pytorch](https://github.com/fducau/AAE_pytorch)|;
|[hwalsuklee/tensorflow-mnist-AAE](https://github.com/hwalsuklee/tensorflow-mnist-AAE)|;
|[gitmatti/AAE-tensorflow](https://github.com/gitmatti/AAE-tensorflow)|;
|[spoilt333/onco-aae&ipynb](https://github.com/spoilt333/onco-aae/blob/master/fpt_ae/aae.ipynb)|;
|[takat0m0/AAE](https://github.com/takat0m0/AAE)|;
|[bfarzin/pytorch_aae](https://github.com/bfarzin/pytorch_aae)|;
|[greentfrapp/keras-aae](https://github.com/greentfrapp/keras-aae)|;
|[alimirzaei/adverserial-autoencoder-keras](https://github.com/alimirzaei/adverserial-autoencoder-keras)|;
|[sjchoi86/deep-autoencoders&ipynb](https://github.com/sjchoi86/deep-autoencoders/blob/master/src/demo_aae.ipynb)|;
|[MINGUKKANG/Adversarial-AutoEncoder](https://github.com/MINGUKKANG/Adversarial-AutoEncoder)|;
|[LLipter/aae](https://github.com/LLipter/aae)|;
|[zduguid/aae](https://github.com/zduguid/aae)|;
|[davidath/aae](https://github.com/davidath/aae)|;
|[gdbmanu/git-aae-vae-gan&ipynb](https://github.com/gdbmanu/git-aae-vae-gan);|
|[Aanax/newbie_GAN](https://github.com/Aanax/newbie_GAN)|;
|[ykwon0407/variational_autoencoder](https://github.com/ykwon0407/variational_autoencoder)|
]
- Jost Tobias Springenberg .[Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks](https://arxiv.org/pdf/1511.06390) .[J] arXiv preprint arXiv:1511.06390.
- 【DCGAN】Alec Radford et al. [Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks](https://arxiv.org/abs/1511.06434).[J] arXiv preprint arXiv:1511.06434.
[code:[Newmu/dcgan_code](https://github.com/Newmu/dcgan_code);
[pytorch_dcgan](https://github.com/pytorch/examples/tree/master/dcgan);
[carpedm20/DCGAN-tensorflow](https://github.com/carpedm20/DCGAN-tensorflow);
[soumith/dcgan.torch](https://github.com/soumith/dcgan.torch);
[jacobgil/keras-dcgan](https://github.com/jacobgil/keras-dcgan)]### 2016
- Chuan Li, Michael Wand .[Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks](https://arxiv.org/pdf/1604.04382) .[J] arXiv preprint arXiv:1604.04382.
- Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee .[Generative Adversarial Text to Image Synthesis](https://arxiv.org/pdf/1605.05396) .[J] arXiv preprint arXiv:1605.05396.
- Sebastian Nowozin, Botond Cseke, Ryota Tomioka .[f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization](https://arxiv.org/pdf/1606.00709) .[J] arXiv preprint arXiv:1606.00709.
- Augustus Odena .[Semi-Supervised Learning with Generative Adversarial Networks](https://arxiv.org/pdf/1606.01583) .[J] arXiv preprint arXiv:1606.01583.
- Jonathan Ho, Stefano Ermon .[Generative Adversarial Imitation Learning](https://arxiv.org/pdf/1606.03476) .[J] arXiv preprint arXiv:1606.03476.
- 【Improved-GAN】Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen .[Improved Techniques for Training GANs](https://arxiv.org/pdf/1606.03498) .[J] arXiv preprint arXiv:1606.03498.
[code:
|[openai/improved-gan](https://github.com/openai/improved-gan)|;
|[Sleepychord/ImprovedGAN-pytorch](https://github.com/Sleepychord/ImprovedGAN-pytorch)|;
|[LDOUBLEV/semi-supervised-GAN](https://github.com/LDOUBLEV/semi-supervised-GAN)|;
|[musyoku/improved-gan](https://github.com/musyoku/improved-gan)|;
|[bruno-31/ImprovedGAN-Tensorflow](https://github.com/bruno-31/ImprovedGAN-Tensorflow)|;
|[eli5168/improved_gan_pytorch](https://github.com/eli5168/improved_gan_pytorch)|;
|[hvy/chainer-gan-improvements](https://github.com/hvy/chainer-gan-improvements)|;
|[hiroharu-kato/improved_gan_chainer](https://github.com/hiroharu-kato/improved_gan_chainer)|;
|[xjwang-cs/improved-gan-tf1.0.1](https://github.com/xjwang-cs/improved-gan-tf1.0.1)|; ]
- Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, Pieter Abbeel .[InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets](https://arxiv.org/pdf/1606.03657) .[J] arXiv preprint arXiv:1606.03657.
- Ming-Yu Liu, Oncel Tuzel .[Coupled Generative Adversarial Networks](https://arxiv.org/pdf/1606.07536) .[J] arXiv preprint arXiv:1606.07536.
- Hanock Kwak, Byoung-Tak Zhang .[Generating Images Part by Part with Composite Generative Adversarial Networks](https://arxiv.org/pdf/1607.05387) .[J] arXiv preprint arXiv:1607.05387.
- 【EBGAN】Junbo Zhao, Michael Mathieu, Yann LeCun .[Energy-based Generative Adversarial Network](https://arxiv.org/pdf/1609.03126) .[J] arXiv preprint arXiv:1609.03126.
[code:[buriburisuri/ebgan](https://github.com/buriburisuri/ebgan)]
- 【iGAN】Jun-Yan Zhu et al. [Generative Visual Manipulation on the Natural Image Manifold](https://arxiv.org/abs/1609.03552) .[J] arXiv preprint arXiv:1609.03126.
[code:
|[junyanz/iGAN](https://github.com/junyanz/iGAN)|:
|[kevinthesun/IGAN_MXNet](https://github.com/kevinthesun/IGAN_MXNet)|
]
- C. Ledig, L. Theis, F. Husz´ar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, et al. [Photo-realistic single image super-resolution using a generative adversarial network](https://arxiv.org/pdf/1609.04802). arXiv preprint arXiv:1609.04802, 2016.
- Lantao Yu, Weinan Zhang, Jun Wang, Yong Yu .[SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient](https://arxiv.org/pdf/1609.05473) .[J] arXiv preprint arXiv:1609.05473.
- Arnab Ghosh, Viveka Kulharia, Amitabha Mukerjee, Vinay Namboodiri, Mohit Bansal .[Contextual RNN-GANs for Abstract Reasoning Diagram Generation](https://arxiv.org/pdf/1609.09444) .[J] arXiv preprint arXiv:1609.09444.
- David Pfau, Oriol Vinyals .[Connecting Generative Adversarial Networks and Actor-Critic Methods](https://arxiv.org/pdf/1610.01945) .[J] arXiv preprint arXiv:1610.01945.
- Masatoshi Uehara, Issei Sato, Masahiro Suzuki, Kotaro Nakayama, Yutaka Matsuo .[Generative Adversarial Nets from a Density Ratio Estimation Perspective](https://arxiv.org/pdf/1610.02920) .[J] arXiv preprint arXiv:1610.02920.
- Augustus Odena, Christopher Olah, Jonathon Shlens .[Conditional Image Synthesis With Auxiliary Classifier GANs](https://arxiv.org/pdf/1610.09585) .[J] arXiv preprint arXiv:1610.09585.
- Leon Sixt, Benjamin Wild, Tim Landgraf .[RenderGAN: Generating Realistic Labeled Data](https://arxiv.org/pdf/1611.01331) .[J] arXiv preprint arXiv:1611.01331.
- Hanock Kwak, Byoung-Tak Zhang .[Ways of Conditioning Generative Adversarial Networks](https://arxiv.org/pdf/1611.01455) .[J] arXiv preprint arXiv:1611.01455.
- Dilin Wang, Qiang Liu .[Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning](https://arxiv.org/pdf/1611.01722) .[J] arXiv preprint arXiv:1611.01722.
- AuthorsJacob Andreas, Dan Klein, Sergey Levine .[Generative Adversarial Networks as Variational Training of Energy Based Models](https://arxiv.org/pdf/1611.01799) .[J] arXiv preprint arXiv:1611.01799.
- Authorseir Coupling to Gravity .[Generative Adversarial Networks as Variational Training of Energy Based Models](https://arxiv.org/pdf/1611.01799) .[J] arXiv preprint arXiv:1611.01799.
- Mickaël Chen, Ludovic Denoyer .[Multi-view Generative Adversarial Networks](https://arxiv.org/pdf/1611.02019) .[J] arXiv preprint arXiv:1611.02019.
- Luke Metz, Ben Poole, David Pfau, Jascha Sohl-Dickstein .[Unrolled Generative Adversarial Networks](https://arxiv.org/pdf/1611.02163) .[J] arXiv preprint arXiv:1611.02163.
- Chelsea Finn, Paul Christiano, Pieter Abbeel, Sergey Levine .[A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models](https://arxiv.org/pdf/1611.03852) .[J] arXiv preprint arXiv:1611.03852.
- Matt J. Kusner, José Miguel Hernández-Lobato .[GANS for Sequences of Discrete Elements with the Gumbel-softmax Distribution](https://arxiv.org/pdf/1611.04051) .[J] arXiv preprint arXiv:1611.04051.
- 【LSGANs】Xudong Mao, Qing Li, Haoran Xie, Raymond Y.K. Lau, Zhen Wang, Stephen Paul Smolley .[Least Squares Generative Adversarial Networks](https://arxiv.org/pdf/1611.04076) .[J] arXiv preprint arXiv:1611.04076.
[code:[wiseodd/generative-models](https://github.com/wiseodd/generative-models)]
- Antonia Creswell, Anil Anthony Bharath .[Inverting The Generator Of A Generative Adversarial Network](https://arxiv.org/pdf/1611.05644) .[J] arXiv preprint arXiv:1611.05644.
- Guim Perarnau, Joost van de Weijer, Bogdan Raducanu, Jose M. Álvarez .[Invertible Conditional GANs for image editing](https://arxiv.org/pdf/1611.06355) .[J] arXiv preprint arXiv:1611.06355.
- Emily Denton, Sam Gross, Rob Fergus .[Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks](https://arxiv.org/pdf/1611.06430) .[J] arXiv preprint arXiv:1611.06430.
- Masaki Saito, Eiichi Matsumoto, Shunta Saito .[Temporal Generative Adversarial Nets with Singular Value Clipping](https://arxiv.org/pdf/1611.06624) .[J] arXiv preprint arXiv:1611.06624.
- 【pix2pix】Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, Alexei A. Efros. [Image-to-Image Translation with Conditional Adversarial Networks](https://arxiv.org/pdf/1611.07004) .[J] arXiv preprint arXiv:1611.07004.
[code:[phillipi/pix2pix](https://github.com/phillipi/pix2pix);
[junyanz/pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix);
[phillipi.github.io/pix2pix](https://phillipi.github.io/pix2pix/)]
- Nikolay Jetchev, Urs Bergmann, Roland Vollgraf .[Texture Synthesis with Spatial Generative Adversarial Networks](https://arxiv.org/pdf/1611.08207) .[J] arXiv preprint arXiv:1611.08207.
- Arna Ghosh, Biswarup Bhattacharya, Somnath Basu Roy Chowdhury .[SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networks](https://arxiv.org/pdf/1611.08788) .[J] arXiv preprint arXiv:1611.08788.
- Arna Ghosh, Biswarup Bhattacharya, Somnath Basu Roy Chowdhury .[Handwriting Profiling using Generative Adversarial Networks](https://arxiv.org/pdf/1611.08789) .[J] arXiv preprint arXiv:1611.08789.
- Olof Mogren .[C-RNN-GAN: Continuous recurrent neural networks with adversarial training](https://arxiv.org/pdf/1611.09904) .[J] arXiv preprint arXiv:1611.09904.
- Yaxing Wang, Lichao Zhang, Joost van de Weijer .[Ensembles of Generative Adversarial Networks](https://arxiv.org/pdf/1612.00991) .[J] arXiv preprint arXiv:1612.00991.
- Arnab Ghosh, Viveka Kulharia, Vinay Namboodiri .[Message Passing Multi-Agent GANs](https://arxiv.org/pdf/1612.01294) .[J] arXiv preprint arXiv:1612.01294.
- Tong Che, Yanran Li, Athul Paul Jacob, Yoshua Bengio, Wenjie Li .[Mode Regularized Generative Adversarial Networks](https://arxiv.org/pdf/1612.02136) .[J] arXiv preprint arXiv:1612.02136.
- Ben Poole, Alexander A. Alemi, Jascha Sohl-Dickstein, Anelia Angelova .[Improved generator objectives for GANs](https://arxiv.org/pdf/1612.02780) .[J] arXiv preprint arXiv:1612.02780.
- Daniel Jiwoong Im, He Ma, Chris Dongjoo Kim, Graham Taylor .[Generative Adversarial Parallelization](https://arxiv.org/pdf/1612.04021) .[J] arXiv preprint arXiv:1612.04021.
- Xun Huang, Yixuan Li, Omid Poursaeed, John Hopcroft, Serge Belongie .[Stacked Generative Adversarial Networks](https://arxiv.org/pdf/1612.04357) .[J] arXiv preprint arXiv:1612.04357.
- Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan .[Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks](https://arxiv.org/pdf/1612.05424) .[J] arXiv preprint arXiv:1612.05424.
- Daoyu Lin, Kun Fu, Yang Wang, Guangluan Xu, Xian Sun .[MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification](https://arxiv.org/pdf/1612.08879) .[J] arXiv preprint arXiv:1612.08879.
- John Glover .[Modeling documents with Generative Adversarial Networks](https://arxiv.org/pdf/1612.09122) .[J] arXiv preprint arXiv:1612.09122.### 2017
- Ian Goodfellow .[NIPS 2016 Tutorial: Generative Adversarial Networks](https://arxiv.org/pdf/1701.00160) .[J] arXiv preprint arXiv:1701.00160.
- Junting Pan, Cristian Canton Ferrer, Kevin McGuinness, Noel E. O'Connor, Jordi Torres, Elisa Sayrol, Xavier Giro-i-Nieto .[SalGAN: Visual Saliency Prediction with Generative Adversarial Networks](https://arxiv.org/pdf/1701.01081) .[J] arXiv preprint arXiv:1701.01081.
- 【AdaGAN】Ilya Tolstikhin, Sylvain Gelly, Olivier Bousquet, Carl-Johann Simon-Gabriel, Bernhard Schölkopf .[AdaGAN: Boosting Generative Models](https://arxiv.org/pdf/1701.02386) .[J] arXiv preprint arXiv:1701.02386.
[code:
|[tolstikhin/adagan](https://github.com/tolstikhin/adagan)|: ]
- Hao Dong, Paarth Neekhara, Chao Wu, Yike Guo .[Unsupervised Image-to-Image Translation with Generative Adversarial Networks](https://arxiv.org/pdf/1701.02676) .[J] arXiv preprint arXiv:1701.02676.
- Mahesh Gorijala, Ambedkar Dukkipati .[Image Generation and Editing with Variational Info Generative AdversarialNetworks](https://arxiv.org/pdf/1701.04568) .[J] arXiv preprint arXiv:1701.04568.
- Lars Mescheder, Sebastian Nowozin, Andreas Geiger .[Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks](https://arxiv.org/pdf/1701.04722) .[J] arXiv preprint arXiv:1701.04722.
- 【Pre-WGAN】Martin Arjovsky, Léon Bottou .[Towards Principled Methods for Training Generative Adversarial Networks](https://arxiv.org/pdf/1701.04862) .[J] arXiv preprint arXiv:1701.04862.
- Luke de Oliveira, Michela Paganini, Benjamin Nachman .[Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis](https://arxiv.org/pdf/1701.05927) .[J] arXiv preprint arXiv:1701.05927.
- He Zhang, Vishwanath Sindagi, Vishal M. Patel .[Image De-raining Using a Conditional Generative Adversarial Network](https://arxiv.org/pdf/1701.05957) .[J] arXiv preprint arXiv:1701.05957.
- 【LS-GAN&GLS-GAN】Guo-Jun Qi .[Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities](https://arxiv.org/pdf/1701.06264) .[J] arXiv preprint arXiv:1701.06264.[code:[guojunq/lsgan](https://github.com/guojunq/lsgan)]
- Alex Kuefler, Jeremy Morton, Tim Wheeler, Mykel Kochenderfer .[Imitating Driver Behavior with Generative Adversarial Networks](https://arxiv.org/pdf/1701.06699) .[J] arXiv preprint arXiv:1701.06699.
- Zhedong Zheng, Liang Zheng, Yi Yang .[Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro](https://arxiv.org/pdf/1701.07717) .[J] arXiv preprint arXiv:1701.07717.
- 【WGAN】Martin Arjovsky, Soumith Chintala, Léon Bottou .[Wasserstein GAN](https://arxiv.org/pdf/1701.07875) .[J] arXiv preprint arXiv:1701.07875.
[code:
|[martinarjovsky/WassersteinGAN](https://github.com/martinarjovsky/WassersteinGAN)|;
|[Zardinality/WGAN-tensorflow](https://github.com/Zardinality/WGAN-tensorflow)|;
|[shekkizh/WassersteinGAN.tensorflow](https://github.com/shekkizh/WassersteinGAN.tensorflow)|;
|[musyoku/wasserstein-gan](https://github.com/musyoku/wasserstein-gan)|;
|[jiamings/wgan&wganV2](https://github.com/jiamings/wgan)|;
|[adler-j/minimal_wgan](https://github.com/adler-j/minimal_wgan)|;
|[fonfonx/WassersteinGAN.torch](https://github.com/fonfonx/WassersteinGAN.torch)|;
|[bobchennan/Wasserstein-GAN-Keras](https://github.com/bobchennan/Wasserstein-GAN-Keras)|;
|[mjdietzx/GAN-Sandbox](https://github.com/mjdietzx/GAN-Sandbox)|;
|[MustafaMustafa/WassersteinGAN-TensorFlow](https://github.com/MustafaMustafa/WassersteinGAN-TensorFlow)|;
|[hvy/chainer-wasserstein-gan](https://github.com/hvy/chainer-wasserstein-gan)|;
|[cameronfabbri/Wasserstein-GAN-Tensorflow](https://github.com/cameronfabbri/Wasserstein-GAN-Tensorflow)|;
|[EmilienDupont/wgan-gp](https://github.com/EmilienDupont/wgan-gp)|;
|[cedrickchee/wasserstein-gan](https://github.com/cedrickchee/wasserstein-gan)|;
|[Goldesel23/DCGAN-for-Bird-Generation](https://github.com/Goldesel23/DCGAN-for-Bird-Generation)|;
|[ChengBinJin/WGAN-TensorFlow](https://github.com/ChengBinJin/WGAN-TensorFlow)|;
|[shayneobrien/generative-models¬ebook](https://github.com/shayneobrien/generative-models)|;
|[KnetML/WGAN.jl&julia](https://github.com/KnetML/WGAN.jl)|;
|[germain-hug/GANs-Keras](https://github.com/germain-hug/GANs-Keras)|;
|[ConnorJL/WGAN-Tensorflow&slim](https://github.com/ConnorJL/WGAN-Tensorflow)|;
]
- Kevin Schawinski, Ce Zhang, Hantian Zhang, Lucas Fowler, Gokula Krishnan Santhanam .[Generative Adversarial Networks recover features in astrophysical images of galaxies beyond the deconvolution limit](https://arxiv.org/pdf/1702.00403) .[J] arXiv preprint arXiv:1702.00403.
- Zihang Dai, Amjad Almahairi, Philip Bachman, Eduard Hovy, Aaron Courville .[Calibrating Energy-based Generative Adversarial Networks](https://arxiv.org/pdf/1702.01691) .[J] arXiv preprint arXiv:1702.01691.
- Grigory Antipov, Moez Baccouche, Jean-Luc Dugelay .[Face Aging With Conditional Generative Adversarial Networks](https://arxiv.org/pdf/1702.01983) .[J] arXiv preprint arXiv:1702.01983.
- Wei Ren Tan, Chee Seng Chan, Hernan Aguirre, Kiyoshi Tanaka .[ArtGAN: Artwork Synthesis with Conditional Categorical GANs](https://arxiv.org/pdf/1702.03410) .[J] arXiv preprint arXiv:1702.03410.
- Chengde Wan, Thomas Probst, Luc Van Gool, Angela Yao .[Crossing Nets: Combining GANs and VAEs with a Shared Latent Space for Hand Pose Estimation](https://arxiv.org/pdf/1702.03431) .[J] arXiv preprint arXiv:1702.03431.
- Zachary C. Lipton, Subarna Tripathi .[Precise Recovery of Latent Vectors from Generative Adversarial Networks](https://arxiv.org/pdf/1702.04782) .[J] arXiv preprint arXiv:1702.04782.
- Weiwei Hu, Ying Tan .[Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN](https://arxiv.org/pdf/1702.05983) .[J] arXiv preprint arXiv:1702.05983.
- Yun Cao, Zhiming Zhou, Weinan Zhang, Yong Yu .[Unsupervised Diverse Colorization via Generative Adversarial Networks](https://arxiv.org/pdf/1702.06674) .[J] arXiv preprint arXiv:1702.06674.
- Muthuraman Chidambaram, Yanjun Qi .[Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently](https://arxiv.org/pdf/1702.06762) .[J] arXiv preprint arXiv:1702.06762.
- Jie Li, Katherine A. Skinner, Ryan M. Eustice, Matthew Johnson-Roberson .[WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images](https://arxiv.org/pdf/1702.07392) .[J] arXiv preprint arXiv:1702.07392.
- Briland Hitaj, Giuseppe Ateniese, Fernando Perez-Cruz .[Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning](https://arxiv.org/pdf/1702.07464) .[J] arXiv preprint arXiv:1702.07464.
- Jia-Jie Zhu, José Bento .[Generative Adversarial Active Learning](https://arxiv.org/pdf/1702.07956) .[J] arXiv preprint arXiv:1702.07956.
- Tong Che, Yanran Li, Ruixiang Zhang, R Devon Hjelm, Wenjie Li, Yangqiu Song, Yoshua Bengio .[Maximum-Likelihood Augmented Discrete Generative Adversarial Networks](https://arxiv.org/pdf/1702.07983) .[J] arXiv preprint arXiv:1702.07983.
- 【CAAE】Zhifei Zhang et al. [Age Progression/Regression by Conditional Adversarial Autoencoder](https://arxiv.org/abs/1702.08423) .[J] arXiv preprint arXiv:1702.08423.
[code:
|[zzutk.github.io/Face-Aging-CAAE](https://zzutk.github.io/Face-Aging-CAAE)|
|[Jooong/Face-Aging-CAAE-Pytorch](https://github.com/Jooong/Face-Aging-CAAE-Pytorch)|
|[wangxiao5791509/Age-Progression-Regression-by-CAAE](https://github.com/wangxiao5791509/Age-Progression-Regression-by-CAAE)|
|[hai046/Face-Aging-CAAE_pro](https://github.com/hai046/Face-Aging-CAAE_pro)|
|[SaltedSlark/CAAE.ipynb](https://github.com/SaltedSlark/CAAE/blob/master/CAAE.ipynb)|
]
- 【BS-GAN】R Devon Hjelm, Athul Paul Jacob, Tong Che, Adam Trischler, Kyunghyun Cho, Yoshua Bengio .[Boundary-Seeking Generative Adversarial Networks](https://arxiv.org/pdf/1702.08431) .[J] arXiv preprint arXiv:1702.08431.
[code:[wiseodd/generative-models](https://github.com/wiseodd/generative-models) [ekrim/bgan-t](https://github.com/ekrim/bgan-tf) [rdevon/BGAN](https://github.com/rdevon/BGAN) [DeepTensors/Boundary-Seeking-GAN](https://github.com/DeepTensors/Boundary-Seeking-GAN)
]
- Sanjeev Arora, Rong Ge, Yingyu Liang, Tengyu Ma, Yi Zhang .[Generalization and Equilibrium in Generative Adversarial Nets (GANs)](https://arxiv.org/pdf/1703.00573) .[J] arXiv preprint arXiv:1703.00573.
- Jianwei Yang, Anitha Kannan, Dhruv Batra, Devi Parikh .[LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation](https://arxiv.org/pdf/1703.01560) .[J] arXiv preprint arXiv:1703.01560.
- Zhiming Zhou, Han Cai, Shu Rong, Yuxuan Song, Kan Ren, Weinan Zhang, Yong Yu, Jun Wang .[Activation Maximization Generative Adversarial Nets](https://arxiv.org/pdf/1703.02000) .[J] arXiv preprint arXiv:1703.02000.
- Chongxuan Li, Kun Xu, Jun Zhu, Bo Zhang .[Triple Generative Adversarial Nets](https://arxiv.org/pdf/1703.02291) .[J] arXiv preprint arXiv:1703.02291.
- Samuel Albanie, Sébastien Ehrhardt, João F. Henriques .[Stopping GAN Violence: Generative Unadversarial Networks](https://arxiv.org/pdf/1703.02528) .[J] arXiv preprint arXiv:1703.02528.
- Zhen Yang, Wei Chen, Feng Wang, Bo Xu .[Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets](https://arxiv.org/pdf/1703.04887) .[J] arXiv preprint arXiv:1703.04887.
- Taeksoo Kim, Moonsu Cha, Hyunsoo Kim, Jung Kwon Lee, Jiwon Kim .[Learning to Discover Cross-Domain Relations with Generative Adversarial Networks](https://arxiv.org/pdf/1703.05192) .[J] arXiv preprint arXiv:1703.05192.
- Thomas Schlegl, Philipp Seeböck, Sebastian M. Waldstein, Ursula Schmidt-Erfurth, Georg Langs .[Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery](https://arxiv.org/pdf/1703.05921) .[J] arXiv preprint arXiv:1703.05921.
- Bo Dai, Sanja Fidler, Raquel Urtasun, Dahua Lin .[Towards Diverse and Natural Image Descriptions via a Conditional GAN](https://arxiv.org/pdf/1703.06029) .[J] arXiv preprint arXiv:1703.06029.
- Ayushman Dash, John Cristian Borges Gamboa, Sheraz Ahmed, Marcus Liwicki, Muhammad Zeshan Afzal .[TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network](https://arxiv.org/pdf/1703.06412) .[J] arXiv preprint arXiv:1703.06412.
- Edward Choi, Siddharth Biswal, Bradley Malin, Jon Duke, Walter F. Stewart, Jimeng Sun .[Generating Multi-label Discrete Patient Records using Generative Adversarial Networks](https://arxiv.org/pdf/1703.06490) .[J] arXiv preprint arXiv:1703.06490.
- Huikai Wu, Shuai Zheng, Junge Zhang, Kaiqi Huang .[GP-GAN: Towards Realistic High-Resolution Image Blending](https://arxiv.org/pdf/1703.07195) .[J] arXiv preprint arXiv:1703.07195.
- Akshay Mehrotra, Ambedkar Dukkipati .[Generative Adversarial Residual Pairwise Networks for One Shot Learning](https://arxiv.org/pdf/1703.08033) .[J] arXiv preprint arXiv:1703.08033.
- Santiago Pascual, Antonio Bonafonte, Joan Serrà .[SEGAN: Speech Enhancement Generative Adversarial Network](https://arxiv.org/pdf/1703.09452) .[J] arXiv preprint arXiv:1703.09452.
- Nasim Souly, Concetto Spampinato, Mubarak Shah .[Semi and Weakly Supervised Semantic Segmentation Using Generative Adversarial Network](https://arxiv.org/pdf/1703.09695) .[J] arXiv preprint arXiv:1703.09695.
- Junyu Luo, Yong Xu, Chenwei Tang, Jiancheng Lv .[Learning Inverse Mapping by Autoencoder based Generative Adversarial Nets](https://arxiv.org/pdf/1703.10094) .[J] arXiv preprint arXiv:1703.10094.
- Kiana Ehsani, Roozbeh Mottaghi, Ali Farhadi .[SeGAN: Segmenting and Generating the Invisible](https://arxiv.org/pdf/1703.10239) .[J] arXiv preprint arXiv:1703.10239.
- 【CycleGAN】Jun-Yan Zhu et al. [Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks](https://arxiv.org/abs/1703.10593).[J] arXiv preprint arXiv:1703.10593.
[code:[junyanz/CycleGAN](https://github.com/junyanz/CycleGAN);
[junyanz.github.io/CycleGAN](https://junyanz.github.io/CycleGAN/);
[junyanz/pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix)]
- 【BEGAN】David Berthelot, Thomas Schumm, Luke Metz .[BEGAN: Boundary Equilibrium Generative Adversarial Networks](https://arxiv.org/pdf/1703.10717) .[J] arXiv preprint arXiv:1703.10717.
[code;
|[wiseodd/generative-models](https://github.com/wiseodd/generative-models)|
|[rdevon/BGAN](https://github.com/rdevon/BGAN)|
|[ekrim/bgan-tf](https://github.com/ekrim/bgan-tf)|
|[carpedm20/BEGAN-tensorflow](https://github.com/carpedm20/BEGAN-tensorflow)|
|[artcg/BEGAN](https://github.com/artcg/BEGAN)|
|[Heumi/BEGAN-tensorflow](https://github.com/Heumi/BEGAN-tensorflow)|
|[carpedm20/BEGAN-pytorch](https://github.com/carpedm20/BEGAN-pytorch)|
|[taey16/pix2pixBEGAN.pytorch](https://github.com/taey16/pix2pixBEGAN.pytorch)|
|[mokemokechicken/keras_BEGAN](https://github.com/mokemokechicken/keras_BEGAN)|
|[YadiraF/GAN_Theorie&TOTAL](https://github.com/YadiraF/GAN_Theories)|
|[adepierre/Caffe_BEGAN](https://github.com/adepierre/Caffe_BEGAN)|
|[HiiYL/BEGAN-PyTorch](https://github.com/HiiYL/BEGAN-PyTorch)|
|[shayneobrien/generative-models](https://github.com/shayneobrien/generative-models)|
|[anantzoid/BEGAN-pytorch](https://github.com/anantzoid/BEGAN-pytorch)|
|[sanghoon/tf-exercise-gan](https://github.com/sanghoon/tf-exercise-gan)|
|[RuiShu/began](https://github.com/RuiShu/began)|
|[khanrc/tf.gans-comparison](https://github.com/khanrc/tf.gans-comparison)|
|[musyoku/began&chainer](https://github.com/musyoku/began)|
|[Overseer66/Tensorflow-GAN¬ebook](https://github.com/Overseer66/Tensorflow-GAN)|
|[HolyCaonima/BEGAN](https://github.com/HolyCaonima/BEGAN)|
|[hvy/chainer-began&chainer](https://github.com/hvy/chainer-began)|
|[2wins/BEGAN-cntk](https://github.com/2wins/BEGAN-cntk)|
|[2wins/BEGAN-tensorlayer](https://github.com/2wins/BEGAN-tensorlayer)|
|[1Konny/BEGAN-pytorch](https://github.com/1Konny/BEGAN-pytorch)|
|[nashory/BEGAN-torch7](https://github.com/nashory/BEGAN-torch7)|
]
- Li-Chia Yang, Szu-Yu Chou, Yi-Hsuan Yang .[MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation](https://arxiv.org/pdf/1703.10847) .[J] arXiv preprint arXiv:1703.10847.
- 【Improved-WGAN】Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, Aaron Courville .[Improved Training of Wasserstein GANs](https://arxiv.org/pdf/1704.00028) .[J] arXiv preprint arXiv:1704.00028.
- Chin-Cheng Hsu, Hsin-Te Hwang, Yi-Chiao Wu, Yu Tsao, Hsin-Min Wang .[Voice Conversion from Unaligned Corpora using Variational Autoencoding Wasserstein Generative Adversarial Networks](https://arxiv.org/pdf/1704.00849) .[J] arXiv preprint arXiv:1704.00849.
- Swami Sankaranarayanan, Yogesh Balaji, Carlos D. Castillo, Rama Chellappa .[Generate To Adapt: Aligning Domains using Generative Adversarial Networks](https://arxiv.org/pdf/1704.01705) .[J] arXiv preprint arXiv:1704.01705.
- Weidong Yin, Yanwei Fu, Leonid Sigal, Xiangyang Xue .[Semi-Latent GAN: Learning to generate and modify facial images from attributes](https://arxiv.org/pdf/1704.02166) .[J] arXiv preprint arXiv:1704.02166.
- Maciej Zieba, Lei Wang .[Training Triplet Networks with GAN](https://arxiv.org/pdf/1704.02227) .[J] arXiv preprint arXiv:1704.02227.
- Zili Yi, Hao Zhang, Ping Tan, Minglun Gong .[DualGAN: Unsupervised Dual Learning for Image-to-Image Translation](https://arxiv.org/pdf/1704.02510) .[J] arXiv preprint arXiv:1704.02510.
- Leonardo Galteri, Lorenzo Seidenari, Marco Bertini, Alberto Del Bimbo .[Deep Generative Adversarial Compression Artifact Removal](https://arxiv.org/pdf/1704.02518) .[J] arXiv preprint arXiv:1704.02518.
- Arnab Ghosh, Viveka Kulharia, Vinay Namboodiri, Philip H. S. Torr, Puneet K. Dokania .[Multi-Agent Diverse Generative Adversarial Networks](https://arxiv.org/pdf/1704.02906) .[J] arXiv preprint arXiv:1704.02906.
- Lukas Mosser, Olivier Dubrule, Martin J. Blunt .[Reconstruction of three-dimensional porous media using Generative Adversarial neural networks](https://arxiv.org/pdf/1704.03225) .[J] arXiv preprint arXiv:1704.03225.
- Ruohan Wang, Antoine Cully, Hyung Jin Chang, Yiannis Demiris .[MAGAN: Margin Adaptation for Generative Adversarial Networks](https://arxiv.org/pdf/1704.03817) .[J] arXiv preprint arXiv:1704.03817.
- Sitao Xiang, Hao Li .[On the Effects of Batch and Weight Normalization in Generative Adversarial Networks](https://arxiv.org/pdf/1704.03971) .[J] arXiv preprint arXiv:1704.03971.
- 【App】Rui Huang, Shu Zhang, Tianyu Li, Ran He .[Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis](https://arxiv.org/pdf/1704.04086) .[J] arXiv preprint arXiv:1704.04086.
- Min Lin .[Softmax GAN](https://arxiv.org/pdf/1704.06191) .[J] arXiv preprint arXiv:1704.06191.
- Yifan Liu, Zengchang Qin, Zhenbo Luo, Hua Wang .[Auto-painter: Cartoon Image Generation from Sketch by Using Conditional Generative Adversarial Networks](https://arxiv.org/pdf/1705.01908) .[J] arXiv preprint arXiv:1705.01908.
- Jonathan Chang, Stefan Scherer .[Learning Representations of Emotional Speech with Deep Convolutional Generative Adversarial Networks](https://arxiv.org/pdf/1705.02394) .[J] arXiv preprint arXiv:1705.02394.
- Zhimin Chen, Yuguang Tong .[Face Super-Resolution Through Wasserstein GANs](https://arxiv.org/pdf/1705.02438) .[J] arXiv preprint arXiv:1705.02438.
- Jae Hyun Lim, Jong Chul Ye .[Geometric GAN](https://arxiv.org/pdf/1705.02894) .[J] arXiv preprint arXiv:1705.02894.
- Hyeungill Lee, Sungyeob Han, Jungwoo Lee .[Generative Adversarial Trainer: Defense to Adversarial Perturbations with GAN](https://arxiv.org/pdf/1705.03387) .[J] arXiv preprint arXiv:1705.03387.
- Shuchang Zhou, Taihong Xiao, Yi Yang, Dieqiao Feng, Qinyao He, Weiran He .[GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data](https://arxiv.org/pdf/1705.04932) .[J] arXiv preprint arXiv:1705.04932.
- Vedran Vukotic, Christian Raymond, Guillaume Gravier .[Generative Adversarial Networks for Multimodal Representation Learning in Video Hyperlinking](https://arxiv.org/pdf/1705.05103) .[J] arXiv preprint arXiv:1705.05103.
- Ivo Danihelka, Balaji Lakshminarayanan, Benigno Uria, Daan Wierstra, Peter Dayan .[Comparison of Maximum Likelihood and GAN-based training of Real NVPs](https://arxiv.org/pdf/1705.05263) .[J] arXiv preprint arXiv:1705.05263.
- Urs Bergmann, Nikolay Jetchev, Roland Vollgraf .[Learning Texture Manifolds with the Periodic Spatial GAN](https://arxiv.org/pdf/1705.06566) .[J] arXiv preprint arXiv:1705.06566.
- Xin Guo, Johnny Hong, Tianyi Lin, Nan Yang .[Relaxed Wasserstein with Applications to GANs](https://arxiv.org/pdf/1705.07164) .[J] arXiv preprint arXiv:1705.07164.
- Naveen Kodali, Jacob Abernethy, James Hays, Zsolt Kira .[On Convergence and Stability of GANs](https://arxiv.org/pdf/1705.07215) .[J] arXiv preprint arXiv:1705.07215.
- Arash Mehrjou, Bernhard Schölkopf, Saeed Saremi .[Annealed Generative Adversarial Networks](https://arxiv.org/pdf/1705.07505) .[J] arXiv preprint arXiv:1705.07505.
- Olivier Bousquet, Sylvain Gelly, Ilya Tolstikhin, Carl-Johann Simon-Gabriel, Bernhard Schoelkopf .[From optimal transport to generative modeling: the VEGAN cookbook](https://arxiv.org/pdf/1705.07642) .[J] arXiv preprint arXiv:1705.07642.
- Jamie Hayes, Luca Melis, George Danezis, Emiliano De Cristofaro .[LOGAN: Evaluating Privacy Leakage of Generative Models Using Generative Adversarial Networks](https://arxiv.org/pdf/1705.07663) .[J] arXiv preprint arXiv:1705.07663.
- Akash Srivastava, Lazar Valkov, Chris Russell, Michael U. Gutmann, Charles Sutton .[VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning](https://arxiv.org/pdf/1705.07761) .[J] arXiv preprint arXiv:1705.07761.
- Behnam Neyshabur, Srinadh Bhojanapalli, Ayan Chakrabarti .[Stabilizing GAN Training with Multiple Random Projections](https://arxiv.org/pdf/1705.07831) .[J] arXiv preprint arXiv:1705.07831.
- Chris Donahue, Zachary C. Lipton, Akshay Balsubramani, Julian McAuley .[Semantically Decomposing the Latent Spaces of Generative Adversarial Networks](https://arxiv.org/pdf/1705.07904) .[J] arXiv preprint arXiv:1705.07904.
- Ari Seff, Alex Beatson, Daniel Suo, Han Liu .[Continual Learning in Generative Adversarial Nets](https://arxiv.org/pdf/1705.08395) .[J] arXiv preprint arXiv:1705.08395.
- Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, Barnabás Póczos .[MMD GAN: Towards Deeper Understanding of Moment Matching Network](https://arxiv.org/pdf/1705.08584) .[J] arXiv preprint arXiv:1705.08584.
- Paolo Russo, Fabio Maria Carlucci, Tatiana Tommasi, Barbara Caputo .[From source to target and back: symmetric bi-directional adaptive GAN](https://arxiv.org/pdf/1705.08824) .[J] arXiv preprint arXiv:1705.08824.
- Abhishek Kumar, Prasanna Sattigeri, P. Thomas Fletcher .[Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference](https://arxiv.org/pdf/1705.08850) .[J] arXiv preprint arXiv:1705.08850.
- Aditya Grover, Manik Dhar, Stefano Ermon .[Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models](https://arxiv.org/pdf/1705.08868) .[J] arXiv preprint arXiv:1705.08868.
- Shuang Liu, Olivier Bousquet, Kamalika Chaudhuri .[Approximation and Convergence Properties of Generative Adversarial Learning](https://arxiv.org/pdf/1705.08991) .[J] arXiv preprint arXiv:1705.08991.
- Mathieu Sinn, Ambrish Rawat .[Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training](https://arxiv.org/pdf/1705.09199) .[J] arXiv preprint arXiv:1705.09199.
- Kevin Roth, Aurelien Lucchi, Sebastian Nowozin, Thomas Hofmann .[Stabilizing Training of Generative Adversarial Networks through Regularization](https://arxiv.org/pdf/1705.09367) .[J] arXiv preprint arXiv:1705.09367.
- Yunus Saatchi, Andrew Gordon Wilson .[Bayesian GAN](https://arxiv.org/pdf/1705.09558) .[J] arXiv preprint arXiv:1705.09558.
- Youssef Mroueh, Tom Sercu .[Fisher GAN](https://arxiv.org/pdf/1705.09675) .[J] arXiv preprint arXiv:1705.09675.
- Zihang Dai, Zhilin Yang, Fan Yang, William W. Cohen, Ruslan Salakhutdinov .[Good Semi-supervised Learning that Requires a Bad GAN](https://arxiv.org/pdf/1705.09783) .[J] arXiv preprint arXiv:1705.09783.
- Yongyi Lu, Yu-Wing Tai, Chi-Keung Tang .[Conditional CycleGAN for Attribute Guided Face Image Generation](https://arxiv.org/pdf/1705.09966) .[J] arXiv preprint arXiv:1705.09966.
- Evgeny Zamyatin, Andrey Filchenkov .[Learning to Generate Chairs with Generative Adversarial Nets](https://arxiv.org/pdf/1705.10413) .[J] arXiv preprint arXiv:1705.10413.
- Lars Mescheder, Sebastian Nowozin, Andreas Geiger .[The Numerics of GANs](https://arxiv.org/pdf/1705.10461) .[J] arXiv preprint arXiv:1705.10461.
- Karol Hausman, Yevgen Chebotar, Stefan Schaal, Gaurav Sukhatme, Joseph Lim .[Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets](https://arxiv.org/pdf/1705.10479) .[J] arXiv preprint arXiv:1705.10479.
- Jun Wang, Lantao Yu, Weinan Zhang, Yu Gong, Yinghui Xu, Benyou Wang, Peng Zhang, Dell Zhang .[IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models](https://arxiv.org/pdf/1705.10513) .[J] arXiv preprint arXiv:1705.10513.
- Morteza Mardani, Enhao Gong, Joseph Y. Cheng, Shreyas Vasanawala, Greg Zaharchuk, Marcus Alley, Neil Thakur, Song Han, William Dally, John M. Pauly, Lei Xing .[Deep Generative Adversarial Networks for Compressed Sensing Automates MRI](https://arxiv.org/pdf/1706.00051) .[J] arXiv preprint arXiv:1706.00051.
- Marco Marchesi .[Megapixel Size Image Creation using Generative Adversarial Networks](https://arxiv.org/pdf/1706.00082) .[J] arXiv preprint arXiv:1706.00082.
- Elena Ibragimova, Ilgis Ibragimov .[The ELEGANT NMR Spectrometer](https://arxiv.org/pdf/1706.00237) .[J] arXiv preprint arXiv:1706.00237.
- Alireza Makhzani, Brendan Frey .[PixelGAN Autoencoders](https://arxiv.org/pdf/1706.00531) .[J] arXiv preprint arXiv:1706.00531.
- Ofir Press, Amir Bar, Ben Bogin, Jonathan Berant, Lior Wolf .[Language Generation with Recurrent Generative Adversarial Networks without Pre-training](https://arxiv.org/pdf/1706.01399) .[J] arXiv preprint arXiv:1706.01399.
- Yuan Xue, Tao Xu, Han Zhang, Rodney Long, Xiaolei Huang .[SegAN: Adversarial Network with Multi-scale $L_1$ Loss for Medical Image Segmentation](https://arxiv.org/pdf/1706.01805) .[J] arXiv preprint arXiv:1706.01805.
- Aude Genevay, Gabriel Peyré, Marco Cuturi .[GAN and VAE from an Optimal Transport Point of View](https://arxiv.org/pdf/1706.01807) .[J] arXiv preprint arXiv:1706.01807.
- Swaminathan Gurumurthy, Ravi Kiran Sarvadevabhatla, Venkatesh Babu Radhakrishnan .[DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data](https://arxiv.org/pdf/1706.02071) .[J] arXiv preprint arXiv:1706.02071.
- He Zhao, Huiqi Li, Li Cheng .[Synthesizing Filamentary Structured Images with GANs](https://arxiv.org/pdf/1706.02185) .[J] arXiv preprint arXiv:1706.02185.
- Mustafa Mustafa, Deborah Bard, Wahid Bhimji, Rami Al-Rfou, Zarija Lukić .[Creating Virtual Universes Using Generative Adversarial Networks](https://arxiv.org/pdf/1706.02390) .[J] arXiv preprint arXiv:1706.02390.
- Cristóbal Esteban, Stephanie L. Hyland, Gunnar Rätsch .[Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs](https://arxiv.org/pdf/1706.02633) .[J] arXiv preprint arXiv:1706.02633.
- Wenqi Xian, Patsorn Sangkloy, Varun Agrawal, Amit Raj, Jingwan Lu, Chen Fang, Fisher Yu, James Hays .[TextureGAN: Controlling Deep Image Synthesis with Texture Patches](https://arxiv.org/pdf/1706.02823) .[J] arXiv preprint arXiv:1706.02823.
- Paulina Grnarova, Kfir Y. Levy, Aurelien Lucchi, Thomas Hofmann, Andreas Krause .[An Online Learning Approach to Generative Adversarial Networks](https://arxiv.org/pdf/1706.03269) .[J] arXiv preprint arXiv:1706.03269.
- Lvmin Zhang, Yi Ji, Xin Lin .[Style Transfer for Anime Sketches with Enhanced Residual U-net and Auxiliary Classifier GAN](https://arxiv.org/pdf/1706.03319) .[J] arXiv preprint arXiv:1706.03319.
- Vaishnavh Nagarajan, J. Zico Kolter .[Gradient descent GAN optimization is locally stable](https://arxiv.org/pdf/1706.04156) .[J] arXiv preprint arXiv:1706.04156.
- Mihaela Rosca, Balaji Lakshminarayanan, David Warde-Farley, Shakir Mohamed .[Variational Approaches for Auto-Encoding Generative Adversarial Networks](https://arxiv.org/pdf/1706.04987) .[J] arXiv preprint arXiv:1706.04987.
- Jerry Liu, Fisher Yu, Thomas Funkhouser .[Interactive 3D Modeling with a Generative Adversarial Network](https://arxiv.org/pdf/1706.05170) .[J] arXiv preprint arXiv:1706.05170.
- Jianan Li, Xiaodan Liang, Yunchao Wei, Tingfa Xu, Jiashi Feng, Shuicheng Yan .[Perceptual Generative Adversarial Networks for Small Object Detection](https://arxiv.org/pdf/1706.05274) .[J] arXiv preprint arXiv:1706.05274.
- Yujia Li, Alexander Schwing, Kuan-Chieh Wang, Richard Zemel .[Dualing GANs](https://arxiv.org/pdf/1706.06216) .[J] arXiv preprint arXiv:1706.06216.
- Paulina Hensman, Kiyoharu Aizawa .[cGAN-based Manga Colorization Using a Single Training Image](https://arxiv.org/pdf/1706.06918) .[J] arXiv preprint arXiv:1706.06918.
- Sanjeev Arora, Yi Zhang .[Do GANs actually learn the distribution? An empirical study](https://arxiv.org/pdf/1706.08224) .[J] arXiv preprint arXiv:1706.08224.
- Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Sepp Hochreiter .[GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium](https://arxiv.org/pdf/1706.08500) .[J] arXiv preprint arXiv:1706.08500.
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[code;[/biggan_generation_with_tf_hub.ipynb](https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/biggan_generation_with_tf_hub.ipynb#scrollTo=Cd1dhL4Ykbm7)]
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- David M. Reiman, Brett E. Göhre .[Deblending galaxy superpositions with branched generative adversarial networks](https://arxiv.org/pdf/1810.10098) .[J] arXiv preprint arXiv:1810.10098.
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- Yilei Shi, Qingyu Li, Xiao Xiang Zhu .[Building Footprint Generation Using Improved Generative Adversarial Networks](https://arxiv.org/pdf/1810.11224) .[J] arXiv preprint arXiv:1810.11224.
- Karren D. Yang, Caroline Uhler .[Scalable Unbalanced Optimal Transport using Generative Adversarial Networks](https://arxiv.org/pdf/1810.11447) .[J] arXiv preprint arXiv:1810.11447.
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- Farzan Farnia, David Tse .[A Convex Duality Framework for GANs](https://arxiv.org/pdf/1810.11740) .[J] arXiv preprint arXiv:1810.11740.
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- Lauri Juvela, Bajibabu Bollepalli, Junichi Yamagishi, Paavo Alku .[Waveform generation for text-to-speech synthesis using pitch-synchronous multi-scale generative adversarial networks](https://arxiv.org/pdf/1810.12598) .[J] arXiv preprint arXiv:1810.12598.
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- Guy Tevet, Gavriel Habib, Vered Shwartz, Jonathan Berant .[Evaluating Text GANs as Language Models](https://arxiv.org/pdf/1810.12686) .[J] arXiv preprint arXiv:1810.12686.
- Alexander Y. Sun .[Discovering state-parameter mappings in subsurface models using generative adversarial networks](https://arxiv.org/pdf/1810.12856) .[J] arXiv preprint arXiv:1810.12856.
- Xiao Liang, Liyuan Chen, Dan Nguyen, Zhiguo Zhou, Xuejun Gu, Ming Yang, Jing Wang, Steve Jiang .[Generating Synthesized Computed Tomography (CT) from Cone-Beam Computed Tomography (CBCT) using CycleGAN for Adaptive Radiation Therapy](https://arxiv.org/pdf/1810.13350) .[J] arXiv preprint arXiv:1810.13350.
- Hamid Eghbal-zadeh, Werner Zellinger, Gerhard Widmer .[Mixture Density Generative Adversarial Networks](https://arxiv.org/pdf/1811.00152) .[J] arXiv preprint arXiv:1811.00152.
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- Kaidi Cao, Jing Liao, Lu Yuan .[CariGANs: Unpaired Photo-to-Caricature Translation](https://arxiv.org/pdf/1811.00222) .[J] arXiv preprint arXiv:1811.00222.
- Cho Ying Wu, Ulrich Neumann .[Efficient Multi-Domain Dictionary Learning with GANs](https://arxiv.org/pdf/1811.00274) .[J] arXiv preprint arXiv:1811.00274.
- Xiaotong Luo, Rong Chen, Yuan Xie, Yanyun Qu, Cuihua Li .[Bi-GANs-ST for Perceptual Image Super-resolution](https://arxiv.org/pdf/1811.00367) .[J] arXiv preprint arXiv:1811.00367.
- Wenbin Li, Wei Xiong, Haofu Liao, Jing Huo, Yang Gao, Jiebo Luo .[CariGAN: Caricature Generation through Weakly Paired Adversarial Learning](https://arxiv.org/pdf/1811.00445) .[J] arXiv preprint arXiv:1811.00445.
- Amanda Rios, Laurent Itti .[Closed-Loop GAN for continual Learning](https://arxiv.org/pdf/1811.01146) .[J] arXiv preprint arXiv:1811.01146.
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- Maryam Sultana, Arif Mahmood, Sajid Javed, Soon Ki Jung .[Unsupervised RGBD Video Object Segmentation Using GANs](https://arxiv.org/pdf/1811.01526) .[J] arXiv preprint arXiv:1811.01526.
- Ya-Ping Hsieh, Chen Liu, Volkan Cevher .[Finding Mixed Nash Equilibria of Generative Adversarial Networks](https://arxiv.org/pdf/1811.02002) .[J] arXiv preprint arXiv:1811.02002.
- Liu Yang, Dongkun Zhang, George Em Karniadakis .[Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations](https://arxiv.org/pdf/1811.02033) .[J] arXiv preprint arXiv:1811.02033.
- Jinxuan Sun, Guoqiang Zhong, Yang Chen, Yongbin Liu, Tao Li, Zhongwen Guo .[Student's t-Generative Adversarial Networks](https://arxiv.org/pdf/1811.02132) .[J] arXiv preprint arXiv:1811.02132.
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- Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin .[Language GANs Falling Short](https://arxiv.org/pdf/1811.02549) .[J] arXiv preprint arXiv:1811.02549.
- Yannis Pantazis, Dipjyoti Paul, Michail Fasoulakis, Yannis Stylianou .[Training Generative Adversarial Networks with Weights](https://arxiv.org/pdf/1811.02598) .[J] arXiv preprint arXiv:1811.02598.
- Aman Rana, Gregory Yauney, Alarice Lowe, Pratik Shah .[Computational Histological Staining and Destaining of Prostate Core Biopsy RGB Images with Generative Adversarial Neural Networks](https://arxiv.org/pdf/1811.02642) .[J] arXiv preprint arXiv:1811.02642.
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- Zhizhong Han, Mingyang Shang, Yu-Shen Liu, Matthias Zwicker .[View Inter-Prediction GAN: Unsupervised Representation Learning for 3D Shapes by Learning Global Shape Memories to Support Local View Predictions](https://arxiv.org/pdf/1811.02744) .[J] arXiv preprint arXiv:1811.02744.
- Ilya Kamenshchikov, Matthias Krauledat .[Effects of Dataset properties on the training of GANs](https://arxiv.org/pdf/1811.02850) .[J] arXiv preprint arXiv:1811.02850.
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- Levi Fussell, Ben Moews .[Forging new worlds: high-resolution synthetic galaxies with chained generative adversarial networks](https://arxiv.org/pdf/1811.03081) .[J] arXiv preprint arXiv:1811.03081.
- Tengyuan Liang .[On How Well Generative Adversarial Networks Learn Densities: Nonparametric and Parametric Results](https://arxiv.org/pdf/1811.03179) .[J] arXiv preprint arXiv:1811.03179.
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- Enrique Sanchez, Michel Valstar .[Triple consistency loss for pairing distributions in GAN-based face synthesis](https://arxiv.org/pdf/1811.03492) .[J] arXiv preprint arXiv:1811.03492.
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- Oleksii Sidorov .[Changing the Image Memorability: From Basic Photo Editing to GANs](https://arxiv.org/pdf/1811.03825) .[J] arXiv preprint arXiv:1811.03825.
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- Maciej Zamorski, Maciej Zięba .[Semi-supervised learning with Bidirectional GANs](https://arxiv.org/pdf/1811.11426) .[J] arXiv preprint arXiv:1811.11426.
- Jialun Liu .[Identity Preserving Generative Adversarial Network for Cross-Domain Person Re-identification](https://arxiv.org/pdf/1811.11510) .[J] arXiv preprint arXiv:1811.11510.
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- Wenyuan Li, Yunlong Wang, Yong Cai, Corey Arnold, Emily Zhao, Yilian Yuan .[Semi-supervised Rare Disease Detection Using Generative Adversarial Network](https://arxiv.org/pdf/1812.00547) .[J] arXiv preprint arXiv:1812.00547.
- Lijun Zhang, Yujin Zhang, Yongbin Gao .[A Wasserstein GAN model with the total variational regularization](https://arxiv.org/pdf/1812.00810) .[J] arXiv preprint arXiv:1812.00810.
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- Patricia Vitoria, Joan Sintes, Coloma Ballester .[Semantic Image Inpainting Through Improved Wasserstein Generative Adversarial Networks](https://arxiv.org/pdf/1812.01071) .[J] arXiv preprint arXiv:1812.01071.
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- Sebastian Bujwid, Miquel Martí, Hossein Azizpour, Alessandro Pieropan .[GANtruth - an unpaired image-to-image translation method for driving scenarios](https://arxiv.org/pdf/1812.01710) .[J] arXiv preprint arXiv:1812.01710.
- Mario Rüttgers, Sangseung Lee, Donghyun You .[Prediction of typhoon tracks using a generative adversarial network with observational and meteorological data](https://arxiv.org/pdf/1812.01943) .[J] arXiv preprint arXiv:1812.01943.
- Ruishan Liu, Nicolo Fusi, Lester Mackey .[Model Compression with Generative Adversarial Networks](https://arxiv.org/pdf/1812.02271) .[J] arXiv preprint arXiv:1812.02271.
- Qiao Tian, Bing Yang, Jing Chen, Benlai Tang, Shan Liu .[Generative Adversarial Network based Speaker Adaptation for High Fidelity WaveNet Vocoder](https://arxiv.org/pdf/1812.02339) .[J] arXiv preprint arXiv:1812.02339.
- Ilyass Haloui, Jayant Sen Gupta, Vincent Feuillard .[Anomaly detection with Wasserstein GAN](https://arxiv.org/pdf/1812.02463) .[J] arXiv preprint arXiv:1812.02463.
- Jogendra Nath Kundu, Maharshi Gor, R. Venkatesh Babu .[BiHMP-GAN: Bidirectional 3D Human Motion Prediction GAN](https://arxiv.org/pdf/1812.02591) .[J] arXiv preprint arXiv:1812.02591.
- Yitong Li, Zhe Gan, Yelong Shen, Jingjing Liu, Yu Cheng, Yuexin Wu, Lawrence Carin, David Carlson, Jianfeng Gao .[StoryGAN: A Sequential Conditional GAN for Story Visualization](https://arxiv.org/pdf/1812.02784) .[J] arXiv preprint arXiv:1812.02784.
- Partha Das, Anil S. Baslamisli, Yang Liu, Sezer Karaoglu, Theo Gevers .[Color Constancy by GANs: An Experimental Survey](https://arxiv.org/pdf/1812.03085) .[J] arXiv preprint arXiv:1812.03085.
- Xiangtian Zheng, Bin Wang, Le Xie .[Synthetic Dynamic PMU Data Generation: A Generative Adversarial Network Approach](https://arxiv.org/pdf/1812.03203) .[J] arXiv preprint arXiv:1812.03203.
- Blerta Lindqvist, Shridatt Sugrim, Rauf Izmailov .[AutoGAN: Robust Classifier Against Adversarial Attacks](https://arxiv.org/pdf/1812.03405) .[J] arXiv preprint arXiv:1812.03405.
- Milad Salem, Shayan Taheri, Jiann Shiun Yuan .[Anomaly Generation using Generative Adversarial Networks in Host Based Intrusion Detection](https://arxiv.org/pdf/1812.04697) .[J] arXiv preprint arXiv:1812.04697.
- Dung N. Tran, Trac D. Tran, Lam Nguyen .[Generative Adversarial Networks for Recovering Missing Spectral Information](https://arxiv.org/pdf/1812.04744) .[J] arXiv preprint arXiv:1812.04744.
- Harsh Nilesh Pathak, Xinxin Li, Shervin Minaee, Brooke Cowan .[Efficient Super Resolution For Large-Scale Images Using Attentional GAN](https://arxiv.org/pdf/1812.04821) .[J] arXiv preprint arXiv:1812.04821.
- Shervin Minaee, Amirali Abdolrashidi .[Iris-GAN: Learning to Generate Realistic Iris Images Using Convolutional GAN](https://arxiv.org/pdf/1812.04822) .[J] arXiv preprint arXiv:1812.04822.
- 【StyleGAN&Nvidia】Tero Karras, Samuli Laine, Timo Aila .[A Style-Based Generator Architecture for Generative Adversarial Networks](https://arxiv.org/pdf/1812.04948) .[J] arXiv preprint arXiv:1812.04948.
[code:
|[NVlabs/stylegan](https://github.com/NVlabs/stylegan)|
|[neuralnotworklab/stylegan](https://github.com/neuralnotworklab/stylegan)|
|[korjusk/stylega](https://github.com/korjusk/stylegan)|
]
- He Zhang, Benjamin S. Riggan, Shuowen Hu, Nathaniel J. Short, Vishal M.Patel .[Synthesis of High-Quality Visible Faces from Polarimetric Thermal Faces using Generative Adversarial Networks](https://arxiv.org/pdf/1812.05155) .[J] arXiv preprint arXiv:1812.05155.
- Lu Mi, Macheng Shen, Jingzhao Zhang .[A Probe Towards Understanding GAN and VAE Models](https://arxiv.org/pdf/1812.05676) .[J] arXiv preprint arXiv:1812.05676.
- Fangneng Zhan, Hongyuan Zhu, Shijian Lu .[Spatial Fusion GAN for Image Synthesis](https://arxiv.org/pdf/1812.05840) .[J] arXiv preprint arXiv:1812.05840.
- L. Li, A. Vakanski (University of Idaho, USA) .[Generative adversarial networks for generation and classification of physical rehabilitation movement episodes](https://arxiv.org/pdf/1812.06307) .[J] arXiv preprint arXiv:1812.06307.
- Shuai Yang, Jiaying Liu, Wenjing Wang, Zongming Guo .[TET-GAN: Text Effects Transfer via Stylization and Destylization](https://arxiv.org/pdf/1812.06384) .[J] arXiv preprint arXiv:1812.06384.
- Lili Pan, Shen Cheng, Jian Liu, Yazhou Ren, Zenglin Xu .[Latent Dirichlet Allocation in Generative Adversarial Networks](https://arxiv.org/pdf/1812.06571) .[J] arXiv preprint arXiv:1812.06571.
- Harshala Gammulle, Simon Denman, Sridha Sridharan, Clinton Fookes .[Multi-Level Sequence GAN for Group Activity Recognition](https://arxiv.org/pdf/1812.07124) .[J] arXiv preprint arXiv:1812.07124.
- Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes .[GD-GAN: Generative Adversarial Networks for Trajectory Prediction and Group Detection in Crowds](https://arxiv.org/pdf/1812.07667) .[J] arXiv preprint arXiv:1812.07667.
- Holly Grimm .[Training on Art Composition Attributes to Influence CycleGAN Art Generation](https://arxiv.org/pdf/1812.07710) .[J] arXiv preprint arXiv:1812.07710.
- Rahul Dey, Felix Juefei-Xu, Vishnu Naresh Boddeti, Marios Savvides .[RankGAN: A Maximum Margin Ranking GAN for Generating Faces](https://arxiv.org/pdf/1812.08196) .[J] arXiv preprint arXiv:1812.08196.
- Scott McCloskey, Michael Albright .[Detecting GAN-generated Imagery using Color Cues](https://arxiv.org/pdf/1812.08247) .[J] arXiv preprint arXiv:1812.08247.
- Yu Cheng, Zhe Gan, Yitong Li, Jingjing Liu, Jianfeng Gao .[Sequential Attention GAN for Interactive Image Editing via Dialogue](https://arxiv.org/pdf/1812.08352) .[J] arXiv preprint arXiv:1812.08352.
- Eric Laloy, Niklas Linde, Cyprien Ruffino, Romain Hérault, Gilles Gasso, Diedrik Jacques .[Gradient-based deterministic inversion of geophysical data with Generative Adversarial Networks: is it feasible?](https://arxiv.org/pdf/1812.09140) .[J] arXiv preprint arXiv:1812.09140.
- Aaron Babier, Rafid Mahmood, Andrea L. McNiven, Adam Diamant, Timothy C. Y. Chan .[Knowledge-based automated planning with three-dimensional generative adversarial networks](https://arxiv.org/pdf/1812.09309) .[J] arXiv preprint arXiv:1812.09309.
- WenTing Chen, Xinpeng Xie, Xi Jia, Linlin Shen .[Texture Deformation Based Generative Adversarial Networks for Face Editing](https://arxiv.org/pdf/1812.09832) .[J] arXiv preprint arXiv:1812.09832.
- Wei Wang, Yuan Sun, Saman Halgamuge .[Improving MMD-GAN Training with Repulsive Loss Function](https://arxiv.org/pdf/1812.09916) .[J] arXiv preprint arXiv:1812.09916.
- Bappaditya Mandal, N. B. Puhan, Avijit Verma .[Deep Convolutional Generative Adversarial Network Based Food Recognition Using Partially Labeled Data](https://arxiv.org/pdf/1812.10179) .[J] arXiv preprint arXiv:1812.10179.
- Aria Rezaei, Chaowei Xiao, Jie Gao, Bo Li .[Protecting Sensitive Attributes via Generative Adversarial Networks](https://arxiv.org/pdf/1812.10193) .[J] arXiv preprint arXiv:1812.10193.
- Shervin Minaee, Amirali Abdolrashidi .[Finger-GAN: Generating Realistic Fingerprint Images Using Connectivity Imposed GAN](https://arxiv.org/pdf/1812.10482) .[J] arXiv preprint arXiv:1812.10482.
- Shayne O'Brien, Matt Groh, Abhimanyu Dubey .[Evaluating Generative Adversarial Networks on Explicitly Parameterized Distributions](https://arxiv.org/pdf/1812.10782) .[J] arXiv preprint arXiv:1812.10782.
- 【InstaGAN】Sangwoo Mo, Minsu Cho, Jinwoo Shin .[InstaGAN: Instance-aware Image-to-Image Translation](https://arxiv.org/pdf/1812.10889) .[J] arXiv preprint arXiv:1812.10889.
[code:[sangwoomo/instagan](https://github.com/sangwoomo/instagan)]
- Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao .[On Computation and Generalization of GANs with Spectrum Control](https://arxiv.org/pdf/1812.10912) .[J] arXiv preprint arXiv:1812.10912.
- Moran Rubin, Omer Stein, Nir A. Turko, Yoav Nygate, Darina Roitshtain, Lidor Karako, Itay Barnea, Raja Giryes, Natan T. Shaked .[TOP-GAN: Label-Free Cancer Cell Classification Using Deep Learning with a Small Training Set](https://arxiv.org/pdf/1812.11006) .[J] arXiv preprint arXiv:1812.11006.
- Irina Sanchez, Veronica Vilaplana .[Brain MRI super-resolution using 3D generative adversarial networks](https://arxiv.org/pdf/1812.11440) .[J] arXiv preprint arXiv:1812.11440.
- Francesco Marra, Diego Gragnaniello, Luisa Verdoliva, Giovanni Poggi .[Do GANs leave artificial fingerprints?](https://arxiv.org/pdf/1812.11842) .[J] arXiv preprint arXiv:1812.11842.---
### 2019
- Kamyar Nazeri, Eric Ng, Tony Joseph, Faisal Z. Qureshi, Mehran Ebrahimi .[EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning](https://arxiv.org/pdf/1901.00212) .[J] arXiv preprint arXiv:1901.00212.
- Jonathan Romero, Alan Aspuru-Guzik .[Variational quantum generators: Generative adversarial quantum machine learning for continuous distributions](https://arxiv.org/pdf/1901.00848) .[J] arXiv preprint arXiv:1901.00848.
- Quan Yuan, Junxia Li, Lingwei Zhang, Zhefu Wu, Guangyu Liu .[Blind Motion Deblurring with Cycle Generative Adversarial Networks](https://arxiv.org/pdf/1901.01641) .[J] arXiv preprint arXiv:1901.01641.
- Guohao Ying, Yingtian Zou, Lin Wan, Yiming Hu, Jiashi Feng .[Better Guider Predicts Future Better: Difference Guided Generative Adversarial Networks](https://arxiv.org/pdf/1901.01649) .[J] arXiv preprint arXiv:1901.01649.
- Adriano Koshiyama, Nick Firoozye, Philip Treleaven .[Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination](https://arxiv.org/pdf/1901.01751) .[J] arXiv preprint arXiv:1901.01751.
- Lorenzo Frigerio, Anderson Santana de Oliveira, Laurent Gomez, Patrick Duverger .[Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data](https://arxiv.org/pdf/1901.02477) .[J] arXiv preprint arXiv:1901.02477.
- Stephanie Ger, Diego Klabjan .[Autoencoders and Generative Adversarial Networks for Anomaly Detection for Sequences](https://arxiv.org/pdf/1901.02514) .[J] arXiv preprint arXiv:1901.02514.
- Constantinos Papayiannis, Christine Evers, Patrick A. Naylor .[Data Augmentation of Room Classifiers using Generative Adversarial Networks](https://arxiv.org/pdf/1901.03257) .[J] arXiv preprint arXiv:1901.03257.
- Jin Zhu, Guang Yang, Pietro Lio .[How Can We Make GAN Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale Approach](https://arxiv.org/pdf/1901.03419) .[J] arXiv preprint arXiv:1901.03419.
- Jiaxing Tan, Longlong Jing, Yumei Huo, Yingli Tian, Oguz Akin .[LGAN: Lung Segmentation in CT Scans Using Generative Adversarial Network](https://arxiv.org/pdf/1901.03473) .[J] arXiv preprint arXiv:1901.03473.
- Kishan Babu Kancharagunta, Shiv Ram Dubey .[CSGAN: Cyclic-Synthesized Generative Adversarial Networks for Image-to-Image Transformation](https://arxiv.org/pdf/1901.03554) .[J] arXiv preprint arXiv:1901.03554.
- Yisroel Mirsky, Tom Mahler, Ilan Shelef, Yuval Elovici .[CT-GAN: Malicious Tampering of 3D Medical Imagery using Deep Learning](https://arxiv.org/pdf/1901.03597) .[J] arXiv preprint arXiv:1901.03597.
- Kevin Alex Zhang, Alfredo Cuesta-Infante, Lei Xu, Kalyan Veeramachaneni .[SteganoGAN: High Capacity Image Steganography with GANs](https://arxiv.org/pdf/1901.03892) .[J] arXiv preprint arXiv:1901.03892.
- Jingwei Gan, Pai Liu, Rajan K. Chakrabarty .[Introducing a Generative Adversarial Network Model for Lagrangian Trajectory Simulation](https://arxiv.org/pdf/1901.03960) .[J] arXiv preprint arXiv:1901.03960.
- Zhaoyang Xu, Carlos Fernández Moro, Béla Bozóky, Qianni Zhang .[GAN-based Virtual Re-Staining: A Promising Solution for Whole Slide Image Analysis](https://arxiv.org/pdf/1901.04059) .[J] arXiv preprint arXiv:1901.04059.
- Omry Sendik, Dani Lischinski, Daniel CohenOr .[XNet: GAN Latent Space Constraints](https://arxiv.org/pdf/1901.04530) .[J] arXiv preprint arXiv:1901.04530.
- Hao Tang, Dan Xu, Wei Wang, Yan Yan, Nicu Sebe .[Dual Generator Generative Adversarial Networks for Multi-Domain Image-to-Image Translation](https://arxiv.org/pdf/1901.04604) .[J] arXiv preprint arXiv:1901.04604.
- Saber Malekzadeh, Maryam Samami, Shahla RezazadehAzar, Maryam Rayegan .[Classical Music Generation in Distinct Dastgahs with AlimNet ACGAN](https://arxiv.org/pdf/1901.04696) .[J] arXiv preprint arXiv:1901.04696.
- Dan Li, Dacheng Chen, Lei Shi, Baihong Jin, Jonathan Goh, See-Kiong Ng .[MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks](https://arxiv.org/pdf/1901.04997) .[J] arXiv preprint arXiv:1901.04997.
- Xilei Cao, Gurupraanesh Raman, Gururaghav Raman, Jimmy Chih-Hsien Peng .[Generative Adversarial Networks for Real-time Stability of Inverter-based Systems](https://arxiv.org/pdf/1901.05114) .[J] arXiv preprint arXiv:1901.05114.
- Bodo Kaiser, Shadi Albarqouni .[MRI to CT Translation with GANs](https://arxiv.org/pdf/1901.05259) .[J] arXiv preprint arXiv:1901.05259.
- Bobak Hashemi, Nick Amin, Kaustuv Datta, Dominick Olivito, Maurizio Pierini .[LHC analysis-specific datasets with Generative Adversarial Networks](https://arxiv.org/pdf/1901.05282) .[J] arXiv preprint arXiv:1901.05282.
- Hugo Oliveira, Edemir Ferreira, Jefersson A. dos Santos .[Conditional Domain Adaptation GANs for Biomedical Image Segmentation](https://arxiv.org/pdf/1901.05553) .[J] arXiv preprint arXiv:1901.05553.
- S. Kida, S. Kaji, K. Nawa, T. Imae, T. Nakamoto, S. Ozaki, T. Ohta, Y. Nozawa, K. Nakagawa .[Cone-beam CT to Planning CT synthesis using generative adversarial networks](https://arxiv.org/pdf/1901.05773) .[J] arXiv preprint arXiv:1901.05773.
- Zhuang Qian, Kaizhu Huang, Qiufeng Wang, Jimin Xiao, Rui Zhang .[Generative Adversarial Classifier for Handwriting Characters Super-Resolution](https://arxiv.org/pdf/1901.06199) .[J] arXiv preprint arXiv:1901.06199.
- Oleksandr Bailo, DongShik Ham, Young Min Shin .[Red blood cell image generation for data augmentation using Conditional Generative Adversarial Networks](https://arxiv.org/pdf/1901.06219) .[J] arXiv preprint arXiv:1901.06219.
- Gil Shamai, Ron Slossberg, Ron Kimmel .[Synthesizing facial photometries and corresponding geometries using generative adversarial networks](https://arxiv.org/pdf/1901.06551) .[J] arXiv preprint arXiv:1901.06551.
- Yuting Jia, Qinqin Zhang, Weinan Zhang, Xinbing Wang .[CommunityGAN: Community Detection with Generative Adversarial Nets](https://arxiv.org/pdf/1901.06631) .[J] arXiv preprint arXiv:1901.06631.
- Uddeshya Upadhyay, Arjun Jain .[Removal of Batch Effects using Generative Adversarial Networks](https://arxiv.org/pdf/1901.06654) .[J] arXiv preprint arXiv:1901.06654.
- Jianan Li, Jimei Yang, Aaron Hertzmann, Jianming Zhang, Tingfa Xu .[LayoutGAN: Generating Graphic Layouts with Wireframe Discriminators](https://arxiv.org/pdf/1901.06767) .[J] arXiv preprint arXiv:1901.06767.
- Kentaro Fukamizu, Masaaki Kondo, Ryuichi Sakamoto .[Generation High resolution 3D model from natural language by Generative Adversarial Network](https://arxiv.org/pdf/1901.07165) .[J] arXiv preprint arXiv:1901.07165.
- Yunfeng Lin, Jiangbei Li, Hanjing Wang .[DCNN-GAN: Reconstructing Realistic Image from fMRI](https://arxiv.org/pdf/1901.07368) .[J] arXiv preprint arXiv:1901.07368.
- Hongyu Yang, Di Huang, Yunhong Wang, Anil K. Jain .[Learning Continuous Face Age Progression: A Pyramid of GANs](https://arxiv.org/pdf/1901.07528) .[J] arXiv preprint arXiv:1901.07528.
- Yeu-Chern Harn, Zhenghao Chen, Vladimir Jojic .[Composition and decomposition of GANs](https://arxiv.org/pdf/1901.07667) .[J] arXiv preprint arXiv:1901.07667.
- M.-H. Herman Shen, Liang Chen .[A New CGAN Technique for Constrained Topology Design Optimization](https://arxiv.org/pdf/1901.07675) .[J] arXiv preprint arXiv:1901.07675.
- Byeongkeun Kang, Subarna Tripathi, Truong Q. Nguyen .[Toward Joint Image Generation and Compression using Generative Adversarial Networks](https://arxiv.org/pdf/1901.07838) .[J] arXiv preprint arXiv:1901.07838.
- Matteo Fabbri, Guido Borghi, Fabio Lanzi, Roberto Vezzani, Simone Calderara, Rita Cucchiara .[Domain Translation with Conditional GANs: from Depth to RGB Face-to-Face](https://arxiv.org/pdf/1901.08101) .[J] arXiv preprint arXiv:1901.08101.
- Matthew Amodio, Smita Krishnaswamy .[Generating and Aligning from Data Geometries with Generative Adversarial Networks](https://arxiv.org/pdf/1901.08177) .[J] arXiv preprint arXiv:1901.08177.
- Peiqi Wang, Dongsheng Wang, Yu Ji, Xinfeng Xie, Haoxuan Song, XuXin Liu, Yongqiang Lyu, Yuan Xie .[QGAN: Quantized Generative Adversarial Networks](https://arxiv.org/pdf/1901.08263) .[J] arXiv preprint arXiv:1901.08263.
- Philipp Seeböck, David Romo-Bucheli, Sebastian Waldstein, Hrvoje Bogunović, José Ignacio Orlando, Bianca S. Gerendas, Georg Langs, Ursula Schmidt-Erfurth .[Using CycleGANs for effectively reducing image variability across OCT devices and improving retinal fluid segmentation](https://arxiv.org/pdf/1901.08379) .[J] arXiv preprint arXiv:1901.08379.
- Frank Zijlstra, Koen Willemsen, Mateusz C. Florkow, Ralph J.B. Sakkers, Harrie H. Weinans, Bart C.H. van der Wal, Marijn van Stralen, Peter R. Seevinck .[CT synthesis from MR images for orthopedic applications in the lower arm using a conditional generative adversarial network](https://arxiv.org/pdf/1901.08449) .[J] arXiv preprint arXiv:1901.08449.
- Isabela Albuquerque, João Monteiro, Thang Doan, Breandan Considine, Tiago Falk, Ioannis Mitliagkas .[Multi-objective training of Generative Adversarial Networks with multiple discriminators](https://arxiv.org/pdf/1901.08680) .[J] arXiv preprint arXiv:1901.08680.
- Samet Akçay, Amir Atapour-Abarghouei, Toby P. Breckon .[Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection](https://arxiv.org/pdf/1901.08954) .[J] arXiv preprint arXiv:1901.08954.
- Dingdong Yang, Seunghoon Hong, Yunseok Jang, Tianchen Zhao, Honglak Lee .[Diversity-Sensitive Conditional Generative Adversarial Networks](https://arxiv.org/pdf/1901.09024) .[J] arXiv preprint arXiv:1901.09024.
- Yi Shi, Yalin E. Sagduyu, Kemal Davaslioglu, Jason H. Li .[Generative Adversarial Networks for Black-Box API Attacks with Limited Training Data](https://arxiv.org/pdf/1901.09113) .[J] arXiv preprint arXiv:1901.09113.
- Kai Lei, Meng Qin, Bo Bai, Gong Zhang, Min Yang .[GCN-GAN: A Non-linear Temporal Link Prediction Model for Weighted Dynamic Networks](https://arxiv.org/pdf/1901.09165) .[J] arXiv preprint arXiv:1901.09165.
- Anubhav Jain, Richa Singh, Mayank Vatsa .[On Detecting GANs and Retouching based Synthetic Alterations](https://arxiv.org/pdf/1901.09237) .[J] arXiv preprint arXiv:1901.09237.
- Stefan Milz, Martin Simon, Kai Fischer, Maximillian Pöpperl .[Points2Pix: 3D Point-Cloud to Image Translation using conditional Generative Adversarial Networks](https://arxiv.org/pdf/1901.09280) .[J] arXiv preprint arXiv:1901.09280.
- Banghua Zhu, Jiantao Jiao, David Tse .[Deconstructing Generative Adversarial Networks](https://arxiv.org/pdf/1901.09465) .[J] arXiv preprint arXiv:1901.09465.
- Pablo Sánchez-Martín, Pablo M. Olmos, Fernando Pérez-Cruz .[Out-of-Sample Testing for GANs](https://arxiv.org/pdf/1901.09557) .[J] arXiv preprint arXiv:1901.09557.
- Parisa Babaheidarian, Mark Wallace .[Decode and Transfer: A New Steganalysis Technique via Conditional Generative Adversarial Networks](https://arxiv.org/pdf/1901.09746) .[J] arXiv preprint arXiv:1901.09746.
- Dongwook Lee, Junyoung Kim, Won-Jin Moon, Jong Chul Ye .[CollaGAN : Collaborative GAN for Missing Image Data Imputation](https://arxiv.org/pdf/1901.09764) .[J] arXiv preprint arXiv:1901.09764.
- Haifeng Shi, Guanyu Cai, Yuqin Wang, Shaohua Shang, Lianghua He .[Virtual Conditional Generative Adversarial Networks](https://arxiv.org/pdf/1901.09822) .[J] arXiv preprint arXiv:1901.09822.
- David Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B. Tenenbaum, William T. Freeman, Antonio Torralba .[Visualizing and Understanding Generative Adversarial Networks (Extended Abstract)](https://arxiv.org/pdf/1901.09887) .[J] arXiv preprint arXiv:1901.09887.
- Zihan Ding, Xiao-Yang Liu, Miao Yin, Wei Liu, Linghe Kong .[TGAN: Deep Tensor Generative Adversarial Nets for Large Image Generation](https://arxiv.org/pdf/1901.09953) .[J] arXiv preprint arXiv:1901.09953.
- Ben Usman, Nick Dufour, Kate Saenko, Chris Bregler .[PuppetGAN: Transferring Disentangled Properties from Synthetic to Real Images](https://arxiv.org/pdf/1901.10024) .[J] arXiv preprint arXiv:1901.10024.
- Yaman Kumar, Shubham Maheshwari, Dhruva Sahrawat, Praveen Jhanwar, Vipin Chaudhary, Rajiv Ratn Shah, Debanjan Mahata .[Harnessing GANs for Addition of New Classes in VSR](https://arxiv.org/pdf/1901.10139) .[J] arXiv preprint arXiv:1901.10139.
- Pierre Nagorny (SYMME), Thomas Lacombe (SYMME), Hugues Favreliere (SYMME), Maurice Pillet (SYMME), Eric Pairel (SYMME), Ronan Le Goff (IPC), Marlene Wali (IPC), Jerome Loureaux (IPC), Patrice Kiener .[Generative Adversarial Networks for geometric surfaces prediction in injection molding](https://arxiv.org/pdf/1901.10178) .[J] arXiv preprint arXiv:1901.10178.
- Dan Zhang, Anna Khoreva .[PA-GAN: Improving GAN Training by Progressive Augmentation](https://arxiv.org/pdf/1901.10422) .[J] arXiv preprint arXiv:1901.10422.
- Casey Chu, Jose Blanchet, Peter Glynn .[Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning](https://arxiv.org/pdf/1901.10691) .[J] arXiv preprint arXiv:1901.10691.
- Ziqiang Zheng, Zhibin Yu, Haiyong Zheng, Yang Wu, Bing Zheng, Ping Lin .[Generative Adversarial Network with Multi-Branch Discriminator for Cross-Species Image-to-Image Translation](https://arxiv.org/pdf/1901.10895) .[J] arXiv preprint arXiv:1901.10895.
- Neale Ratzlaff, Li Fuxin .[HyperGAN: A Generative Model for Diverse, Performant Neural Networks](https://arxiv.org/pdf/1901.11058) .[J] arXiv preprint arXiv:1901.11058.
- Vineet Edupuganti, Morteza Mardani, Joseph Cheng, Shreyas Vasanawala, John Pauly .[VAE-GANs for Probabilistic Compressive Image Recovery: Uncertainty Analysis](https://arxiv.org/pdf/1901.11228) .[J] arXiv preprint arXiv:1901.11228.
- Ho Bae, Dahuin Jung, Sungroh Yoon .[AnomiGAN: Generative adversarial networks for anonymizing private medical data](https://arxiv.org/pdf/1901.11313) .[J] arXiv preprint arXiv:1901.11313.
- Monika Sharma, Abhishek Verma, Lovekesh Vig .[Learning to Clean: A GAN Perspective](https://arxiv.org/pdf/1901.11382) .[J] arXiv preprint arXiv:1901.11382.
- Isabela Albuquerque, João Monteiro, Tiago H. Falk .[Learning to navigate image manifolds induced by generative adversarial networks for unsupervised video generation](https://arxiv.org/pdf/1901.11384) .[J] arXiv preprint arXiv:1901.11384.
- Angeline Aguinaldo, Ping-Yeh Chiang, Alex Gain, Ameya Patil, Kolten Pearson, Soheil Feizi .[Compressing GANs using Knowledge Distillation](https://arxiv.org/pdf/1902.00159) .[J] arXiv preprint arXiv:1902.00159.
- Andrawes Al Bahou, Christine Tanner, Orcun Goksel .[SCATGAN for Reconstruction of Ultrasound Scatterers Using Generative Adversarial Networks](https://arxiv.org/pdf/1902.00469) .[J] arXiv preprint arXiv:1902.00469.
- Peter Klages, Ilyes Benslimane, Sadegh Riyahi, Jue Jiang, Margie Hunt, Joe Deasy, Harini Veeraraghavan, Neelam Tyagi .[Comparison of Patch-Based Conditional Generative Adversarial Neural Net Models with Emphasis on Model Robustness for Use in Head and Neck Cases for MR-Only planning](https://arxiv.org/pdf/1902.00536) .[J] arXiv preprint arXiv:1902.00536.
- Mehmet Ozgur Turkoglu, William Thong, Luuk Spreeuwers, Berkay Kicanaoglu .[A Layer-Based Sequential Framework for Scene Generation with GANs](https://arxiv.org/pdf/1902.00671) .[J] arXiv preprint arXiv:1902.00671.
- Yuejiang Liu, Parth Kothari, Alexandre Alahi .[Collaborative GAN Sampling](https://arxiv.org/pdf/1902.00813) .[J] arXiv preprint arXiv:1902.00813.
- Yuma Kishi, Tsutomu Ikegami, Shin-ichi O'uchi, Ryousei Takano, Wakana Nogami, Tomohiro Kudoh .[Perturbative GAN: GAN with Perturbation Layers](https://arxiv.org/pdf/1902.01514) .[J] arXiv preprint arXiv:1902.01514.
- Süleyman Aslan, Uğur Güdükbay, B. Uğur Töreyin, A. Enis Çetin .[Deep Convolutional Generative Adversarial Networks Based Flame Detection in Video](https://arxiv.org/pdf/1902.01824) .[J] arXiv preprint arXiv:1902.01824.
- Łukasz Maziarka, Agnieszka Pocha, Jan Kaczmarczyk, Krzysztof Rataj, Michał Warchoł .[Mol-CycleGAN - a generative model for molecular optimization](https://arxiv.org/pdf/1902.02119) .[J] arXiv preprint arXiv:1902.02119.
- Dwarikanath Mahapatra, Behzad Bozorgtabar .[Progressive Generative Adversarial Networks for Medical Image Super resolution](https://arxiv.org/pdf/1902.02144) .[J] arXiv preprint arXiv:1902.02144.
- Nir Diamant, Dean Zadok, Chaim Baskin, Eli Schwartz, Alex M. Bronstein .[Beholder-GAN: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level](https://arxiv.org/pdf/1902.02593) .[J] arXiv preprint arXiv:1902.02593.
- Tycho F.A. van der Ouderaa, Daniel E. Worrall .[Reversible GANs for Memory-efficient Image-to-Image Translation](https://arxiv.org/pdf/1902.02729) .[J] arXiv preprint arXiv:1902.02729.
- Maryam Sultana, Soon Ki Jung .[Illumination Invariant Foreground Object Segmentation using ForeGANs](https://arxiv.org/pdf/1902.03120) .[J] arXiv preprint arXiv:1902.03120.
- Alceu Bissoto, Fábio Perez, Eduardo Valle, Sandra Avila .[Skin Lesion Synthesis with Generative Adversarial Networks](https://arxiv.org/pdf/1902.03253) .[J] arXiv preprint arXiv:1902.03253.
- Michal Uricar, Pavel Krizek, David Hurych, Ibrahim Sobh, Senthil Yogamani, Patrick Denny .[Yes, we GAN: Applying Adversarial Techniques for Autonomous Driving](https://arxiv.org/pdf/1902.03442) .[J] arXiv preprint arXiv:1902.03442.
- Yasin Yazıcı, Bruno Lecouat, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar .[Venn GAN: Discovering Commonalities and Particularities of Multiple Distributions](https://arxiv.org/pdf/1902.03444) .[J] arXiv preprint arXiv:1902.03444.
- Victoria Fernandez Abrevaya, Adnane Boukhayma, Stefanie Wuhrer, Edmond Boyer .[A Generative 3D Facial Model by Adversarial Training](https://arxiv.org/pdf/1902.03619) .[J] arXiv preprint arXiv:1902.03619.
- Anton Mallasto, Jes Frellsen, Wouter Boomsma, Aasa Feragen .[(q,p)-Wasserstein GANs: Comparing Ground Metrics for Wasserstein GANs](https://arxiv.org/pdf/1902.03642) .[J] arXiv preprint arXiv:1902.03642.
- Hoang Thanh-Tung, Truyen Tran, Svetha Venkatesh .[Improving Generalization and Stability of Generative Adversarial Networks](https://arxiv.org/pdf/1902.03984) .[J] arXiv preprint arXiv:1902.03984.
- Jonas Löhdefink, Andreas Bär, Nico M. Schmidt, Fabian Hüger, Peter Schlicht, Tim Fingscheidt .[GAN- vs. JPEG2000 Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation](https://arxiv.org/pdf/1902.04311) .[J] arXiv preprint arXiv:1902.04311.
- Edward Collier, Kate Duffy, Sangram Ganguly, Geri Madanguit, Subodh Kalia, Gayaka Shreekant, Ramakrishna Nemani, Andrew Michaelis, Shuang Li, Auroop Ganguly, Supratik Mukhopadhyay .[Progressively Growing Generative Adversarial Networks for High Resolution Semantic Segmentation of Satellite Images](https://arxiv.org/pdf/1902.04604) .[J] arXiv preprint arXiv:1902.04604.
- Mohammadreza Soltani, Swayambhoo Jain, Abhinav Sambasivan .[Learning Generative Models of Structured Signals from Their Superposition Using GANs with Application to Denoising and Demixing](https://arxiv.org/pdf/1902.04664) .[J] arXiv preprint arXiv:1902.04664.
- Swetava Ganguli, Pedro Garzon, Noa Glaser .[GeoGAN: A Conditional GAN with Reconstruction and Style Loss to Generate Standard Layer of Maps from Satellite Images](https://arxiv.org/pdf/1902.05611) .[J] arXiv preprint arXiv:1902.05611.
- Eoin Brophy, Zhengwei Wang, Tomas E. Ward .[Quick and Easy Time Series Generation with Established Image-based GANs](https://arxiv.org/pdf/1902.05624) .[J] arXiv preprint arXiv:1902.05624.
- Zhiming Zhou, Jiadong Liang, Yuxuan Song, Lantao Yu, Hongwei Wang, Weinan Zhang, Yong Yu, Zhihua Zhang .[Lipschitz Generative Adversarial Nets](https://arxiv.org/pdf/1902.05687) .[J] arXiv preprint arXiv:1902.05687.
- Baris Gecer, Stylianos Ploumpis, Irene Kotsia, Stefanos Zafeiriou .[GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction](https://arxiv.org/pdf/1902.05978) .[J] arXiv preprint arXiv:1902.05978.
- Meiyu Li, Michael D. Chan, Xiaobo Zhou, Xiaohua Qian .[DC-Al GAN: Pseudoprogression and True Tumor Progression of Glioblastoma multiform Image Classification Based On DCGAN and Alexnet](https://arxiv.org/pdf/1902.06085) .[J] arXiv preprint arXiv:1902.06085.
- Zhongnian Li, Tao Zhang, Peng Wan, Daoqiang Zhang .[SEGAN: Structure-Enhanced Generative Adversarial Network for Compressed Sensing MRI Reconstruction](https://arxiv.org/pdf/1902.06455) .[J] arXiv preprint arXiv:1902.06455.
- Stephen G. Odaibo, M.D., M.S. (Math), M.S. (Comp. Sci.) .[Generative Adversarial Networks Synthesize Realistic OCT Images of the Retina](https://arxiv.org/pdf/1902.06676) .[J] arXiv preprint arXiv:1902.06676.
- Rahul Gupta .[Data augmentation for low resource sentiment analysis using generative adversarial networks](https://arxiv.org/pdf/1902.06818) .[J] arXiv preprint arXiv:1902.06818.
- Youngjoo Jo, Jongyoul Park .[SC-FEGAN: Face Editing Generative Adversarial Network with User's Sketch and Color](https://arxiv.org/pdf/1902.06838) .[J] arXiv preprint arXiv:1902.06838.
- Xueqing Deng, Yi Zhu, Shawn Newsam .[Using Conditional Generative Adversarial Networks to Generate Ground-Level Views From Overhead Imagery](https://arxiv.org/pdf/1902.06923) .[J] arXiv preprint arXiv:1902.06923.
- Ce Wang, Zhangling Chen, Kun Shang .[Label-Removed Generative Adversarial Networks Incorporating with K-Means](https://arxiv.org/pdf/1902.06938) .[J] arXiv preprint arXiv:1902.06938.
- Amirhossein Taghvaei, Amin Jalali .[2-Wasserstein Approximation via Restricted Convex Potentials with Application to Improved Training for GANs](https://arxiv.org/pdf/1902.07197) .[J] arXiv preprint arXiv:1902.07197.
- Yusuke Ujitoko, Yuki Ban .[Vibrotactile Signal Generation from Texture Images or Attributes using Generative Adversarial Network](https://arxiv.org/pdf/1902.07480) .[J] arXiv preprint arXiv:1902.07480.
- Zhengchun Liu, Tekin Bicer, Rajkumar Kettimuthu, Doga Gursoy, Francesco De Carlo, Ian Foster .[TomoGAN: Low-Dose X-Ray Tomography with Generative Adversarial Networks](https://arxiv.org/pdf/1902.07582) .[J] arXiv preprint arXiv:1902.07582.
- Jesse Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani, Chris Donahue, Adam Roberts .[GANSynth: Adversarial Neural Audio Synthesis](https://arxiv.org/pdf/1902.08710) .[J] arXiv preprint arXiv:1902.08710.
- Wei Peng, Yuhong Dai, Hui Zhang, Lizhi Cheng .[Training GANs with Centripetal Acceleration](https://arxiv.org/pdf/1902.08949) .[J] arXiv preprint arXiv:1902.08949.
- Jaewoong Cho, Changho Suh .[Wasserstein GAN Can Perform PCA](https://arxiv.org/pdf/1902.09073) .[J] arXiv preprint arXiv:1902.09073.
- Soochan Lee, Junsoo Ha, Gunhee Kim .[Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation](https://arxiv.org/pdf/1902.09225) .[J] arXiv preprint arXiv:1902.09225.
- Steven Cheng-Xian Li, Bo Jiang, Benjamin Marlin .[MisGAN: Learning from Incomplete Data with Generative Adversarial Networks](https://arxiv.org/pdf/1902.09599) .[J] arXiv preprint arXiv:1902.09599.
- Matthew Amodio, Smita Krishnaswamy .[TraVeLGAN: Image-to-image Translation by Transformation Vector Learning](https://arxiv.org/pdf/1902.09631) .[J] arXiv preprint arXiv:1902.09631.
- Ankit Raj, Yuqi Li, Yoram Bresler .[GAN-based Projector for Faster Recovery in Compressed Sensing with Convergence Guarantees](https://arxiv.org/pdf/1902.09698) .[J] arXiv preprint arXiv:1902.09698.
- Qingyan Duan, Lei Zhang .[BoostGAN for Occlusive Profile Face Frontalization and Recognition](https://arxiv.org/pdf/1902.09782) .[J] arXiv preprint arXiv:1902.09782.
- Maximilian Pöpperl, Raghavendra Gulagundi, Senthil Yogamani, Stefan Milz .[Realistic Ultrasonic Environment Simulation Using Conditional Generative Adversarial Networks](https://arxiv.org/pdf/1902.09842) .[J] arXiv preprint arXiv:1902.09842.
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