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While Generative Adversarial Networks (GANs) have seen huge successes in image synthesis tasks, they are notoriously difficult to adapt to different datasets, in part due to instability during training and sensitivity to hyperparameters.
Parallel controllable texture synthesis
Sylvain Lefebvre and Hugues Hoppe · 2005
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Space-time completion of video
Yonatan Wexler, Eli Shechtman, and Michal Irani · 2007
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NICE: non-linear independent components estimation
Laurent Dinh, David Krueger, and Yoshua Bengio · 2014
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Deep generative image models using a laplacian pyramid of adversarial networks
Emily L. Denton, Soumith Chintala, Arthur Szlam, and Rob Fergus · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
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Variational inference with normalizing flows
Danilo Jimenez Rezende and Shakir Mohamed · 2015
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Density estimation using real NVP
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
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Generative multi-adversarial networks
Ishan Durugkar, Ian Gemp, and Sridhar Mahadevan · 2016
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Multi-class generative adversarial networks with the l2 loss function
Xudong Mao, Qing Li, Haoran Xie, Raymond Y. K. Lau, and Zhen Wang · 2016
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Unrolled generative adversarial networks, 2016
Luke Metz, Ben Poole, David Pfau, and Jascha Sohl-Dickstein · 2016
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Improved techniques for training GANs
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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Amortised MAP inference for image super-resolution
Casper Kaae Sønderby, Jose Caballero, Lucas Theis, Wenzhe Shi, and Ferenc Huszár · 2016
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Conditional image generation with pixelcnn decoders
Aaron Van den Oord, Nal Kalchbrenner, Lasse Espeholt, Oriol Vinyals, Alex Graves, et al · 2016
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Pixel recurrent neural networks
Aäron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016
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Towards principled methods for training generative adversarial networks
Martín Arjovsky and Léon Bottou · 2017
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Wasserstein generative adversarial networks
Martín Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Improved training of wasserstein GANs
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
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GANs trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Arbitrary style transfer in real-time with adaptive instance normalization
Progressive growing of GANs for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2018
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Glow: Generative flow with invertible 1x1 convolutions
Durk P Kingma and Prafulla Dhariwal · 2018
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PacGAN: The power of two samples in generative adversarial networks
Zinan Lin, Ashish Khetan, Giulia Fanti, and Sewoong Oh · 2018
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Which training methods for GANs do actually converge?
Lars Mescheder, Sebastian Nowozin, and Andreas Geiger · 2018
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High-resolution image synthesis and semantic manipulation with conditional gans
Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Andrew Tao, Jan Kautz, and Bryan Catanzaro · 2018
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Photographic text-to-image synthesis with a hierarchically-nested adversarial network
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Xun Huang and Serge J. Belongie · 2017
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On convergence and stability of GANs
Naveen Kodali, Jacob Abernethy, James Hays, and Zsolt Kira · 2017
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PixelCNN++: A PixelCNN implementation with discretized logistic mixture likelihood and other modifications
Tim Salimans, Andrej Karpathy, Xi Chen, and Diederik P. Kingma · 2017
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Magan: Margin adaptation for generative adversarial networks
Ruohan Wang, Antoine Cully, Hyung Jin Chang, and Yiannis Demiris · 2017
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Lr-gan: Layered recursive generative adversarial networks for image generation
Jianwei Yang, Anitha Kannan, Dhruv Batra, and Devi Parikh · 2017
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Stackgan++: Realistic image synthesis with stacked generative adversarial networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris Metaxas · 2017
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Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris N. Metaxas · 2017
Cited alongside, same era.
Zizhao Zhang, Yuanpu Xie, and Lin Yang · 2018
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Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
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Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
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The relativistic discriminator: a key element missing from standard GAN
Alexia Jolicoeur-Martineau · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Analyzing and improving the image quality of stylegan, 2019
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2019
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Variational discriminator bottleneck: Improving imitation learning, inverse RL, and GANs by constraining information flow
Xue Bin Peng, Angjoo Kanazawa, Sam Toyer, Pieter Abbeel, and Sergey Levine · 2019
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The unusual effectiveness of averaging in GAN training
Yasin Yazıcı, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, and Vijay Chandrasekhar · 2019
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