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The interest of the machine learning community in image synthesis has grown significantly in recent years, with the introduction of a wide range of deep generative models and means for training them.
Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, Li-Jia Li, K. Li, and L. Fei-Fei · 2009
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Learning multiple layers of features from tiny images
A. Krizhevsky · 2012
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Generative Adversarial Nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Auto-Encoding Variational Bayes
D. P. Kingma and M. Welling · 2014
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Conditional Generative Adversarial Nets
M. Mirza and S. Osindero · 2014
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Intriguing properties of neural networks
C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus · 2014
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Explaining and Harnessing Adversarial Examples
I. Goodfellow, J. Shlens, and C. Szegedy · 2015
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Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
A. Radford, L. Metz, and S. Chintala · 2015
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Variational Inference with Normalizing Flows
D. Rezende and S. Mohamed · 2015
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Deep Residual Learning for Image Recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Pixel Recurrent Neural Networks
A. Van Oord, N. Kalchbrenner, and K. Kavukcuoglu · 2016
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Improved Techniques for Training GANs
T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. Chen · 2016
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GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter · 2017
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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros · 2017
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Adversarial examples in the physical world, 2017
A. Kurakin, I. Goodfellow, and S. Bengio · 2017
Cited alongside, same era.
Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks
J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros · 2017
Cited alongside, same era.
Progressive growing of gans for improved quality, stability, and variation
T. Karras, T. Aila, S. Laine, and J. Lehtinen · 2018
Cited alongside, same era.
Towards Deep Learning Models Resistant to Adversarial Attacks
A. Madry, A. Makelov, L. Schmidt, D. Tsipras, and A. Vladu · 2018
Cited alongside, same era.
Spectral Normalization for Generative Adversarial Networks
T. Miyato, T. Kataoka, M. Koyama, and Y. Yoshida · 2018
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Discriminator rejection sampling, 2019
S. Azadi, C. Olsson, T. Darrell, I. Goodfellow, and A. Odena · 2019
Cited alongside, same era.
Robustness May Be at Odds with Accuracy
D. Tsipras, S. Santurkar, L. Engstrom, A. Turner, and A. Madry · 2019
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Metropolis-Hastings generative adversarial networks
R. Turner, J. Hung, E. Frank, Y. Saatchi, and J. Yosinski · 2019
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On the benefits of models with perceptually-aligned gradients
Gunjan Aggarwal, Abhishek Sinha, Nupur Kumari, and Mayank Kumar Singh · 2020
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Denoising diffusion probabilistic models
J. Ho, A. Jain, and P. Abbeel · 2020
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Analyzing and Improving the Image Quality of StyleGAN
T. Karras, S. Laine, M. Aittala, J. Hellsten, J. Lehtinen, and T. Aila · 2020
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Reliable fidelity and diversity metrics for generative models
Muhammad Ferjad Naeem, Seong Joon Oh, Youngjung Uh, Yunjey Choi, and Jaejun Yoo · 2020
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Large Scale GAN Training for High Fidelity Natural Image Synthesis
A. Brock, J. Donahue, and K. Simonyan · 2019
Cited alongside, same era.
Self-Supervised GANs via Auxiliary Rotation Loss
T. Chen, X. Zhai, M. Ritter, M. Lucic, and N. Houlsby · 2019
Cited alongside, same era.
Robustness (python library), 2019
Logan Engstrom, Andrew Ilyas, Hadi Salman, Shibani Santurkar, and Dimitris Tsipras · 2019
Cited alongside, same era.
A style-based generator architecture for generative adversarial networks
T. Karras, S. Laine, and T. Aila · 2019
Cited alongside, same era.
Are perceptually-aligned gradients a general property of robust classifiers?, 10 2019
Simran Kaur, Jeremy Cohen, and Zachary Lipton · 2019
Cited alongside, same era.
Image Synthesis with a Single (Robust) Classifier
S. Santurkar, A. Ilyas, D. Tsipras, L. Engstrom, B. Tran, and A. Madry · 2019
Cited alongside, same era.
Later among the works it cites.
Differentiable augmentation for data-efficient GAN training
S. Zhao, Z. Liu, J. Lin, J.-Y. Zhu, and S. Han · 2020
Later among the works it cites.
Refining deep generative models via discriminator gradient flow, 2021
A. Fatir Ansari, M. Liang Ang, and H. Soh · 2021
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Deep generative modelling: A comparative review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models, 2021
D. Bond-Taylor, A. Leach, Y. Long, and C. G. Willcocks · 2021
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Your gan is secretly an energy-based model and you should use discriminator driven latent sampling, 2021
T. Che, R. Zhang, J. Sohl-Dickstein, H. Larochelle, L. Paull, Y. Cao, and Y. Bengio · 2021
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Diffusion models beat gans on image synthesis
P. Dhariwal and A. Nichol · 2021
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Infomax-gan: Improved adversarial image generation via information maximization and contrastive learning
K. S. Lee, N. T. Tran, and N. M. Cheung · 2021
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Do perceptually aligned gradients imply adversarial robustness?, 2022
Roy Ganz, Bahjat Kawar, and Michael Elad · 2022
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