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Generating realistic images is difficult, and many formulations for this task have been proposed recently.
Neural networks for machine learning
G. Hinton · 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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Conditional generative adversarial nets
M. Mirza and S. Osindero · 2014
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Texture synthesis using convolutional neural networks
L. Gatys, A. S. Ecker, and M. Bethge · 2015
Earlier work this paper cites.
M. Arjovsky, S. Chintala, and L. Bottou · 2017
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Improved training of wasserstein gans
I. Gulrajani, F. Ahmed, M. Arjovsky, V. Dumoulin, and A. C. Courville · 2017
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Progressive growing of gans for improved quality, stability, and variation
T. Karras, T. Aila, S. Laine, and J. Lehtinen · 2017
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Photo-realistic single image super-resolution using a generative adversarial network
C. Ledig, L. Theis, F. Huszár, J. Caballero, A. Cunningham, A. Acosta, A. P. Aitken, A. Tejani, J. Totz, Z. Wang, et al · 2017
Cited alongside, same era.
Enhanced deep residual networks for single image super-resolution
B. Lim, S. Son, H. Kim, S. Nah, and K. M. Lee · 2017
Cited alongside, same era.
Learning a no-reference quality metric for single-image super-resolution
C. Ma, C.-Y. Yang, X. Yang, and M.-H. Yang · 2017
Cited alongside, same era.
Enhancenet: Single image super-resolution through automated texture synthesis
M. S. Sajjadi, B. Schölkopf, and M. Hirsch · 2017
Cited alongside, same era.
Image super-resolution using dense skip connections
T. Tong, G. Li, X. Liu, and Q. Gao · 2017
Cited alongside, same era.
The perception-distortion tradeoff
Y. Blau and T. Michaeli · 2018
To learn image super-resolution, use a gan to learn how to do image degradation first
A. Bulat, J. Yang, and G. Tzimiropoulos · 2018
Later among the works it cites.
The relativistic discriminator: a key element missing from standard gan
A. Jolicoeur-Martineau · 2018
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Learning to maintain natural image statistics
R. Mechrez, I. Talmi, F. Shama, and L. Zelnik-Manor · 2018
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Nima: Neural image assessment
H. Talebi and P. Milanfar · 2018
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Esrgan: Enhanced super-resolution generative adversarial networks
X. Wang, K. Yu, S. Wu, J. Gu, Y. Liu, C. Dong, C. C. Loy, Y. Qiao, and X. Tang · 2018
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Cited alongside, same era.
Later among the works it cites.
A fully progressive approach to single-image super-resolution
Y. Wang, F. Perazzi, B. McWilliams, A. Sorkine-Hornung, O. Sorkine-Hornung, and C. Schroers · 2018
Later among the works it cites.