Fetching the paper…
Reading the bibliography…
Thanks to their remarkable generative capabilities, GANs have gained great popularity, and are used abundantly in state-of-the-art methods and applications.
Learning multiple layers of features from tiny images
A. Krizhevsky and G. Hinton · 2009
Earlier work this paper cites.
Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
Earlier work this paper cites.
Autoencoding beyond pixels using a learned similarity metric
A. B. L. Larsen, S. K. Sønderby, H. Larochelle, and O. Winther · 2015
Earlier work this paper cites.
Deep learning face attributes in the wild
Z. Liu, P. Luo, X. Wang, and X. Tang · 2015
Earlier work this paper cites.
Training a feedback loop for hand pose estimation
M. Oberweger, P. Wohlhart, and V. Lepetit · 2015
Earlier work this paper cites.
Human pose estimation with iterative error feedback
J. Carreira, P. Agrawal, K. Fragkiadaki, and J. Malik · 2016
Earlier work this paper cites.
Generating images with perceptual similarity metrics based on deep networks
A. Dosovitskiy and T. Brox · 2016
Earlier work this paper cites.
Iterative instance segmentation
K. Li, B. Hariharan, and J. Malik · 2016
Earlier work this paper cites.
Deep predictive coding networks for video prediction and unsupervised learning
W. Lotter, G. Kreiman, and D. Cox · 2016
Earlier work this paper cites.
Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2016
Earlier work this paper cites.
Generative adversarial text to image synthesis
S. Reed, Z. Akata, X. Yan, L. Logeswaran, B. Schiele, and H. Lee · 2016
Cited alongside, same era.
Improved techniques for training gans
T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. Chen · 2016
Cited alongside, same era.
M. Arjovsky, S. Chintala, and L. Bottou · 2017
Cited alongside, same era.
Improved training of wasserstein gans
I. Gulrajani, F. Ahmed, M. Arjovsky, V. Dumoulin, and A. C. Courville · 2017
Cited alongside, same era.
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
Cited alongside, same era.
Image-to-image translation with conditional adversarial networks
P. Isola, J.-Y. Zhu, T. Zhou, and A. A. Efros · 2017
Feedback networks
A. R. Zamir, T.-L. Wu, L. Sun, W. B. Shen, B. E. Shi, J. Malik, and S. Savarese · 2017
Later among the works it cites.
Unpaired image-to-image translation using cycle-consistent adversarial networks
J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros · 2017
Later among the works it cites.
2018 pirm challenge on perceptual image super-resolution
Y. Blau, R. Mechrez, R. Timofte, T. Michaeli, and L. Zelnik-Manor · 2018
Closest in time.
Pros and cons of gan evaluation measures
A. Borji · 2018
Closest in time.
Deep backprojection networks for super-resolution
M. Haris, G. Shakhnarovich, and N. Ukita · 2018
Closest in time.
An empirical study on evaluation metrics of generative adversarial networks
G. Huang, Y. Yuan, Q. Xu, C. Guo, Y. Sun, F. Wu, and K. Weinberger · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
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.
Ntire 2017 challenge on single image super-resolution: Methods and results
R. Timofte, E. Agustsson, L. Van Gool, M.-H. Yang, L. Zhang, B. Lim, S. Son, H. Kim, S. Nah, K. M. Lee, et al · 2017
Cited alongside, same era.
High-resolution image synthesis and semantic manipulation with conditional gans
T.-C. Wang, M.-Y. Liu, J.-Y. Zhu, A. Tao, J. Kautz, and B. Catanzaro · 2017
Cited alongside, same era.
Lr-gan: Layered recursive generative adversarial networks for image generation
J. Yang, A. Kannan, D. Batra, and D. Parikh · 2017
Cited alongside, same era.
Perceptual losses for real-time style transfer and super-resolution
J. Johnson, A. Alahi, and L. Fei-Fei
Cited in the paper.
Closest in time.
The relativistic discriminator: a key element missing from standard gan
A. Jolicoeur-Martineau · 2018
Closest in time.
Spectral normalization for generative adversarial networks
T. Miyato, T. Kataoka, M. Koyama, and Y. Yoshida · 2018
Closest in time.
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
Closest in time.