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Although Generative Adversarial Networks have shown remarkable performance in image generation, there are some challenges in image realism and convergence speed.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
Earlier work this paper cites.
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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Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 2014
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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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Autoencoding beyond pixels using a learned similarity metric
Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle, and Ole Winther · 2015
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Invertible conditional gans for image editing
Guim Perarnau, Joost Van De Weijer, Bogdan Raducanu, and Jose M Álvarez · 2016
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f-gan: Training generative neural samplers using variational divergence minimization
Sebastian Nowozin, Botond Cseke, and Ryota Tomioka · 2016
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Infogan: Interpretable representation learning by information maximizing generative adversarial nets
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel · 2016
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Perceptual losses for real-time style transfer and super-resolution
Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016
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Combining markov random fields and convolutional neural networks for image synthesis
Chuan Li and Michael Wand · 2016
Cited alongside, same era.
Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2017
Cited alongside, same era.
Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
Cited alongside, same era.
Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
Cited alongside, same era.
Progressive growing of gans for improved quality, stability, and variation
Large scale gan training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2018
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Spectral normalization for generative adversarial networks
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida · 2018
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Which training methods for gans do actually converge?
Lars Mescheder, Andreas Geiger, and Sebastian Nowozin · 2018
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Self-attention generative adversarial networks
Han Zhang, Ian Goodfellow, Dimitris Metaxas, and Augustus Odena · 2018
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A style-based generator architecture for generative adversarial networks
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Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
Cited alongside, same era.
Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Yunjey Choi, Minje Choi, Munyoung Kim, Jung-Woo Ha, Sunghun Kim, and Jaegul Choo · 2018
Cited alongside, same era.
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Wasserstein gan with quadratic transport cost
Huidong Liu, Xianfeng Gu, and Dimitris Samaras · 2019
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Drpan: A novel adversarial network approach for retinal vessel segmentation
Wenli Tu, Wei Hu, Xiaoming Liu, and Juanjuan He · 2019
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