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We propose a new method to evaluate GANs, namely EvalGAN.
Elements of Information Theory
Thomas M. Cover and Joy A. Thomas · 1991
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Adam: A Method for Stochastic Optimization
Diederik Kingma and Jimmy Ba · 2014
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Learning in Implicit Generative Models
Shakir Mohamed and Balaji Lakshminarayanan · 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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Context Encoders: Feature Learning by Inpainting
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A. Efros · 2016
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Improved Techniques for Training GANs
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen, and Xi Chen · 2016
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A note on the evaluation of generative models
Lucas Theis, Aäron van den Oord, and Matthias Bethge · 2016
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Generative Visual Manipulation on the Natural Image Manifold
Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, and Alexei A. Efros · 2016
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Wasserstein Generative Adversarial Networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Generalization and Equilibrium in Generative Adversarial Nets (GANs)
Sanjeev Arora, Rong Ge, Yingyu Liang, Tengyu Ma, and Yi Zhang · 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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Deep models under the GAN: information leakage from collaborative deep learning
Briland Hitaj, Giuseppe Ateniese, and Fernando Perez-Cruz · 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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Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, and Wenzhe Shi · 2017
Cited alongside, same era.
AdaGAN: Boosting Generative Models
Ilya O Tolstikhin, Sylvain Gelly, Olivier Bousquet, Carl-Johann Simon-Gabriel, and Bernhard Schölkopf · 2017
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On the Quantitative analysis of Decoder-Based Generative Models
Yuhuai Wu, Yuri Burda, Ruslan Salakhutdinov, and Roger Grosse · 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
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Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
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Pros and Cons of GAN Evaluation Measures
Ali Borji · 2018
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MMD GAN: Towards deeper understanding of moment matching network
Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, and Barnabás Póczos · 2017
Cited alongside, same era.
Approximation and Convergence Properties of Generative Adversarial Learning
Shuang Liu, Olivier Bousquet, and Kamalika Chaudhuri · 2017
Cited alongside, same era.
Revisiting Classifier Two-Sample Tests
David Lopez-Paz and Maxime Oquab · 2017
Cited alongside, same era.
The Numerics of GANs
Lars Mescheder, Sebastian Nowozin, and Andreas Geiger · 2017
Cited alongside, same era.
Unrolled Generative Adversarial Networks
Luke Metz, Ben Poole, David Pfau, and Jascha Sohl-Dickstein · 2017
Cited alongside, same era.
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Christian Szegedy, Sergey Ioffe, and Vincent Vanhoucke · 2017
Cited alongside, same era.
Generative Adversarial Nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio
Cited in the paper.
Quantitatively Evaluating GANs With Divergences Proposed for Training
Daniel J. Im, He Ma, Graham Taylor, and Kristin Branson · 2018
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Informative Features for Model Comparison
Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, and Arthur Gretton · 2018
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Are GANs Created Equal? A Large-Scale Study
Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, and Olivier Bousquet · 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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Fast Cosmic Web Simulations with Generative Adversarial Networks
Andres C Rodriguez, Tomasz Kacprzak, Aurelien Lucchi, Adam Amara, Raphael Sgier, Janis Fluri, Thomas Hofmann, and Alexandre Réfrégier · 2018
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Assessing Generative Models via Precision and Recall
Mehdi S. M. Sajjadi, Olivier Bachem, Mario Lucic, Olivier Bousquet, and Sylvain Gelly · 2018
Later among the works it cites.