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Class labels have been empirically shown useful in improving the sample quality of generative adversarial nets (GANs).
Multiscale structural similarity for image quality assessment
Wang, Zhou, Simoncelli, Eero P, and Bovik, Alan C · 2004
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Visualizing higher-layer features of a deep network
Erhan, Dumitru, Bengio, Yoshua, Courville, Aaron, and Vincent, Pascal · 2009
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Generative adversarial nets
Goodfellow, Ian, Pouget-Abadie, Jean, Mirza, Mehdi, Xu, Bing, Warde-Farley, David, Ozair, Sherjil, Courville, Aaron, and Bengio, Yoshua · 2014
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Deep generative image models using a laplacian pyramid of adversarial networks
Denton, Emily L, Chintala, Soumith, Fergus, Rob, et al · 2015
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Unsupervised and semi-supervised learning with categorical generative adversarial networks
Springenberg, Jost Tobias · 2015
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A note on the evaluation of generative models
Theis, Lucas, Oord, Aäron van den, and Bethge, Matthias · 2015
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Mode regularized generative adversarial networks
Che, Tong, Li, Yanran, Jacob, Athul Paul, Bengio, Yoshua, and Li, Wenjie · 2016
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Nips 2016 tutorial: Generative adversarial networks
Goodfellow, Ian · 2016
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Image-to-image translation with conditional adversarial networks
Isola, Phillip, Zhu, Jun-Yan, Zhou, Tinghui, and Efros, Alexei A · 2016
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Least squares generative adversarial networks
Mao, Xudong, Li, Qing, Xie, Haoran, Lau, Raymond YK, Wang, Zhen, and Smolley, Stephen Paul · 2016
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Conditional image synthesis with auxiliary classifier gans
Odena, Augustus, Olah, Christopher, and Shlens, Jonathon · 2016
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Improved techniques for training gans
Salimans, Tim, Goodfellow, Ian, Zaremba, Wojciech, Cheung, Vicki, Radford, Alec, and Chen, Xi · 2016
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Rethinking the inception architecture for computer vision
Szegedy, Christian, Vanhoucke, Vincent, Ioffe, Sergey, Shlens, Jon, and Wojna, Zbigniew · 2016
Towards principled methods for training generative adversarial networks
Arjovsky, Martin and Bottou, Léon · 2017
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Arjovsky, Martin, Chintala, Soumith, and Bottou, Léon · 2017
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Unsupervised diverse colorization via generative adversarial networks
Cao, Yun, Zhou, Zhiming, Zhang, Weinan, and Yu, Yong · 2017
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Class-splitting generative adversarial networks
Guillermo, L. Grinblat, Lucas, C. Uzal, and Pablo, M. Granitto · 2017
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Improved training of wasserstein gans
Gulrajani, Ishaan, Ahmed, Faruk, Arjovsky, Martin, Dumoulin, Vincent, and Courville, Aaron · 2017
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Seqgan: sequence generative adversarial nets with policy gradient
Yu, Lantao, Zhang, Weinan, Wang, Jun, and Yu, Yong · 2016
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Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
Zhang, Han, Xu, Tao, Li, Hongsheng, Zhang, Shaoting, Huang, Xiaolei, Wang, Xiaogang, and Metaxas, Dimitris · 2016
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Generative visual manipulation on the natural image manifold
Zhu, Jun-Yan, Krähenbühl, Philipp, Shechtman, Eli, and Efros, Alexei A · 2016
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Densely connected convolutional networks
Huang, Gao, Liu, Zhuang, Weinberger, Kilian Q, and van der Maaten, Laurens
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Stacked generative adversarial networks
Huang, Xun, Li, Yixuan, Poursaeed, Omid, Hopcroft, John, and Belongie, Serge
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Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
Nguyen, Anh, Dosovitskiy, Alexey, Yosinski, Jason, Brox, Thomas, and Clune, Jeff
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Plug & play generative networks: Conditional iterative generation of images in latent space
Nguyen, Anh, Yosinski, Jason, Bengio, Yoshua, Dosovitskiy, Alexey, and Clune, Jeff
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Heusel, Martin, Ramsauer, Hubert, Unterthiner, Thomas, Nessler, Bernhard, Klambauer, Günter, and Hochreiter, Sepp · 2017
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Progressive growing of gans for improved quality, stability, and variation
Karras, Tero, Aila, Timo, Laine, Samuli, and Lehtinen, Jaakko · 2017
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Improving generative adversarial networks with denoising feature matching
Warde-Farley, D. and Bengio, Y · 2017
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