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Recently, generative adversarial networks (GANs) have achieved stunning realism, fooling even human observers.
Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: · 2014
Earlier work this paper cites.
Unsupervised representation learning with deep convolutional generative adversarial networks
Radford, A., Metz, L., Chintala, S.: · 2015
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Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures
Fredrikson, M., Jha, S., Ristenpart, T.: · 2015
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Deep face recognition
Parkhi, O.M., Vedaldi, A., Zisserman, A.: · 2015
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The megaface benchmark: 1 million faces for recognition at scale
Kemelmacher-Shlizerman, I., Seitz, S.M., Miller, D., Brossard, E.: · 2016
Earlier work this paper cites.
Photo-realistic single image super-resolution using a generative adversarial network
Ledig, C., Theis, L., Huszár, F., Caballero, J., Cunningham, A., Acosta, A., Aitken, A., Tejani, A., Totz, J., Wang, Z., et al.: · 2017
Earlier work this paper cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., Hochreiter, S.: · 2017
Earlier work this paper cites.
Generalization and equilibrium in generative adversarial nets (gans)
Arora, S., Ge, R., Liang, Y., Ma, T., Zhang, Y.: · 2017
Earlier work this paper cites.
Arjovsky, M., Chintala, S., Bottou, L.: · 2017
Earlier work this paper cites.
Machine Learning Models that Remember Too Much
Song, C., Ristenpart, T., Shmatikov, V.: · 2017
Earlier work this paper cites.
Membership Inference Attacks Against Machine Learning Models
Shokri, R., Stronati, M., Song, C., Shmatikov, V.: · 2017
Earlier work this paper cites.
Least squares generative adversarial networks
Mao, X., Li, Q., Xie, H., Lau, R.Y., Wang, Z., Paul Smolley, S.: · 2017
Cited alongside, same era.
Generative image inpainting with contextual attention
Yu, J., Lin, Z., Yang, J., Shen, X., Lu, X., Huang, T.S.: · 2018
Cited alongside, same era.
Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Choi, Y., Choi, M., Kim, M., Ha, J.W., Kim, S., Choo, J.: · 2018
Cited alongside, same era.
Assessing generative models via precision and recall
Sajjadi, M.S., Bachem, O., Lucic, M., Bousquet, O., Gelly, S.: · 2018
Cited alongside, same era.
Large scale gan training for high fidelity natural image synthesis
Brock, A., Donahue, J., Simonyan, K.: · 2018
Cited alongside, same era.
Faceid-gan: Learning a symmetry three-player gan for identity-preserving face synthesis
Large-scale celebfaces attributes (celeba) dataset
Liu, Z., Luo, P., Wang, X., Tang, X.: · 2018
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Deep face recognition: A survey
Wang, M., Deng, W.: · 2018
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Detecting overfitting of deep generative networks via latent recovery
Webster, R., Rabin, J., Simon, L., Jurie, F.: · 2019
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Revisiting precision recall definition for generative modeling
Simon, L., Webster, R., Rabin, J.: · 2019
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A style-based generator architecture for generative adversarial networks
Karras, T., Laine, S., Aila, T.: · 2019
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LOGAN: Membership Inference Attacks Against Generative Models
Hayes, J., Melis, L., Danezis, G., Cristofaro, E.D.: · 2019
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Shen, Y., Luo, P., Yan, J., Wang, X., Tang, X.: · 2018
Cited alongside, same era.
Differentially private generative adversarial network
Xie, L., Lin, K., Wang, S., Wang, F., Zhou, J.: · 2018
Cited alongside, same era.
Inference Attacks Against Collaborative Learning
Melis, L., Song, C., De Cristofaro, E., Shmatikov, V.: · 2018
Cited alongside, same era.
Performing Co-Membership Attacks Against Deep Generative Models
Liu, K.S., Li, B., Gao, J.: · 2018
Cited alongside, same era.
Optimizing the latent space of generative networks
Bojanowski, P., Joulin, A., Lopez-Paz, D., Szlam, A.: · 2018
Cited alongside, same era.
Vggface2: A dataset for recognising faces across pose and age
Cao, Q., Shen, L., Xie, W., Parkhi, O.M., Zisserman, A.: · 2018
Cited alongside, same era.
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PATE-GAN: Generating synthetic data with differential privacy guarantees
Jordon, J., Yoon, J., van der Schaar, M.: · 2019
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Generating private data surrogates for vision related tasks
Webster, R., Rabin, J., Simon, L., Jurie, F.: · 2019
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The secret sharer: Evaluating and testing unintended memorization in neural networks
Carlini, N., Liu, C., Erlingsson, Ú., Kos, J., Song, D.: · 2019
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Exploiting Unintended Feature Leakage in Collaborative Learning
Melis, L., Song, C., De Cristofaro, E., Shmatikov, V.: · 2019
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White-box vs Black-box: Bayes Optimal Strategies for Membership Inference
Sablayrolles, A., Douze, M., Ollivier, Y., Schmid, C., Jégou, H.: · 2019
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