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Recent advances in deep generative models for photo-realistic images have led to high quality visual results.
Unmasking DeepFakes with simple Features
Durall, R.; Keuper, M.; Pfreundt, F.-J.; and Keuper, J. 2019 · 1911
Earlier work this paper cites.
Analyzing and improving the image quality of stylegan
Karras, T.; Laine, S.; Aittala, M.; Hellsten, J.; Lehtinen, J.; and Aila, T. 2019 · 1912
Earlier work this paper cites.
Stackgan++: Realistic image synthesis with stacked generative adversarial networks
Zhang, H.; Xu, T.; Li, H.; Zhang, S.; Wang, X.; Huang, X.; and Metaxas, D. N. 2018 · 1962
Earlier work this paper cites.
An introduction to harmonic analysis
Katznelson, Y. 2004 · 2004
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Generative adversarial nets
Goodfellow, I.; Pouget-Abadie, J.; Mirza, M.; Xu, B.; Warde-Farley, D.; Ozair, S.; Courville, A.; and Bengio, Y. 2014 · 2014
Earlier work this paper cites.
Conditional generative adversarial nets
Mirza, M.; and Osindero, S. 2014 · 2014
Earlier work this paper cites.
Unsupervised representation learning with deep convolutional generative adversarial networks
Radford, A.; Metz, L.; and Chintala, S. 2015 · 2015
Earlier work this paper cites.
Donahue, J.; Krähenbühl, P.; and Darrell, T. 2016 · 2016
Earlier work this paper cites.
Context encoders: Feature learning by inpainting
Pathak, D.; Krahenbuhl, P.; Donahue, J.; Darrell, T.; and Efros, A. A. 2016 · 2016
Earlier work this paper cites.
Generative Adversarial Text to Image Synthesis
Reed, S.; Akata, Z.; Yan, X.; Logeswaran, L.; Schiele, B.; and Lee, H. 2016 · 2016
Earlier work this paper cites.
Arjovsky, M.; Chintala, S.; and Bottou, L. 2017 · 2017
Cited alongside, same era.
Towards diverse and natural image descriptions via a conditional gan
Dai, B.; Fidler, S.; Urtasun, R.; and Lin, D. 2017 · 2017
Cited alongside, same era.
Deligan: Generative adversarial networks for diverse and limited data
Gurumurthy, S.; Kiran Sarvadevabhatla, R.; and Venkatesh Babu, R. 2017 · 2017
Cited alongside, same era.
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
Heusel, M.; Ramsauer, H.; Unterthiner, T.; Nessler, B.; and Hochreiter, S. 2017 · 2017
Cited alongside, same era.
Globally and locally consistent image completion
Iizuka, S.; Simo-Serra, E.; and Ishikawa, H. 2017 · 2017
Cited alongside, same era.
Image-to-image translation with conditional adversarial networks
Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Choi, Y.; Choi, M.; Kim, M.; Ha, J.-W.; Kim, S.; and Choo, J. 2018 · 2018
Later among the works it cites.
Multimodal unsupervised image-to-image translation
Huang, X.; Liu, M.-Y.; Belongie, S.; and Kautz, J. 2018 · 2018
Later among the works it cites.
Spectral normalization for generative adversarial networks
Miyato, T.; Kataoka, T.; Koyama, M.; and Yoshida, Y. 2018 · 2018
Later among the works it cites.
Instance-aware Image-to-Image Translation
Mo, S.; Cho, M.; and Shin, J. 2019 · 2019
Later among the works it cites.
Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints
Yu, N.; Davis, L.; and Fritz, M. 2019 · 2019
Later among the works it cites.
Fake Generated Painting Detection via Frequency Analysis
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Isola, P.; Zhu, J.-Y.; Zhou, T.; and Efros, A. A. 2017 · 2017
Cited alongside, same era.
Progressive growing of gans for improved quality, stability, and variation
Karras, T.; Aila, T.; Laine, S.; and Lehtinen, J. 2017 · 2017
Cited alongside, same era.
On convergence and stability of gans
Kodali, N.; Abernethy, J.; Hays, J.; and Kira, Z. 2017 · 2017
Cited alongside, same era.
Least squares generative adversarial networks
Mao, X.; Li, Q.; Xie, H.; Lau, R. Y.; Wang, Z.; and Paul Smolley, S. 2017 · 2017
Cited alongside, same era.
Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
Zhang, H.; Xu, T.; Li, H.; Zhang, S.; Wang, X.; Huang, X.; and Metaxas, D. N. 2017 · 2017
Cited alongside, same era.
Large scale gan training for high fidelity natural image synthesis
Brock, A.; Donahue, J.; and Simonyan, K. 2018a
Cited in the paper.
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Brock, A.; Donahue, J.; and Simonyan, K. 2018b
Cited in the paper.
Bai, Y.; Guo, Y.; Wei, J.; Lu, L.; Wang, R.; and Wang, Y. 2020 · 2020
Closest in time.
Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are failing to reproduce Spectral Distributions
Durall, R.; Keuper, M.; and Keuper, J. 2020 · 2020
Closest in time.
Leveraging Frequency Analysis for Deep Fake Image Recognition
Frank, J.; Eisenhofer, T.; Schönherr, L.; Fischer, A.; Kolossa, D.; and Holz, T. 2020 · 2020
Closest in time.
CNN-Generated Images Are Surprisingly Easy to Spot… for Now
Wang, S.-Y.; Wang, O.; Zhang, R.; Owens, A.; and Efros, A. A. 2020 · 2020
Closest in time.