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Progress in generative modelling, especially generative adversarial networks, have made it possible to efficiently synthesize and alter media at scale.
Wright v. Warner Books
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MANSFIELD HEEREY and HELY JJ · 2002
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Evasion attacks against machine learning at test time
Battista Biggio, Igino Corona, Davide Maiorca, Blaine Nelson, Nedim Šrndić, Pavel Laskov, Giorgio Giacinto, and Fabio Roli · 2013
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Intriguing properties of neural networks
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Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 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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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, and Zbigniew Wojna · 2015
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otree—an open-source platform for laboratory, online, and field experiments
Daniel L. Chen, Martin Schonger, and Chris Wickens · 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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Nips 2016 tutorial: Generative adversarial networks
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Variational autoencoder for deep learning of images, labels and captions
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Improved Techniques for Training GANs
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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Towards principled methods for training generative adversarial networks, 2017
Martin Arjovsky and Léon Bottou · 2017
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Towards evaluating the robustness of neural networks
Nicholas Carlini and David Wagner · 2017
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Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge Belongie · 2017
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
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Provchain: A blockchain-based data provenance architecture in cloud environment with enhanced privacy and availability
X. Liang, S. Shetty, D. Tosh, C. Kamhoua, K. Kwiat, and L. Njilla · 2017
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Semantic image inpainting with deep generative models
Raymond A. Yeh, Chen Chen, Teck Yian Lim, Alexander G. Schwing, Mark Hasegawa-Johnson, and Minh N. Do · 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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Jens Behrmann, David Duvenaud, and Jörn-Henrik Jacobsen · 2018
Analyzing and improving the image quality of stylegan
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2019
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Fsgan: Subject agnostic face swapping and reenactment
Yuval Nirkin, Yosi Keller, and Tal Hassner · 2019
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Generating diverse high-fidelity images with VQ-VAE-2
Ali Razavi, Aäron van den Oord, and Oriol Vinyals · 2019
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Sitatapatra: Blocking the transfer of adversarial samples
Ilia Shumailov, Xitong Gao, Yiren Zhao, Robert D. Mullins, Ross Anderson, and Cheng-Zhong Xu · 2019
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Fraudsters used ai to mimic ceo’s voice in unusual cybercrime case, Aug 2019
Catherine Stupp · 2019
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Generative adversarial networks: An overview
A. Creswell, T. White, V. Dumoulin, K. Arulkumaran, B. Sengupta, and A. A. Bharath · 2018
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Chris Donahue, Julian McAuley, and Miller Puckette · 2018
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Accurate and efficient image forgery detection using lateral chromatic aberration
O. Mayer and M. C. Stamm · 2018
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Poison frogs! targeted clean-label poisoning attacks on neural networks
Ali Shafahi, W. Ronny Huang, Mahyar Najibi, Octavian Suciu, Christoph Studer, Tudor Dumitras, and Tom Goldstein · 2018
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Mocogan: Decomposing motion and content for video generation
Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, and Jan Kautz · 2018
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Attributing fake images to gans: Learning and analyzing gan fingerprints, 2018
Ning Yu, Larry Davis, and Mario Fritz · 2018
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Image2stylegan: How to embed images into the stylegan latent space?
Rameen Abdal, Yipeng Qin, and Peter Wonka · 2019
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Deepfakes, revenge porn, and the impact on women, Nov 2019
Chenxi Wang · 2019
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Cnn-generated images are surprisingly easy to spot… for now
Sheng-Yu Wang, Oliver Wang, Richard Zhang, Andrew Owens, and Alexei A Efros · 2019
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HYPE: human eye perceptual evaluation of generative models
Sharon Zhou, Mitchell L. Gordon, Ranjay Krishna, Austin Narcomey, Durim Morina, and Michael S. Bernstein · 2019
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Enforcing against manipulated media, Jun 2020
Monika Bickert · 2020
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Albumentations: Fast and flexible image augmentations
Alexander Buslaev, Vladimir I. Iglovikov, Eugene Khvedchenya, Alex Parinov, Mikhail Druzhinin, and Alexandr A. Kalinin · 2020
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Evading deepfake-image detectors with white- and black-box attacks
Nicholas Carlini and Hany Farid · 2020
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Leveraging frequency analysis for deep fake image recognition, 2020
Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, and Thorsten Holz · 2020
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Deepfakes and beyond: A survey of face manipulation and fake detection, 2020
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Nvae: A deep hierarchical variational autoencoder, 2020
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Media forensics and deepfakes: an overview, 2020
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An online propaganda campaign used ai-generated headshots to create fake journalists, Jul 2020
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