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Recent advances in autoencoders and generative models have given rise to effective video forgery methods, used for generating so-called "deepfakes".
Two-stream neural networks for tampered face detection
Peng Zhou, Xintong Han, Vlad I. Morariu, and Larry S. Davis · 2006
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, and Rob Fergus · 2014
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Explaining and harnessing adversarial examples
Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
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Adversarial images for variational autoencoders
Pedro Tabacof, Julia Tavares, and Eduardo Valle · 2016
Earlier work this paper cites.
Face2face: Real-time face capture and reenactment of RGB videos
Justus Thies, Michael Zollhöfer, Marc Stamminger, Christian Theobalt, and Matthias Nießner · 2016
Earlier work this paper cites.
Adversarial transformation networks: Learning to generate adversarial examples
Shumeet Baluja and Ian Fischer · 2017
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How far are we from solving the 2d & 3d face alignment problem? (and a dataset of 230, 000 3d facial landmarks)
Adrian Bulat and Georgios Tzimiropoulos · 2017
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Towards evaluating the robustness of neural networks
Nicholas Carlini and David A. Wagner · 2017
Earlier work this paper cites.
Real-time neural style transfer for videos
Haozhi Huang, Hao Wang, Wenhan Luo, Lin Ma, Wenhao Jiang, Xiaolong Zhu, Zhifeng Li, and Wei Liu · 2017
Earlier work this paper cites.
Adversarial examples in the physical world
Alexey Kurakin, Ian J. Goodfellow, and Samy Bengio · 2017
Earlier work this paper cites.
Universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Omar Fawzi, and Pascal Frossard · 2017
Cited alongside, same era.
Towards poisoning of deep learning algorithms with back-gradient optimization
Luis Muñoz-González, Battista Biggio, Ambra Demontis, Andrea Paudice, Vasin Wongrassamee, Emil C. Lupu, and Fabio Roli · 2017
Cited alongside, same era.
S 3 {}^{\mbox{3}} fd: Single shot scale-invariant face detector
Shifeng Zhang, Xiangyu Zhu, Zhen Lei, Hailin Shi, Xiaobo Wang, and Stan Z. Li · 2017
Cited alongside, same era.
Threat of adversarial attacks on deep learning in computer vision: A survey
Naveed Akhtar and Ajmal S. Mian · 2018
Cited alongside, same era.
Forensictransfer: Weakly-supervised domain adaptation for forgery detection
Davide Cozzolino, Justus Thies, Andreas Rössler, Christian Riess, Matthias Nießner, and Luisa Verdoliva · 2018
Cited alongside, same era.
Ensemble adversarial training: Attacks and defenses
Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Ian J. Goodfellow, Dan Boneh, and Patrick D. McDaniel · 2018
Later among the works it cites.
Learning to confuse: Generating training time adversarial data with auto-encoder
Ji Feng, Qi-Zhi Cai, and Zhi-Hua Zhou · 2019
Later among the works it cites.
Faceforensics++: Learning to detect manipulated facial images
Andreas Rössler, Davide Cozzolino, Luisa Verdoliva, Christian Riess, Justus Thies, and Matthias Nießner · 2019
Later among the works it cites.
Improving vaes’ robustness to adversarial attack
Matthew Willetts, Alexander Camuto, Tom Rainforth, Stephen Roberts, and Chris Holmes · 2019
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Time flies: Animating a still image with time-lapse video as reference
Chia-Chi Cheng, Hung-Yu Chen, and Wei-Chen Chiu · 2020
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Adversarial attacks on variational autoencoders
George Gondim-Ribeiro, Pedro Tabacof, and Eduardo Valle · 2018
Cited alongside, same era.
Fake face detection methods: Can they be generalized?
Ali Khodabakhsh, Ramachandra Raghavendra, Kiran B. Raja, Pankaj Shivdayal Wasnik, and Christoph Busch · 2018
Cited alongside, same era.
Adversarial examples for generative models
Jernej Kos, Ian Fischer, and Dawn Song · 2018
Cited alongside, same era.
Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2018
Cited alongside, same era.
Detection of gan-generated fake images over social networks
Francesco Marra, Diego Gragnaniello, Davide Cozzolino, and Luisa Verdoliva · 2018
Cited alongside, same era.
Deceiving image-to-image translation networks for autonomous driving with adversarial perturbations
Lin Wang, Wonjune Cho, and Kuk-Jin Yoon
Cited in the paper.
Fakespotter: A simple yet robust baseline for spotting ai-synthesized fake faces
Run Wang, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yihao Huang, Jian Wang, and Yang Liu
Cited in the paper.
iperov · 2020
Closest in time.
Nataniel Ruiz, Sarah Adel Bargal, and Stan Sclaroff · 2020
Closest in time.
Deepfakes are going to wreak havoc on society. we are not prepared., 2020
Rob Toews · 2020
Closest in time.
Deepfakes github., 2020
Torzdf · 2020
Closest in time.
Disrupting image-translation-based deepfake algorithms with adversarial attacks
Chin-Yuan Yeh, Hsi-Wen Chen, Shang-Lun Tsai, and Shang-De Wang · 2020
Closest in time.