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Recently, Generative Adversarial Networks (GANs) and image manipulating methods are becoming more powerful and can produce highly realistic face images beyond human recognition which have raised significant concerns regarding the authenticity of digital media.
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Xception: Deep learning with depthwise separable convolutions
F. Chollet · 2016
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Image-to-image translation with conditional adversarial networks
P. Isola, J.-Y. Zhu, T. Zhou, and A. A. Efros · 2016
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Multi-class generative adversarial networks with the L2 loss function
X. Mao, Q. Li, H. Xie, R. Y. K. Lau, and Z. Wang · 2016
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Unsupervised representation learning with deep convolutional generative adversarial networks, 2015
A. Radford, L. Metz, and S. Chintala · 2016
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Face2face: Real-time face capture and reenactment of rgb videos
J. Thies, M. Zollhofer, M. Stamminger, C. Theobalt, and M. NieBner · 2016
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Mesonet: a compact facial video forgery detection network
D. Afchar, V. Nozick, J. Yamagishi, and I. Echizen · 2018
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J. Deng, Y. Zhou, S. Cheng, and S. Zafeiriou · 2018
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Wasserstein generative adversarial networks
M. Arjovsky, S. Chintala, and L. Bottou · 2017
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CVAE-GAN: fine-grained image generation through asymmetric training
J. Bao, D. Chen, F. Wen, H. Li, and G. Hua · 2017
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Began: Boundary equilibrium generative adversarial networks
D. Berthelot, T. Schumm, and L. Metz · 2017
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Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Y. Choi, M. Choi, M. Kim, J. Ha, S. Kim, and J. Choo · 2017
Cited alongside, same era.
Improved training of wasserstein gans
I. Gulrajani, F. Ahmed, M. Arjovsky, V. Dumoulin, and A. C. Courville · 2017
Cited alongside, same era.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter · 2017
Cited alongside, same era.
Progressive growing of gans for improved quality, stability, and variation
T. Karras, T. Aila, S. Laine, and J. Lehtinen · 2017
Cited alongside, same era.
J. Yu, Z. Lin, J. Yang, X. Shen, X. Lu, and T. S. Huang · 2018
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https://github.com/deepfakes/faceswap
Deepfakes · 2019
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https:http://dlib.net/
Dlip c++ library · 2019
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SC-FEGAN: face editing generative adversarial network with user’s sketch and color
Y. Jo and J. Park · 2019
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FaceForensics++: Learning to detect manipulated facial images
A. Rössler, D. Cozzolino, L. Verdoliva, C. Riess, J. Thies, and M. Nießner · 2019
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Self-supervised model adaptation for multimodal semantic segmentation
A. Valada, R. Mohan, and W. Burgard · 2019
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Exposing gan-synthesized faces using landmark locations
X. Yang, Y. Li, H. Qi, and S. Lyu · 2019
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Self-attention generative adversarial networks
H. Zhang, I. Goodfellow, D. Metaxas, and A. Odena · 2019
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