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With the broad use of face recognition, its weakness gradually emerges that it is able to be attacked.
Labeled faces in the wild: A database for studying face recognition in unconstrained environments
G. B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller · 2007
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Intriguing properties of neural networks
C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus · 2013
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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Explaining and harnessing adversarial examples
I. J. Goodfellow, J. Shlens, and C. Szegedy · 2014
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Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
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Deep learning face representation by joint identification-verification
Y. Sun, X. Wang, and X. Tang · 2014
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Deep learning face representation from predicting 10,000 classes
Y. Sun, X. Wang, and X. Tang · 2014
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Deepface: Closing the gap to human-level performance in face verification
Y. Taigman, M. Yang, M. Ranzato, and L. Wolf · 2014
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Webscale training for face identification
Y. Taigman, M. Yang, M. Ranzato, and L. Wolf · 2014
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Learning face representation from scratch
D. Yi, Z. Lei, S. Liao, and S. Z. Li · 2014
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Deep generative image models using a laplacian pyramid of adversarial networks
E. L. Denton, S. Chintala, R. Fergus, and et al · 2015
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Learning with a strong adversary
R. Huang, B. Xu, D. Schuurmans, and C. S. ́ri · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2015
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Learning structured output representation using deep conditional generative models
K. Sohn, X. Yan, and H. Lee · 2015
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Deepid3: Face recognition with very deep neural networks
Y. Sun, D. Liang, X. Wang, and X. Tan · 2015
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Deeply learned face representations are sparse, selective, and robust
Y. Sun, X. Wang, and X. Tang · 2015
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Image style transfer using convolutional neural networks
L. A. Gatys, A. S. Ecker, and M. Bethge · 2016
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Ms-celeb-1m: A dataset and benchmark for large-scale face recognition
Y. Guo, L. Zhang, Y. Hu, X. He, and J. Gao · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Perceptual losses for real-time style transfer and super-resolution
J. Johnson, A. Alahi, and L. Fei-Fei · 2016
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Disentangling factors of variation in deep representation using adversarial training
M. F. Mathieu, J. Zhao, A. Ramesh, P. Sprechmann, and Y. LeCun · 2016
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Distributional smoothing with virtual adversarial training
T. Miyato, S. i. Maeda, M. Koyama, K. Nakae, and S. Ishii · 2016
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Universal adversarial perturbations
S. Moosavi-Dezfooli, A. Fawzi, O. Fawzi, and P. Frossard · 2016
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Deepfool: a simple and accurate method to fool deep neural networks
Image- to-image translation with conditional adversarial networks
P. Isola, J.-Y. Zhu, T. Zhou, and A. A. Efros · 2017
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Geometric robustness of deep networks: analysis and improvement
C. Kanbak, S.-M. Moosavi-Dezfooli, and P. Frossard · 2017
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Sphereface: Deep hypersphere embedding for face recognition
W. Liu, Y. Wen, Z. Yu, M. Li, B. Raj, and L. Song · 2017
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Universal adversarial perturbations
S. M. Moosavi-Dezfooli, A. Fawzi, O. Fawzi, and P. Frossard · 2017
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One pixel attack for fooling deep neural networks
J. Su, D. V. Vargas, and K. Sakurai · 2017
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S.-M. Moosavi-Dezfooli, A. Fawzi, and P. Frossard · 2016
Cited alongside, same era.
Improved techniques for training gans
T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. Chen · 2016
Cited alongside, same era.
Accessorize to a crime: Real and stealthy attacks on state-of-the-art face recognition
M. Sharif, S. Bhagavatula, L. Bauer, and M. K. Reiter · 2016
Cited alongside, same era.
Sparsifying neural network connections for face recognition
Y. Sun, X. Wang, and X. Tang · 2016
Cited alongside, same era.
Texture networks: Feed-forward synthesis of textures and stylized images
D. Ulyanov, V. Lebedev, A. Vedaldi, and V. Lempitsky · 2016
Cited alongside, same era.
A discriminative feature learning approach for deep face recognition
Y. Wen, K. Zhang, Z. Li, and Y. Qiao · 2016
Cited alongside, same era.
Attribute2image: Conditional image generation from visual attributes
X. Yan, J. Yang, K. Sohn, and H. Lee · 2016
Cited alongside, same era.
X. Wang, R. Girshick, A. Gupta, and K. He · 2017
Later among the works it cites.
Unpaired image-to-image translation using cycle-consistent adversarial networks
J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros · 2017
Later among the works it cites.
Toward multimodal image-to-image translation
J.-Y. Zhu, R. Zhang, D. Pathak, T. Darrell, A. A. Efros, O. Wang, and E. Shechtman · 2017
Later among the works it cites.
Threat of adversarial attacks on deep learning in computer vision: A survey
N. Akhtar and A. Mian · 2018
Closest in time.
Adversarial attacks on face detectors using neural net based constrained optimization
A. Bose and P. Aarabi · 2018
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Mobilefacenets: Efficient cnns for accurate real-time face verification on mobile devices
S. Chen, Y. Liu, X. Gao, and Z. Han · 2018
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Fast geometrically-perturbed adversarial faces
A. Dabouei, S. Soleymani, J. Dawson, and N. M. Nasrabadi · 2018
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Arcface: Additive angular margin loss for deep face recognition
J. Deng, J. Guo, and S. Zafeiriou · 2018
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Unravelling robustness of deep learning based face recognition against adversarial attacks
G. Goswami, N. Ratha, A. Agarwal, R. Singh, and M. Vatsa · 2018
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Adversarial generative nets: Neural network attacks on state-of-the-art face recognition
M. Sharif, S. Bhagavatula, L. Bauer, and M. K. Reiter · 2018
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Additive margin softmax for face verification
F. Wang, W. Liu, H. Liu, and J. Cheng · 2018
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Spatially transformed adversarial examples
C. Xiao, J.-Y. Zhu, B. Li, W. He, M. Liu, and D. Song · 2018
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