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Though CNNs have achieved the state-of-the-art performance on various vision tasks, they are vulnerable to adversarial examples --- crafted by adding human-imperceptible perturbations to clean images.
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A. Shrivastava, A. Gupta, and R. Girshick · 2016
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Rethinking the inception architecture for computer vision
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On the robustness of semantic segmentation models to adversarial attacks
A. Arnab, O. Miksik, and P. H. Torr · 2017
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N. Carlini and D. Wagner · 2017
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Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 2017
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Inception-v4, inception-resnet and the impact of residual connections on learning
C. Szegedy, S. Ioffe, V. Vanhoucke, and A. A. Alemi · 2017
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Adversarial Examples for Semantic Segmentation and Object Detection
C. Xie, J. Wang, Z. Zhang, Y. Zhou, L. Xie, and A. Yuille · 2017
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Synthesizing robust adversarial examples
A. Athalye, L. Engstrom, A. Ilyas, and K. Kwok · 2018
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M. Cisse, Y. Adi, N. Neverova, and J. Keshet · 2017
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Boosting adversarial attacks with momentum
Y. Dong, F. Liao, T. Pang, H. Su, X. Hu, J. Li, and J. Zhu · 2017
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Adversarial examples in the physical world
A. Kurakin, I. Goodfellow, and S. Bengio · 2017
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Adversarial machine learning at scale
A. Kurakin, I. Goodfellow, and S. Bengio · 2017
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Tactics of adversarial attack on deep reinforcement learning agents
Y.-C. Lin, Z.-W. Hong, Y.-H. Liao, M.-L. Shih, M.-Y. Liu, and M. Sun · 2017
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Delving into transferable adversarial examples and black-box attacks
Y. Liu, X. Chen, C. Liu, and D. Song · 2017
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Magnet: a two-pronged defense against adversarial examples
D. Meng and H. Chen · 2017
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Stochastic activation pruning for robust adversarial defense
G. S. Dhillon, K. Azizzadenesheli, J. D. Bernstein, J. Kossaifi, A. Khanna, Z. C. Lipton, and A. Anandkumar · 2018
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Countering adversarial images using input transformations
C. Guo, M. Rana, M. Cissé, and L. van der Maaten · 2018
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Adversarial attacks and defences competition
A. Kurakin, I. Goodfellow, S. Bengio, Y. Dong, F. Liao, M. Liang, T. Pang, J. Zhu, X. Hu, C. Xie, et al · 2018
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Defense against adversarial attacks using high-level representation guided denoiser
F. Liao, M. Liang, Y. Dong, T. Pang, X. Hu, and J. Zhu · 2018
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cleverhans v2.1.0: an adversarial machine learning library
N. Papernot, F. Faghri, N. Carlini, I. Goodfellow, R. Feinman, A. Kurakin, C. Xie, Y. Sharma, T. Brown, A. Roy, A. Matyasko, V. Behzadan, K. Hambardzumyan, Z. Zhang, Y.-L. Juang, Z. Li, R. Sheatsley, A. Garg, J. Uesato, W. Gierke, Y. Dong, D. Berthelot, P. Hendricks, J. Rauber, and R. Long · 2018
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Deflecting adversarial attacks with pixel deflection
A. Prakash, N. Moran, S. Garber, A. DiLillo, and J. Storer · 2018
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Defense-GAN: Protecting classifiers against adversarial attacks using generative models
P. Samangouei, M. Kabkab, and R. Chellappa · 2018
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Mitigating adversarial effects through randomization
C. Xie, J. Wang, Z. Zhang, Z. Ren, and A. Yuille · 2018
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