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Convolutional neural networks are vulnerable to small $\ell^p$ adversarial attacks, while the human visual system is not.
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Christoph Kayser, Kristina J Nielsen, and Nikos K Logothetis · 2006
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Interesting objects are visually salient
Lior Elazary and Laurent Itti · 2008
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ImageNet: A Large-Scale Hierarchical Image Database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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A review of log-polar imaging for visual perception in robotics
V Javier Traver and Alexandre Bernardino · 2010
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Differential connectivity and response dynamics of excitatory and inhibitory neurons in visual cortex
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Understanding the effective receptive field in deep convolutional neural networks
Wenjie Luo, Yujia Li, Raquel Urtasun, and Richard Zemel · 2016
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Carlos Esteves, Christine Allen-Blanchette, Xiaowei Zhou, and Kostas Daniilidis · 2017
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2017
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Harmonic networks: Deep translation and rotation equivariance
Daniel E Worrall, Stephan J Garbin, Daniyar Turmukhambetov, and Gabriel J Brostow · 2017
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Sonja B Hofer, Ho Ko, Bruno Pichler, Joshua Vogelstein, Hana Ros, Hongkui Zeng, Ed Lein, Nicholas A Lesica, and Thomas D Mrsic-Flogel · 2011
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Gateways of ventral and dorsal streams in mouse visual cortex
Quanxin Wang, Enquan Gao, and Andreas Burkhalter · 2011
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Dynamic integration of information about salience and value for saccadic eye movements
Alexander C. Schütz, Julia Trommershäuser, and Karl R. Gegenfurtner · 2012
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The dynamics of invariant object recognition in the human visual system
Leyla Isik, Ethan M Meyers, Joel Z Leibo, and Tomaso A Poggio · 2013
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Adam: A method for stochastic optimization, 2014
Diederik P. Kingma and Jimmy Ba · 2014
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Recurrent models of visual attention
Volodymyr Mnih, Nicolas Heess, Alex Graves, et al · 2014
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Synthesizing robust adversarial examples
Anish Athalye, Logan Engstrom, Andrew Ilyas, and Kevin Kwok · 2018
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Robustness of rotation-equivariant networks to adversarial perturbations
Beranger Dumont, Simona Maggio, and Pablo Montalvo · 2018
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Adversarial examples that fool both computer vision and time-limited humans, 2018
Gamaleldin F. Elsayed, Shreya Shankar, Brian Cheung, Nicolas Papernot, Alex Kurakin, Ian Goodfellow, and Jascha Sohl-Dickstein · 2018
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Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A Wichmann, and Wieland Brendel · 2018
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Adversarial risk and the dangers of evaluating against weak attacks, 2018
Jonathan Uesato, Brendan O’Donoghue, Aaron van den Oord, and Pushmeet Kohli · 2018
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Spatially transformed adversarial examples
Chaowei Xiao, Jun-Yan Zhu, Bo Li, Warren He, Mingyan Liu, and Dawn Song · 2018
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Approximating CNNs with bag-of-local-features models works surprisingly well on imagenet
Wieland Brendel and Matthias Bethge · 2019
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AdverTorch v0.1: An adversarial robustness toolbox based on pytorch
Gavin Weiguang Ding, Luyu Wang, and Xiaomeng Jin · 2019
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Saccader: Improving accuracy of hard attention models for vision
Gamaleldin Elsayed, Simon Kornblith, and Quoc V Le · 2019
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Discrete attractor dynamics underlies persistent activity in the frontal cortex
Hidehiko K Inagaki, Lorenzo Fontolan, Sandro Romani, and Karel Svoboda · 2019
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Adversarial examples are not bugs, they are features
Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, and Aleksander Madry · 2019
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