Fetching the paper…
Reading the bibliography…
To operate in real-world high-stakes environments, deep learning systems have to endure noises that have been continuously thwarting their robustness.
Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
Earlier work this paper cites.
Context-aware saliency detection
Stas Goferman, Lihi Zelnik-Manor, and Ayellet Tal · 2011
Earlier work this paper cites.
The german traffic sign recognition benchmark: a multi-class classification competition
Johannes Stallkamp, Marc Schlipsing, Jan Salmen, and Christian Igel · 2011
Earlier work this paper cites.
Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
Earlier work this paper cites.
Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Zisserman A Simonyan K · 2014
Earlier work this paper cites.
Sparse malicious false data injection attacks and defense mechanisms in smart grids
Jinping Hao, Robert J Piechocki, Dritan Kaleshi, Woon Hau Chin, and Zhong Fan · 2015
Earlier work this paper cites.
Image style transfer using convolutional neural networks
L. A. Gatys, A. S. Ecker, and M. Bethge · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Distillation as a defense to adversarial perturbations against deep neural networks
Nicolas Papernot, Patrick McDaniel, Xi Wu, Somesh Jha, and Ananthram Swami · 2016
Earlier work this paper cites.
Tom B Brown, Dandelion Mané, Aurko Roy, Martín Abadi, and Justin Gilmer · 2017
Earlier work this paper cites.
Adversarial and clean data are not twins
Zhitao Gong, Wenlu Wang, and Wei-Shinn Ku · 2017
Earlier work this paper cites.
On the (statistical) detection of adversarial examples
Kathrin Grosse, Praveen Manoharan, Nicolas Papernot, Michael Backes, and Patrick McDaniel · 2017
Earlier work this paper cites.
Countering adversarial images using input transformations
Chuan Guo, Mayank Rana, Moustapha Cisse, and Laurens Van Der Maaten · 2017
Earlier work this paper cites.
Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2017
Earlier work this paper cites.
Towards deep learning models resistant to adversarial attacks
A. Madry, A. Makelov, L. Schmidt, D. Tsipras, and A. Vladu · 2017
Earlier work this paper cites.
Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
Earlier work this paper cites.
Ensemble adversarial training: Attacks and defenses
Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Ian Goodfellow, Dan Boneh, and Patrick McDaniel · 2017
Earlier work this paper cites.
Mitigating adversarial effects through randomization
Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, and Alan Yuille · 2017
Earlier work this paper cites.
Mitigating adversarial effects through randomization
Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, and Alan L. Yuille · 2017
Cited alongside, same era.
Stochastic activation pruning for robust adversarial defense
Guneet S Dhillon, Kamyar Azizzadenesheli, Zachary C Lipton, Jeremy Bernstein, Jean Kossaifi, Aran Khanna, and Anima Anandkumar · 2018
Cited alongside, same era.
Shufflenet v2: Practical guidelines for efficient cnn architecture design
Ningning Ma, Xiangyu Zhang, Hai-Tao Zheng, and Jian Sun · 2018
Cited alongside, same era.
Defense-gan: Protecting classifiers against adversarial attacks using generative models
Pouya Samangouei, Maya Kabkab, and Rama Chellappa · 2018
Cited alongside, same era.
Behind the face of holistic perception: Holistic processing of gestalt stimuli and faces recruit overlapping perceptual mechanisms
Unadversarial examples: Designing objects for robust vision
Hadi Salman, Andrew Ilyas, Logan Engstrom, Sai Vemprala, Aleksander Madry, and Ashish Kapoor · 2020
Later among the works it cites.
Fast is better than free: Revisiting adversarial training
Eric Wong, Leslie Rice, and J Zico Kolter · 2020
Later among the works it cites.
Patchguard: Provable defense against adversarial patches using masks on small receptive fields
C. Xiang, A. N. Bhagoji, V. Sehwag, and P. Mittal · 2020
Later among the works it cites.
Cihang Xie, Mingxing Tan, Boqing Gong, Alan Yuille, and Quoc V Le · 2020
Later among the works it cites.
Adversarial laser beam: Effective physical-world attack to dnns in a blink
Ranjie Duan, Xiaofeng Mao, A Kai Qin, Yuefeng Chen, Shaokai Ye, Yuan He, and Yun Yang · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Kim M Curby and Denise Moerel · 2019
Cited alongside, same era.
Benchmarking neural network robustness to common corruptions and perturbations
Dan Hendrycks and Thomas Dietterich · 2019
Cited alongside, same era.
Searching for mobilenetv3
Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, et al · 2019
Cited alongside, same era.
Comdefend: An efficient image compression model to defend adversarial examples
Xiaojun Jia, Xingxing Wei, Xiaochun Cao, and Hassan Foroosh · 2019
Cited alongside, same era.
Do neural networks show gestalt phenomena? an exploration of the law of closure
Been Kim, Emily Reif, Martin Wattenberg, and Samy Bengio · 2019
Cited alongside, same era.
Perceptual-sensitive gan for generating adversarial patches
Aishan Liu, Xianglong Liu, Jiaxin Fan, Yuqing Ma, Anlan Zhang, Huiyuan Xie, and Dacheng Tao · 2019
Cited alongside, same era.
Adversarial training for free!
Ali Shafahi, Mahyar Najibi, Amin Ghiasi, Zheng Xu, John Dickerson, Christoph Studer, Larry S Davis, Gavin Taylor, and Tom Goldstein · 2019
Cited alongside, same era.
Adversarial fine-grained composition learning for unseen attribute-object recognition
Kun Wei, Muli Yang, Hao Wang, Cheng Deng, and Xianglong Liu · 2019
Cited alongside, same era.
Later among the works it cites.
Natural adversarial examples
Dan Hendrycks, Kevin Zhao, Steven Basart, Jacob Steinhardt, and Dawn Song · 2021
Later among the works it cites.
Multi-branch deep radial basis function networks for facial emotion recognition
Fernanda Hernández-Luquin and Hugo Jair Escalante · 2021
Later among the works it cites.
25 astonishing self-driving car statistics for 2021
Alex Kopestinsky · 2021
Later among the works it cites.
Robust sclera recognition based on a local spherical structure
Sanghak Lee, Cheng Yaw Low, Jaihie Kim, and Andrew Beng Jin Teoh · 2021
Later among the works it cites.
Generalized zero-shot learning via disentangled representation
Xiangyu Li, Zhe Xu, Kun Wei, and Cheng Deng · 2021
Later among the works it cites.
Training robust deep neural networks via adversarial noise propagation
Aishan Liu, Xianglong Liu, Hang Yu, Chongzhi Zhang, Qiang Liu, and Dacheng Tao · 2021
Later among the works it cites.
An efficient robust method for accurate and real-time vehicle plate recognition
Jamshid Pirgazi, Ali Ghanbari Sorkhi, and Mohammad Mehdi Pourhashem Kallehbasti · 2021
Later among the works it cites.
A unified game-theoretic interpretation of adversarial robustness
Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, et al · 2021
Later among the works it cites.
Robustart: Benchmarking robustness on architecture design and training techniques
Shiyu Tang, Ruihao Gong, Yan Wang, Aishan Liu, Jiakai Wang, Xinyun Chen, Fengwei Yu, Xianglong Liu, Dawn Song, Alan Yuille, Philip H.S. Torr, and Dacheng Tao · 2021
Later among the works it cites.
Universal adversarial patch attack for automatic checkout using perceptual and attentional bias
Jiakai Wang, Aishan Liu, Xiao Bai, and Xianglong Liu · 2021
Later among the works it cites.
Dual attention suppression attack: Generate adversarial camouflage in physical world
Jiakai Wang, Aishan Liu, Zixin Yin, Shunchang Liu, Shiyu Tang, and Xianglong Liu · 2021
Later among the works it cites.
Improving generalization of deepfake detection with domain adaptive batch normalization
Zixin Yin, Jiakai Wang, Yifu Ding, Yisong Xiao, Jun Guo, Renshuai Tao, and Haotong Qin · 2021
Later among the works it cites.
Fooling thermal infrared pedestrian detectors in real world using small bulbs
Xiaopei Zhu, Xiao Li, Jianmin Li, Zheyao Wang, and Xiaolin Hu · 2021
Later among the works it cites.
Discrete cosine transform network for guided depth map super-resolution
Zixiang Zhao, Jiangshe Zhang, Shuang Xu, Zudi Lin, and Hanspeter Pfister · 2022
Closest in time.