Reveal of Vision Transformers Robustness against Adversarial Attacks

7 June 2021

Papers citing "Reveal of Vision Transformers Robustness against Adversarial Attacks"

50 / 51 papers shown

Title
Adversarially Pretrained Transformers may be Universally Robust In-Context Learners Soichiro Kumano Hiroshi Kera Toshihiko Yamasaki AAML 105 0 0 20 May 2025
MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness Xiaoyun Xu Shujian Yu Jingzheng Wu S. Picek AAML 82 0 0 08 Dec 2023
Vision Transformers are Robust Learners Sayak Paul Pin-Yu Chen ViT 59 311 0 17 May 2021
On the Robustness of Vision Transformers to Adversarial Examples Kaleel Mahmood Rigel Mahmood Marten van Dijk ViT 116 224 0 31 Mar 2021
CvT: Introducing Convolutions to Vision Transformers Haiping Wu Bin Xiao Noel Codella Mengchen Liu Xiyang Dai Lu Yuan Lei Zhang ViT 152 1,910 0 29 Mar 2021
Understanding Robustness of Transformers for Image Classification Srinadh Bhojanapalli Ayan Chakrabarti Daniel Glasner Daliang Li Thomas Unterthiner Andreas Veit ViT 87 385 0 26 Mar 2021
Transformer in Transformer Kai Han An Xiao Enhua Wu Jianyuan Guo Chunjing Xu Yunhe Wang ViT 389 1,565 0 27 Feb 2021
Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet Li-xin Yuan Yunpeng Chen Tao Wang Weihao Yu Yujun Shi Zihang Jiang Francis E. H. Tay Jiashi Feng Shuicheng Yan ViT 130 1,939 0 28 Jan 2021
Color Channel Perturbation Attacks for Fooling Convolutional Neural Networks and A Defense Against Such Attacks Jayendra Kantipudi S. Dubey Soumendu Chakraborty AAML 66 21 0 20 Dec 2020
Transformer-Encoder Detector Module: Using Context to Improve Robustness to Adversarial Attacks on Object Detection Faisal Alamri Sinan Kalkan N. Pugeault ViT 42 7 0 13 Nov 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 651 41,103 0 22 Oct 2020
RayS: A Ray Searching Method for Hard-label Adversarial Attack Jinghui Chen Quanquan Gu AAML 50 138 0 23 Jun 2020
A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects Zewen Li Wenjie Yang Shouheng Peng Fan Liu HAI 3DV 98 2,720 0 01 Apr 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 216 1,846 0 03 Mar 2020
Hold me tight! Influence of discriminative features on deep network boundaries Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 36 50 0 15 Feb 2020
Big Transfer (BiT): General Visual Representation Learning Alexander Kolesnikov Lucas Beyer Xiaohua Zhai J. Puigcerver Jessica Yung Sylvain Gelly N. Houlsby MQ 286 1,205 0 24 Dec 2019
Square Attack: a query-efficient black-box adversarial attack via random search Maksym Andriushchenko Francesco Croce Nicolas Flammarion Matthias Hein AAML 85 987 0 29 Nov 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review Han Xu Yao Ma Haochen Liu Debayan Deb Hui Liu Jiliang Tang Anil K. Jain AAML 65 675 0 17 Sep 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack Francesco Croce Matthias Hein AAML 87 488 0 03 Jul 2019
Perceptual Evaluation of Adversarial Attacks for CNN-based Image Classification Sid Ahmed Fezza Yassine Bakhti W. Hamidouche Olivier Déforges AAML 47 31 0 01 Jun 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 89 1,838 0 06 May 2019
On the Effectiveness of Low Frequency Perturbations Yash Sharma G. Ding Marcus A. Brubaker AAML 69 122 0 28 Feb 2019
Adversarial Attacks and Defences: A Survey Anirban Chakraborty Manaar Alam Vishal Dey Anupam Chattopadhyay Debdeep Mukhopadhyay AAML OOD 73 679 0 28 Sep 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 219 3,186 0 01 Feb 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey Naveed Akhtar Ajmal Mian AAML 95 1,867 0 02 Jan 2018
Adversarial Examples: Attacks and Defenses for Deep Learning Xiaoyong Yuan Pan He Qile Zhu Xiaolin Li SILM AAML 88 1,622 0 19 Dec 2017
Countering Adversarial Images using Input Transformations Chuan Guo Mayank Rana Moustapha Cissé Laurens van der Maaten AAML 112 1,405 0 31 Oct 2017
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era Chen Sun Abhinav Shrivastava Saurabh Singh Abhinav Gupta VLM 185 2,398 0 10 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 304 12,069 0 19 Jun 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 701 131,652 0 12 Jun 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 121 1,857 0 20 May 2017
Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with JPEG Compression Nilaksh Das Madhuri Shanbhogue Shang-Tse Chen Fred Hohman Li-Wei Chen Michael E. Kounavis Duen Horng Chau AAML 61 306 0 08 May 2017
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 1.1K 20,837 0 17 Apr 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks Weilin Xu David Evans Yanjun Qi AAML 85 1,268 0 04 Apr 2017
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Zhuowen Tu Kaiming He 509 10,330 0 16 Nov 2016
Universal adversarial perturbations Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi Omar Fawzi P. Frossard AAML 136 2,527 0 26 Oct 2016
Assessing Threat of Adversarial Examples on Deep Neural Networks Abigail Graese Andras Rozsa Terrance E. Boult AAML 39 57 0 13 Oct 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 297 20,003 0 07 Oct 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 261 8,552 0 16 Aug 2016
A study of the effect of JPG compression on adversarial images Gintare Karolina Dziugaite Zoubin Ghahramani Daniel M. Roy AAML 86 533 0 02 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 540 5,897 0 08 Jul 2016
Gaussian Error Linear Units (GELUs) Dan Hendrycks Kevin Gimpel 169 5,000 0 27 Jun 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,020 0 10 Dec 2015
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 883 27,358 0 02 Dec 2015
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 105 3,962 0 24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 151 4,897 0 14 Nov 2015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks Nicolas Papernot Patrick McDaniel Xi Wu S. Jha A. Swami AAML 102 3,072 0 14 Nov 2015
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks Shaoqing Ren Kaiming He Ross B. Girshick Jian Sun AIMat ObjD 502 62,294 0 04 Jun 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,066 0 20 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.6K 100,386 0 04 Sep 2014