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ZeroPur: Succinct Training-Free Adversarial Purification

5 June 2024

Papers citing "ZeroPur: Succinct Training-Free Adversarial Purification"

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Title
Adversarial Training on Purification (AToP): Advancing Both Robustness and Generalization Guang Lin Chao Li Jianhai Zhang Toshihisa Tanaka Qibin Zhao 271 22 0 29 Jan 2024
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game PerspectiveNeural Information Processing Systems (NeurIPS), 2023 Yifei Wang Liangchen Li Jiansheng Yang Zhouchen Lin Yisen Wang 220 19 0 30 Oct 2023
DiffAttack: Evasion Attacks Against Diffusion-Based Adversarial PurificationNeural Information Processing Systems (NeurIPS), 2023 Mintong Kang Basel Alomair Yue Liu 258 46 0 27 Oct 2023
Decoupled Kullback-Leibler Divergence LossNeural Information Processing Systems (NeurIPS), 2023 Jiequan Cui Zhuotao Tian Zhisheng Zhong Xiaojuan Qi Bei Yu Hanwang Zhang 213 68 0 23 May 2023
Robust Evaluation of Diffusion-Based Adversarial PurificationIEEE International Conference on Computer Vision (ICCV), 2023 M. Lee Dongwoo Kim 315 80 0 16 Mar 2023
Better Diffusion Models Further Improve Adversarial TrainingInternational Conference on Machine Learning (ICML), 2023 Zekai Wang Tianyu Pang Chao Du Min Lin Weiwei Liu Shuicheng Yan DiffM 379 277 0 09 Feb 2023
Exploring and Exploiting Decision Boundary Dynamics for Adversarial RobustnessInternational Conference on Learning Representations (ICLR), 2023 Yuancheng Xu Yanchao Sun Micah Goldblum Tom Goldstein Furong Huang AAML 268 47 0 06 Feb 2023
Data Augmentation Alone Can Improve Adversarial TrainingInternational Conference on Learning Representations (ICLR), 2023 Lin Li Michael W. Spratling 161 63 0 24 Jan 2023
DISCO: Adversarial Defense with Local Implicit FunctionsNeural Information Processing Systems (NeurIPS), 2022 Chih-Hui Ho Nuno Vasconcelos AAML 349 51 0 11 Dec 2022
Efficient and Effective Augmentation Strategy for Adversarial TrainingNeural Information Processing Systems (NeurIPS), 2022 Sravanti Addepalli Samyak Jain R. Venkatesh Babu AAML 170 69 0 27 Oct 2022
Towards Efficient Adversarial Training on Vision TransformersEuropean Conference on Computer Vision (ECCV), 2022 Boxi Wu Jindong Gu Zhifeng Li Deng Cai Xiaofei He Wei Liu ViT AAML 217 45 0 21 Jul 2022
Guided Diffusion Model for Adversarial Purification Jinyi Wang Zhaoyang Lyu Dahua Lin Bo Dai Hongfei Fu DiffM 428 109 0 30 May 2022
Diffusion Models for Adversarial PurificationInternational Conference on Machine Learning (ICML), 2022 Weili Nie Brandon Guo Yujia Huang Chaowei Xiao Arash Vahdat Anima Anandkumar WIGM 438 572 0 16 May 2022
Formulating Robustness Against Unforeseen AttacksNeural Information Processing Systems (NeurIPS), 2022 Sihui Dai Saeed Mahloujifar Prateek Mittal OOD AAML 268 9 0 28 Apr 2022
Generative Adversarial NetworksInternational Conference on Computing Communication and Networking Technologies (ICCCNT), 2021 Gilad Cohen Raja Giryes GAN 753 30,270 0 01 Mar 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) DefinitionInternational Conference on Machine Learning (ICML), 2022 Tianyu Pang Min Lin Xiao Yang Junyi Zhu Shuicheng Yan 323 145 0 21 Feb 2022
Mutual Adversarial Training: Learning together is better than going alone Jiang-Long Liu Chun Pong Lau Hossein Souri Soheil Feizi Ramalingam Chellappa OOD AAML 156 26 0 09 Dec 2021
Subspace Adversarial Training Tao Li Yingwen Wu Sizhe Chen Kun Fang Xiaolin Huang AAML OOD 220 64 0 24 Nov 2021
Masked Autoencoders Are Scalable Vision LearnersComputer Vision and Pattern Recognition (CVPR), 2021 Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 1.6K 9,791 0 11 Nov 2021
Are Transformers More Robust Than CNNs?Neural Information Processing Systems (NeurIPS), 2021 Yutong Bai Jieru Mei Alan Yuille Cihang Xie ViT AAML 423 309 0 10 Nov 2021
Improving Robustness using Generated Data Sven Gowal Sylvestre-Alvise Rebuffi Olivia Wiles Florian Stimberg D. A. Calian Timothy A. Mann 297 341 0 18 Oct 2021
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense Duhun Hwang Eunjung Lee Wonjong Rhee AAML 299 19 0 14 Jul 2021
Adversarial purification with Score-based generative modelsInternational Conference on Machine Learning (ICML), 2021 Jongmin Yoon Sung Ju Hwang Juho Lee DiffM 170 176 0 11 Jun 2021
Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?International Conference on Learning Representations (ICLR), 2021 Vikash Sehwag Saeed Mahloujifar Tinashe Handina Sihui Dai Chong Xiang M. Chiang Prateek Mittal OOD 198 143 0 19 Apr 2021
Adversarial Attacks are Reversible with Natural SupervisionIEEE International Conference on Computer Vision (ICCV), 2021 Chengzhi Mao Mia Chiquer Hao Wang Junfeng Yang Carl Vondrick BDL AAML 336 65 0 26 Mar 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 204 296 0 02 Mar 2021
Score-Based Generative Modeling through Stochastic Differential EquationsInternational Conference on Learning Representations (ICLR), 2020 Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 1.1K 8,584 0 26 Nov 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 627 803 0 19 Oct 2020
Torchattacks: A PyTorch Repository for Adversarial Attacks Hoki Kim 449 249 0 24 Sep 2020
Do Adversarially Robust ImageNet Models Transfer Better?Neural Information Processing Systems (NeurIPS), 2020 Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor Aleksander Madry 294 462 0 16 Jul 2020
Understanding and Improving Fast Adversarial Training Maksym Andriushchenko Nicolas Flammarion AAML 247 324 0 06 Jul 2020
Perceptual Adversarial Robustness: Defense Against Unseen Threat ModelsInternational Conference on Learning Representations (ICLR), 2020 Cassidy Laidlaw Sahil Singla Soheil Feizi AAML OOD 339 208 0 22 Jun 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 4.2K 24,966 0 19 Jun 2020
Stochastic Security: Adversarial Defense Using Long-Run Dynamics of Energy-Based ModelsInternational Conference on Learning Representations (ICLR), 2020 Mitch Hill Jonathan Mitchell Song-Chun Zhu AAML 175 83 0 27 May 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacksInternational Conference on Machine Learning (ICML), 2020 Francesco Croce Matthias Hein AAML 588 2,145 0 03 Mar 2020
Overfitting in adversarially robust deep learningInternational Conference on Machine Learning (ICML), 2020 Leslie Rice Eric Wong Zico Kolter 497 882 0 26 Feb 2020
Fast is better than free: Revisiting adversarial trainingInternational Conference on Learning Representations (ICLR), 2020 Eric Wong Leslie Rice J. Zico Kolter AAML OOD 673 1,288 0 12 Jan 2020
Adversarial Training for Free!Neural Information Processing Systems (NeurIPS), 2019 Ali Shafahi Mahyar Najibi Amin Ghiasi Zheng Xu John P. Dickerson Christoph Studer L. Davis Gavin Taylor Tom Goldstein AAML 537 1,358 0 29 Apr 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Sai Li 654 2,826 0 24 Jan 2019
Learning Implicit Fields for Generative Shape Modeling Zhiqin Chen Hao Zhang AI4CE 3DV 510 1,746 0 06 Dec 2018
Adversarial Defense by Stratified Convolutional Sparse Coding Bo Sun Nian-hsuan Tsai Fangchen Liu Ronald Yu Hao Su AAML 239 83 0 30 Nov 2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei Maya Kabkab Rama Chellappa AAML GAN 468 1,224 0 17 May 2018
Improving Transferability of Adversarial Examples with Input Diversity Cihang Xie Zhishuai Zhang Yuyin Zhou Song Bai Jianyu Wang Zhou Ren Alan Yuille AAML 315 1,285 0 19 Mar 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 1.2K 3,357 0 01 Feb 2018
Generative Image Inpainting with Contextual Attention Jiahui Yu Zhe Lin Jimei Yang Xiaohui Shen Xin Lu Thomas S. Huang GAN DiffM 301 2,444 0 24 Jan 2018
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Richard Y. Zhang Phillip Isola Alexei A. Efros Eli Shechtman Oliver Wang EGVM 1.0K 14,911 0 11 Jan 2018
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality Jiabo He Yue Liu Yisen Wang S. Erfani S. Wijewickrema Grant Schoenebeck Basel Alomair Michael E. Houle James Bailey AAML 352 791 0 08 Jan 2018
Countering Adversarial Images using Input Transformations Chuan Guo Mayank Rana Moustapha Cissé Laurens van der Maaten AAML 569 1,518 0 31 Oct 2017
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial ExamplesInternational Conference on Learning Representations (ICLR), 2017 Yang Song Taesup Kim Sebastian Nowozin Stefano Ermon Nate Kushman AAML 345 819 0 30 Oct 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 1.2K 13,556 0 19 Jun 2017

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ZeroPur: Succinct Training-Free Adversarial Purification

Papers citing "ZeroPur: Succinct Training-Free Adversarial Purification"