Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks

5 September 2020

Papers citing "Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks"

43 / 43 papers shown

Title
Towards Scalable Topological Regularizers Hiu-Tung Wong Darrick Lee Hong Yan BDL 59 0 0 24 Jan 2025
Natural Language Induced Adversarial Images Xiaopei Zhu Peiyang Xu Guanning Zeng Yingpeng Dong Xiaolin Hu AAML 28 0 0 11 Oct 2024
Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility Rajdeep Haldar Yue Xing Qifan Song Guang Lin 31 0 0 09 Oct 2024
SCA: Highly Efficient Semantic-Consistent Unrestricted Adversarial Attack Zihao Pan Weibin Wu Yuhang Cao Zibin Zheng DiffM AAML 60 1 0 03 Oct 2024
A Grey-box Attack against Latent Diffusion Model-based Image Editing by Posterior Collapse Zhongliang Guo Lei Fang Jingyu Lin Yifei Qian Shuai Zhao Zeyu Wang Zeyu Wang Cunjian Chen Ognjen Arandjelović Chun Pong Lau DiffM AAML 40 6 0 20 Aug 2024
DifAttack++: Query-Efficient Black-Box Adversarial Attack via Hierarchical Disentangled Feature Space in Cross-Domain Jun Liu Jiantao Zhou Jiandian Zeng Jinyu Tian Zheng Li 35 0 0 05 Jun 2024
Robust Overfitting Does Matter: Test-Time Adversarial Purification With FGSM Linyu Tang Lei Zhang AAML 29 3 0 18 Mar 2024
Adversarially Robust Feature Learning for Breast Cancer Diagnosis Degan Hao Dooman Arefan M. Zuley Wendie Berg Shandong Wu OOD MedIm 24 1 0 13 Feb 2024
Instruct2Attack: Language-Guided Semantic Adversarial Attacks Jiang-Long Liu Chen Wei Yuxiang Guo Heng Yu Alan L. Yuille S. Feizi Chun Pong Lau Rama Chellappa DiffM AAML 27 5 0 27 Nov 2023
$Is Certifying $\ell_p$ Robustness Still Worthwhile?$ Is Certifying $\ell_p$ Robustness Still Worthwhile? Ravi Mangal Klas Leino Zifan Wang Kai Hu Weicheng Yu Corina S. Pasareanu Anupam Datta Matt Fredrikson AAML OOD 25 1 0 13 Oct 2023
PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization Jiancong Xiao Ruoyu Sun Zhimin Luo AAML 30 6 0 09 Oct 2023
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness Ambar Pal Huaijin Hao René Vidal 26 8 0 28 Sep 2023
Why Does Little Robustness Help? Understanding and Improving Adversarial Transferability from Surrogate Training Yechao Zhang Shengshan Hu Leo Yu Zhang Junyu Shi Minghui Li Xiaogeng Liu Wei Wan Hai Jin AAML 22 21 0 15 Jul 2023
DiffProtect: Generate Adversarial Examples with Diffusion Models for Facial Privacy Protection Jiang-Long Liu Chun Pong Lau Ramalingam Chellappa DiffM 29 31 0 23 May 2023
Attribute-Guided Encryption with Facial Texture Masking Chun Pong Lau Jiang-Long Liu Ramalingam Chellappa PICV AAML 21 3 0 22 May 2023
Understanding Overfitting in Adversarial Training via Kernel Regression Teng Zhang Kang Li 13 2 0 13 Apr 2023
Improving Model Generalization by On-manifold Adversarial Augmentation in the Frequency Domain Chang-rui Liu Wenzhao Xiang Yuan He H. Xue Shibao Zheng Hang Su 35 3 0 28 Feb 2023
DISCO: Adversarial Defense with Local Implicit Functions Chih-Hui Ho Nuno Vasconcelos AAML 21 38 0 11 Dec 2022
Dual Graphs of Polyhedral Decompositions for the Detection of Adversarial Attacks Huma Jamil Yajing Liu Christina Cole Nathaniel Blanchard E. King Michael Kirby C. Peterson AAML 33 2 0 23 Nov 2022
Assessing Neural Network Robustness via Adversarial Pivotal Tuning Peter Ebert Christensen Vésteinn Snaebjarnarson Andrea Dittadi Serge J. Belongie Sagie Benaim AAML 23 1 0 17 Nov 2022
Adversarial Purification with the Manifold Hypothesis Zhaoyuan Yang Zhiwei Xu Jing Zhang Richard I. Hartley Peter Tu AAML 16 5 0 26 Oct 2022
Dissipative residual layers for unsupervised implicit parameterization of data manifolds Viktor Reshniak 6 0 0 13 Oct 2022
Understanding Adversarial Robustness Against On-manifold Adversarial Examples Jiancong Xiao Liusha Yang Yanbo Fan Jue Wang Zhimin Luo OOD 18 13 0 02 Oct 2022
Explicit Tradeoffs between Adversarial and Natural Distributional Robustness Mazda Moayeri Kiarash Banihashem S. Feizi OOD 72 21 0 15 Sep 2022
Masked Spatial-Spectral Autoencoders Are Excellent Hyperspectral Defenders Jiahao Qi Z. Gong Xingyue Liu Kangcheng Bin Chen Chen Yongqiang Li Wei Xue Yu Zhang P. Zhong AAML 34 6 0 16 Jul 2022
Analysis and Extensions of Adversarial Training for Video Classification K. A. Kinfu René Vidal AAML 27 13 0 16 Jun 2022
Diffeomorphic Counterfactuals with Generative Models Ann-Kathrin Dombrowski Jan E. Gerken Klaus-Robert Muller Pan Kessel DiffM BDL 27 15 0 10 Jun 2022
A Manifold View of Adversarial Risk Wen-jun Zhang Yikai Zhang Xiaoling Hu Mayank Goswami Chao Chen Dimitris N. Metaxas AAML 9 6 0 24 Mar 2022
Why adversarial training can hurt robust accuracy Jacob Clarysse Julia Hörrmann Fanny Yang AAML 13 18 0 03 Mar 2022
Enhancing Adversarial Robustness for Deep Metric Learning Mo Zhou Vishal M. Patel AAML 17 18 0 02 Mar 2022
Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses Chun Pong Lau Jiang-Long Liu Hossein Souri Wei-An Lin S. Feizi Ramalingam Chellappa AAML 29 12 0 12 Dec 2021
Mutual Adversarial Training: Learning together is better than going alone Jiang-Long Liu Chun Pong Lau Hossein Souri S. Feizi Ramalingam Chellappa OOD AAML 35 24 0 09 Dec 2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps Muhammad Awais Fengwei Zhou Chuanlong Xie Jiawei Li Sung-Ho Bae Zhenguo Li AAML 29 17 0 09 Nov 2021
Adversarial robustness for latent models: Revisiting the robust-standard accuracies tradeoff Adel Javanmard M. Mehrabi AAML 17 5 0 22 Oct 2021
Identification of Attack-Specific Signatures in Adversarial Examples Hossein Souri Pirazh Khorramshahi Chun Pong Lau Micah Goldblum Rama Chellappa AAML MLAU 35 4 0 13 Oct 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Saeed Mian Navid Kardan M. Shah AAML 26 235 0 01 Aug 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs S. Feizi AAML 32 45 0 15 Feb 2021
$Towards Defending Multiple $\ell_p$-norm Bounded Adversarial Perturbations via Gated Batch Normalization$ Towards Defending Multiple $\ell_p$ -norm Bounded Adversarial Perturbations via Gated Batch Normalization Aishan Liu Shiyu Tang Xinyun Chen Lei Huang Zhuozhuo Tu Xianglong Liu Dacheng Tao AAML 27 31 0 03 Dec 2020
Defending Against Multiple and Unforeseen Adversarial Videos Shao-Yuan Lo Vishal M. Patel AAML 23 23 0 11 Sep 2020
Testing Robustness Against Unforeseen Adversaries Maximilian Kaufmann Daniel Kang Yi Sun Steven Basart Xuwang Yin ... Adam Dziedzic Franziska Boenisch Tom B. Brown Jacob Steinhardt Dan Hendrycks AAML 9 0 0 21 Aug 2019
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 279 10,348 0 12 Dec 2018
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 186 272 0 03 Dec 2018
Constructing Unrestricted Adversarial Examples with Generative Models Yang Song Rui Shu Nate Kushman Stefano Ermon GAN AAML 185 302 0 21 May 2018