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Fixing Data Augmentation to Improve Adversarial Robustness

2 March 2021

Sylvestre-Alvise Rebuffi

Papers citing "Fixing Data Augmentation to Improve Adversarial Robustness"

50 / 185 papers shown

Title
BlackboxBench: A Comprehensive Benchmark of Black-box Adversarial Attacks Meixi Zheng Xuanchen Yan Zihao Zhu Hongrui Chen Baoyuan Wu ELM MLAU AAML 402 16 0 28 Dec 2023
MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness Xiaoyun Xu Shujian Yu Jingzheng Wu S. Picek AAML 506 7 0 08 Dec 2023
Indirect Gradient Matching for Adversarial Robust DistillationInternational Conference on Learning Representations (ICLR), 2023 Hongsin Lee Yujin Yang Changick Kim AAML FedML 244 3 0 06 Dec 2023
ScAR: Scaling Adversarial Robustness for LiDAR Object DetectionIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2023 Xiaohu Lu H. Radha AAML 3DPC 304 2 0 05 Dec 2023
Rethinking PGD Attack: Is Sign Function Necessary? Junjie Yang Tianlong Chen Xuxi Chen Zinan Lin Yingbin Liang AAML 261 2 0 03 Dec 2023
Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-OffConference on Learning for Dynamics & Control (L4DC), 2023 Yatong Bai Brendon G. Anderson Somayeh Sojoudi AAML 256 2 0 26 Nov 2023
Purify++: Improving Diffusion-Purification with Advanced Diffusion Models and Control of Randomness Boya Zhang Weijian Luo Zhihua Zhang 186 15 0 28 Oct 2023
DiffAttack: Evasion Attacks Against Diffusion-Based Adversarial PurificationNeural Information Processing Systems (NeurIPS), 2023 Mintong Kang Basel Alomair Yue Liu 266 46 0 27 Oct 2023
OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift Lin Li Yifei Wang Chawin Sitawarin Michael W. Spratling 256 11 0 19 Oct 2023
IRAD: Implicit Representation-driven Image Resampling against Adversarial AttacksInternational Conference on Learning Representations (ICLR), 2023 Yue Cao Tianlin Li Xiaofeng Cao Ivor Tsang Yang Liu Qing Guo AAML 241 4 0 18 Oct 2023
Towards Deep Learning Models Resistant to Transfer-based Adversarial Attacks via Data-centric Robust Learning Yulong Yang Chenhao Lin Xiang Ji Qiwei Tian Qian Li Hongshan Yang Zhibo Wang Chao Shen 186 7 0 15 Oct 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 223 1 0 13 Oct 2023
Visual Data-Type Understanding does not emerge from Scaling Vision-Language ModelsInternational Conference on Learning Representations (ICLR), 2023 Vishaal Udandarao Max F. Burg Samuel Albanie Matthias Bethge VLM 291 11 0 12 Oct 2023
Improving Fast Minimum-Norm Attacks with Hyperparameter OptimizationThe European Symposium on Artificial Neural Networks (ESANN), 2023 Giuseppe Floris Raffaele Mura Luca Scionis Giorgio Piras Maura Pintor Ambra Demontis Battista Biggio AAML 120 5 0 12 Oct 2023
PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust GeneralizationNeural Information Processing Systems (NeurIPS), 2023 Jiancong Xiao Tian Ding Zhimin Luo AAML 211 8 0 09 Oct 2023
Generating Less Certain Adversarial Examples Improves Robust Generalization Minxing Zhang Michael Backes Xiao Zhang AAML 509 1 0 06 Oct 2023
Splitting the Difference on Adversarial TrainingUSENIX Security Symposium (USENIX Security), 2023 Matan Levi A. Kontorovich 223 8 0 03 Oct 2023
Parameter-Saving Adversarial Training: Reinforcing Multi-Perturbation Robustness via Hypernetworks Huihui Gong Minjing Dong Siqi Ma S. Çamtepe Surya Nepal Chang Xu AAML OOD 166 1 0 28 Sep 2023
Improving Robustness of Deep Convolutional Neural Networks via Multiresolution Learning Hongyan Zhou Yao Liang OOD 190 0 0 24 Sep 2023
Hazards in Deep Learning Testing: Prevalence, Impact and Recommendations Salah Ghamizi Maxime Cordy Yuejun Guo Mike Papadakis And Yves Le Traon 161 1 0 11 Sep 2023
DiffDefense: Defending against Adversarial Attacks via Diffusion ModelsInternational Conference on Image Analysis and Processing (ICIAP), 2023 Hondamunige Prasanna Silva Lorenzo Seidenari Marco Bertini DiffM 132 9 0 07 Sep 2023
DiffSmooth: Certifiably Robust Learning via Diffusion Models and Local SmoothingUSENIX Security Symposium (USENIX Security), 2023 Jiawei Zhang Zhongzhu Chen Huan Zhang Chaowei Xiao Yue Liu DiffM 194 32 0 28 Aug 2023
Revisiting and Exploring Efficient Fast Adversarial Training via LAW: Lipschitz Regularization and Auto Weight AveragingIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2023 Yang Liu YueFeng Chen Xiaofeng Mao Ranjie Duan Jindong Gu Rong Zhang H. Xue Xiaochun Cao AAML 193 13 0 22 Aug 2023
Improving Generalization of Adversarial Training via Robust Critical Fine-TuningIEEE International Conference on Computer Vision (ICCV), 2023 Lingyao Li Yongfeng Zhang Xixu Hu Xingxu Xie G. Yang AAML 140 35 0 01 Aug 2023
NSA: Naturalistic Support Artifact to Boost Network ConfidenceIEEE International Joint Conference on Neural Network (IJCNN), 2023 Abhijith Sharma Phil Munz Apurva Narayan AAML 180 1 0 27 Jul 2023
Fast Adaptive Test-Time Defense with Robust Features Anurag Singh Mahalakshmi Sabanayagam Krikamol Muandet Debarghya Ghoshdastidar AAML TTA OOD 167 0 0 21 Jul 2023
Fix your downsampling ASAP! Be natively more robust via Aliasing and Spectral Artifact free Pooling Julia Grabinski Steffen Jung J. Keuper Margret Keuper AAML 188 9 0 19 Jul 2023
Enhancing Adversarial Robustness via Score-Based OptimizationNeural Information Processing Systems (NeurIPS), 2023 Boya Zhang Weijian Luo Zhihua Zhang DiffM 314 16 0 10 Jul 2023
Enhancing Adversarial Training via Reweighting Optimization Trajectory Tianjin Huang Shiwei Liu Tianlong Chen Meng Fang Lijuan Shen Vlaod Menkovski Lu Yin Yulong Pei Mykola Pechenizkiy AAML 241 5 0 25 Jun 2023
Adversarial Training Should Be Cast as a Non-Zero-Sum GameInternational Conference on Learning Representations (ICLR), 2023 Avi Schwarzschild Fabian Latorre George J. Pappas Hamed Hassani Volkan Cevher AAML 276 14 0 19 Jun 2023
Revisiting and Advancing Adversarial Training Through A Simple Baseline Hong Liu AAML 202 0 0 13 Jun 2023
Toward Understanding Generative Data AugmentationNeural Information Processing Systems (NeurIPS), 2023 Chenyu Zheng Guoqiang Wu Chongxuan Li 194 40 0 27 May 2023
Robust Classification via a Single Diffusion ModelInternational Conference on Machine Learning (ICML), 2023 Huanran Chen Yinpeng Dong Zhengyi Wang Xiaohu Yang Chen-Dong Duan Hang Su Jun Zhu 318 77 0 24 May 2023
Decoupled Kullback-Leibler Divergence LossNeural Information Processing Systems (NeurIPS), 2023 Jiequan Cui Zhuotao Tian Zhisheng Zhong Xiaojuan Qi Bei Yu Hanwang Zhang 241 71 0 23 May 2023
DiffProtect: Generate Adversarial Examples with Diffusion Models for Facial Privacy ProtectionPattern Recognition (Pattern Recogn.), 2023 Jiang-Long Liu Chun Pong Lau Ramalingam Chellappa Yuxiang Guo Zhaoyang Wang Rama Chellappa DiffM 291 42 0 23 May 2023
Annealing Self-Distillation Rectification Improves Adversarial TrainingInternational Conference on Learning Representations (ICLR), 2023 Yuehua Wu Hung-Jui Wang Shang-Tse Chen AAML 241 6 0 20 May 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks & DefensesIEEE Access (IEEE Access), 2023 Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 354 104 0 18 May 2023
GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative ModelsNeural Information Processing Systems (NeurIPS), 2023 Zaitang Li Pin-Yu Chen Tsung-Yi Ho AAML DiffM 170 6 0 19 Apr 2023
Cross-Entropy Loss Functions: Theoretical Analysis and ApplicationsInternational Conference on Machine Learning (ICML), 2023 Anqi Mao M. Mohri Yutao Zhong AAML 275 608 0 14 Apr 2023
Improving Fast Adversarial Training with Prior-Guided KnowledgeIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023 Yang Liu Yong Zhang Xingxing Wei Baoyuan Wu Ke Ma Jue Wang Xiaochun Cao AAML 226 45 0 01 Apr 2023
Generalist: Decoupling Natural and Robust GeneralizationComputer Vision and Pattern Recognition (CVPR), 2023 Hongjun Wang Yisen Wang OOD AAML 198 17 0 24 Mar 2023
Revisiting DeepFool: generalization and improvement Alireza Abdollahpourrostam Mahed Abroshan Seyed-Mohsen Moosavi-Dezfooli AAML 240 2 0 22 Mar 2023
Randomized Adversarial Training via Taylor ExpansionComputer Vision and Pattern Recognition (CVPR), 2023 Gao Jin Xinping Yi Dengyu Wu Ronghui Mu Xiaowei Huang AAML 309 53 0 19 Mar 2023
Robust Evaluation of Diffusion-Based Adversarial PurificationIEEE International Conference on Computer Vision (ICCV), 2023 M. Lee Dongwoo Kim 359 81 0 16 Mar 2023
MultiRobustBench: Benchmarking Robustness Against Multiple AttacksInternational Conference on Machine Learning (ICML), 2023 Sihui Dai Saeed Mahloujifar Chong Xiang Vikash Sehwag Pin-Yu Chen Prateek Mittal AAML OOD 254 9 0 21 Feb 2023
Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few LabelsNeural Information Processing Systems (NeurIPS), 2023 Zebin You Yong Zhong Fan Bao Jiacheng Sun Chongxuan Li Jun Zhu DiffM VLM 484 50 0 21 Feb 2023
X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item DetectionUSENIX Security Symposium (USENIX Security), 2023 Aishan Liu Jun Guo Jinyang Guo Yaning Tan Renshuai Tao Wenbo Zhou Cong Liu Xianglong Liu Dacheng Tao AAML 204 89 0 19 Feb 2023
HateProof: Are Hateful Meme Detection Systems really Robust?The Web Conference (WWW), 2023 Piush Aggarwal Pranit Chawla Mithun Das Punyajoy Saha Binny Mathew Torsten Zesch Animesh Mukherjee AAML 142 12 0 11 Feb 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 415 278 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 300 47 0 06 Feb 2023

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Fixing Data Augmentation to Improve Adversarial Robustness

Papers citing "Fixing Data Augmentation to Improve Adversarial Robustness"