Fixing Data Augmentation to Improve Adversarial Robustness

2 March 2021

Sylvestre-Alvise Rebuffi

Papers citing "Fixing Data Augmentation to Improve Adversarial Robustness"

50 / 174 papers shown

Title
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 11 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 20 1 0 13 Oct 2023
Visual Data-Type Understanding does not emerge from Scaling Vision-Language Models Vishaal Udandarao Max F. Burg Samuel Albanie Matthias Bethge VLM 24 8 0 12 Oct 2023
Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization Giuseppe Floris Raffaele Mura Luca Scionis Giorgio Piras Maura Pintor Ambra Demontis Battista Biggio AAML 19 4 0 12 Oct 2023
PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization Jiancong Xiao Ruoyu Sun Zhimin Luo AAML 23 6 0 09 Oct 2023
Generating Less Certain Adversarial Examples Improves Robust Generalization Minxing Zhang Michael Backes Xiao Zhang AAML 30 1 0 06 Oct 2023
Splitting the Difference on Adversarial Training Matan Levi A. Kontorovich 21 4 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 13 1 0 28 Sep 2023
Improving Robustness of Deep Convolutional Neural Networks via Multiresolution Learning Hongyan Zhou Yao Liang OOD 10 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 8 1 0 11 Sep 2023
DiffDefense: Defending against Adversarial Attacks via Diffusion Models Hondamunige Prasanna Silva Lorenzo Seidenari A. Bimbo DiffM 33 6 0 07 Sep 2023
DiffSmooth: Certifiably Robust Learning via Diffusion Models and Local Smoothing Jiawei Zhang Zhongzhu Chen Huan Zhang Chaowei Xiao Bo-wen Li DiffM 31 20 0 28 Aug 2023
Revisiting and Exploring Efficient Fast Adversarial Training via LAW: Lipschitz Regularization and Auto Weight Averaging Xiaojun Jia YueFeng Chen Xiaofeng Mao Ranjie Duan Jindong Gu Rong Zhang H. Xue Xiaochun Cao AAML 9 9 0 22 Aug 2023
Improving Generalization of Adversarial Training via Robust Critical Fine-Tuning Kaijie Zhu Jindong Wang Xixu Hu Xingxu Xie G. Yang AAML 12 23 0 01 Aug 2023
NSA: Naturalistic Support Artifact to Boost Network Confidence Abhijith Sharma Phil Munz Apurva Narayan AAML 13 1 0 27 Jul 2023
Fix your downsampling ASAP! Be natively more robust via Aliasing and Spectral Artifact free Pooling Julia Grabinski J. Keuper M. Keuper AAML 14 7 0 19 Jul 2023
Enhancing Adversarial Robustness via Score-Based Optimization Boya Zhang Weijian Luo Zhihua Zhang DiffM 19 11 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 12 4 0 25 Jun 2023
Adversarial Training Should Be Cast as a Non-Zero-Sum Game Alexander Robey Fabian Latorre George J. Pappas Hamed Hassani V. Cevher AAML 66 12 0 19 Jun 2023
Revisiting and Advancing Adversarial Training Through A Simple Baseline Hong Liu AAML 16 0 0 13 Jun 2023
Toward Understanding Generative Data Augmentation Chenyu Zheng Guoqiang Wu Chongxuan Li 13 24 0 27 May 2023
Robust Classification via a Single Diffusion Model Huanran Chen Yinpeng Dong Zhengyi Wang X. Yang Chen-Dong Duan Hang Su Jun Zhu 69 56 0 24 May 2023
Decoupled Kullback-Leibler Divergence Loss Jiequan Cui Zhuotao Tian Zhisheng Zhong Xiaojuan Qi Bei Yu Hanwang Zhang 18 38 0 23 May 2023
DiffProtect: Generate Adversarial Examples with Diffusion Models for Facial Privacy Protection Jiang-Long Liu Chun Pong Lau Ramalingam Chellappa DiffM 21 28 0 23 May 2023
Annealing Self-Distillation Rectification Improves Adversarial Training Yuehua Wu Hung-Jui Wang Shang-Tse Chen AAML 16 3 0 20 May 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 30 47 0 18 May 2023
GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models Zaitang Li Pin-Yu Chen Tsung-Yi Ho AAML DiffM 17 4 0 19 Apr 2023
Cross-Entropy Loss Functions: Theoretical Analysis and Applications Anqi Mao M. Mohri Yutao Zhong AAML 8 265 0 14 Apr 2023
Improving Fast Adversarial Training with Prior-Guided Knowledge Xiaojun Jia Yong Zhang Xingxing Wei Baoyuan Wu Ke Ma Jue Wang Xiaochun Cao AAML 14 26 0 01 Apr 2023
Generalist: Decoupling Natural and Robust Generalization Hongjun Wang Yisen Wang OOD AAML 20 14 0 24 Mar 2023
Revisiting DeepFool: generalization and improvement Alireza Abdollahpourrostam Mahed Abroshan Seyed-Mohsen Moosavi-Dezfooli AAML 11 2 0 22 Mar 2023
Randomized Adversarial Training via Taylor Expansion Gao Jin Xinping Yi Dengyu Wu Ronghui Mu Xiaowei Huang AAML 20 34 0 19 Mar 2023
Robust Evaluation of Diffusion-Based Adversarial Purification M. Lee Dongwoo Kim 34 52 0 16 Mar 2023
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks Sihui Dai Saeed Mahloujifar Chong Xiang Vikash Sehwag Pin-Yu Chen Prateek Mittal AAML OOD 14 7 0 21 Feb 2023
Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels Zebin You Yong Zhong Fan Bao Jiacheng Sun Chongxuan Li Jun Zhu DiffM VLM 198 35 0 21 Feb 2023
X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detection Aishan Liu Jun Guo Jiakai Wang Siyuan Liang Renshuai Tao Wenbo Zhou Cong Liu Xianglong Liu Dacheng Tao AAML 26 60 0 19 Feb 2023
HateProof: Are Hateful Meme Detection Systems really Robust? Piush Aggarwal Pranit Chawla Mithun Das Punyajoy Saha Binny Mathew Torsten Zesch Animesh Mukherjee AAML 11 8 0 11 Feb 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min-Bin Lin Weiwei Liu Shuicheng Yan DiffM 14 206 0 09 Feb 2023
Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness Yuancheng Xu Yanchao Sun Micah Goldblum Tom Goldstein Furong Huang AAML 10 35 0 06 Feb 2023
A Minimax Approach Against Multi-Armed Adversarial Attacks Detection Federica Granese Marco Romanelli S. Garg Pablo Piantanida AAML 17 0 0 04 Feb 2023
Uncovering Adversarial Risks of Test-Time Adaptation Tong Wu Feiran Jia Xiangyu Qi Jiachen T. Wang Vikash Sehwag Saeed Mahloujifar Prateek Mittal AAML TTA 11 9 0 29 Jan 2023
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing Yatong Bai Brendon G. Anderson Aerin Kim Somayeh Sojoudi AAML 19 18 0 29 Jan 2023
Provable Unrestricted Adversarial Training without Compromise with Generalizability Lili Zhang Ning Yang Yanchao Sun Philip S. Yu AAML 11 2 0 22 Jan 2023
Phase-shifted Adversarial Training Yeachan Kim Seongyeon Kim Ihyeok Seo Bonggun Shin AAML OOD 19 0 0 12 Jan 2023
Beckman Defense A. V. Subramanyam OOD AAML 14 0 0 04 Jan 2023
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks Nikolaos Antoniou Efthymios Georgiou Alexandros Potamianos AAML 22 5 0 15 Dec 2022
Generative Robust Classification Xuwang Yin TPM 17 0 0 14 Dec 2022
DISCO: Adversarial Defense with Local Implicit Functions Chih-Hui Ho Nuno Vasconcelos AAML 21 38 0 11 Dec 2022
$Multiple Perturbation Attack: Attack Pixelwise Under Different $\ell_p$-norms For Better Adversarial Performance$ Multiple Perturbation Attack: Attack Pixelwise Under Different $\ell_p$ -norms For Better Adversarial Performance Ngoc N. Tran Anh Tuan Bui Dinh Q. Phung Trung Le AAML 10 1 0 05 Dec 2022
Adversarial Rademacher Complexity of Deep Neural Networks Jiancong Xiao Yanbo Fan Ruoyu Sun Zhimin Luo AAML 15 22 0 27 Nov 2022