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
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles Shengcai Liu Fu Peng Ke Tang AAML 20 11 0 23 Nov 2022
The Enemy of My Enemy is My Friend: Exploring Inverse Adversaries for Improving Adversarial Training Junhao Dong Seyed-Mohsen Moosavi-Dezfooli Jianhuang Lai Xiaohua Xie AAML 35 26 0 01 Nov 2022
Adversarial Purification with the Manifold Hypothesis Zhaoyuan Yang Zhiwei Xu Jing Zhang Richard I. Hartley Peter Tu AAML 14 5 0 26 Oct 2022
Hindering Adversarial Attacks with Implicit Neural Representations Andrei A. Rusu D. A. Calian Sven Gowal R. Hadsell AAML 123 4 0 22 Oct 2022
Scaling Adversarial Training to Large Perturbation Bounds Sravanti Addepalli Samyak Jain Gaurang Sriramanan R. Venkatesh Babu AAML 8 22 0 18 Oct 2022
Robust Models are less Over-Confident Julia Grabinski Paul Gavrikov J. Keuper M. Keuper AAML 14 24 0 12 Oct 2022
Stability Analysis and Generalization Bounds of Adversarial Training Jiancong Xiao Yanbo Fan Ruoyu Sun Jue Wang Zhimin Luo AAML 8 30 0 03 Oct 2022
DeltaBound Attack: Efficient decision-based attack in low queries regime L. Rossi AAML 12 0 0 01 Oct 2022
Improving Robustness with Adaptive Weight Decay Amin Ghiasi Ali Shafahi R. Ardekani OOD 12 6 0 30 Sep 2022
Part-Based Models Improve Adversarial Robustness Chawin Sitawarin Kornrapat Pongmala Yizheng Chen Nicholas Carlini David A. Wagner 39 11 0 15 Sep 2022
Be Your Own Neighborhood: Detecting Adversarial Example by the Neighborhood Relations Built on Self-Supervised Learning Zhiyuan He Yijun Yang Pin-Yu Chen Qiang Xu Tsung-Yi Ho AAML 6 6 0 31 Aug 2022
Constraining Representations Yields Models That Know What They Don't Know João Monteiro Pau Rodríguez López Pierre-Andre Noel I. Laradji David Vazquez AAML 23 0 0 30 Aug 2022
Two Heads are Better than One: Robust Learning Meets Multi-branch Models Dong Huang Qi Bu Yuhao Qing Haowen Pi Sen Wang Heming Cui OOD AAML 16 0 0 17 Aug 2022
A Multi-objective Memetic Algorithm for Auto Adversarial Attack Optimization Design Jialiang Sun Wen Yao Tingsong Jiang Xiaoqian Chen AAML 10 0 0 15 Aug 2022
GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction Jiacheng Zhu Jielin Qiu Zhuolin Yang Douglas Weber M. Rosenberg Emerson Liu Bo-wen Li Ding Zhao OOD 15 13 0 02 Aug 2022
Attacking Adversarial Defences by Smoothing the Loss Landscape Panagiotis Eustratiadis H. Gouk Da Li Timothy M. Hospedales AAML 14 4 0 01 Aug 2022
Robust Trajectory Prediction against Adversarial Attacks Yulong Cao Danfei Xu Xinshuo Weng Zhuoqing Mao Anima Anandkumar Chaowei Xiao Marco Pavone AAML 12 28 0 29 Jul 2022
One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training Sekitoshi Kanai Shinýa Yamaguchi Masanori Yamada Hiroshi Takahashi Kentaro Ohno Yasutoshi Ida AAML 9 7 0 21 Jul 2022
RUSH: Robust Contrastive Learning via Randomized Smoothing Yijiang Pang Boyang Liu Jiayu Zhou OOD AAML 11 1 0 11 Jul 2022
How many perturbations break this model? Evaluating robustness beyond adversarial accuracy R. Olivier Bhiksha Raj AAML 29 5 0 08 Jul 2022
Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations Tianlong Chen Peihao Wang Zhiwen Fan Zhangyang Wang 17 55 0 04 Jul 2022
Diversified Adversarial Attacks based on Conjugate Gradient Method Keiichiro Yamamura Haruki Sato Nariaki Tateiwa Nozomi Hata Toru Mitsutake Issa Oe Hiroki Ishikura Katsuki Fujisawa AAML 14 14 0 20 Jun 2022
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack Ruize Gao Jiongxiao Wang Kaiwen Zhou Feng Liu Binghui Xie Gang Niu Bo Han James Cheng AAML 10 14 0 15 Jun 2022
Towards Alternative Techniques for Improving Adversarial Robustness: Analysis of Adversarial Training at a Spectrum of Perturbations Kaustubh Sridhar Souradeep Dutta Ramneet Kaur James Weimer O. Sokolsky Insup Lee AAML 27 4 0 13 Jun 2022
FACM: Intermediate Layer Still Retain Effective Features against Adversarial Examples Xiangyuan Yang Jie Lin Hanlin Zhang Xinyu Yang Peng Zhao AAML 34 0 0 02 Jun 2022
Semi-supervised Semantics-guided Adversarial Training for Trajectory Prediction Ruochen Jiao Xiangguo Liu Takami Sato Qi Alfred Chen Qi Zhu AAML 23 20 0 27 May 2022
Squeeze Training for Adversarial Robustness Qizhang Li Yiwen Guo W. Zuo Hao Chen OOD 34 9 0 23 May 2022
Post-breach Recovery: Protection against White-box Adversarial Examples for Leaked DNN Models Shawn Shan Wen-Luan Ding Emily Wenger Haitao Zheng Ben Y. Zhao AAML 20 10 0 21 May 2022
Gradient Concealment: Free Lunch for Defending Adversarial Attacks Sen Pei Jiaxi Sun Xiaopeng Zhang Gaofeng Meng AAML 24 0 0 21 May 2022
Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification Leo Schwinn Leon Bungert A. Nguyen René Raab Falk Pulsmeyer Doina Precup Björn Eskofier Dario Zanca OOD 42 12 0 19 May 2022
Gradient Aligned Attacks via a Few Queries Xiangyuan Yang Jie Lin Hanlin Zhang Xinyu Yang Peng Zhao AAML 30 0 0 19 May 2022
TTAPS: Test-Time Adaption by Aligning Prototypes using Self-Supervision Alexander Bartler Florian Bender Felix Wiewel B. Yang TTA 38 9 0 18 May 2022
Diffusion Models for Adversarial Purification Weili Nie Brandon Guo Yujia Huang Chaowei Xiao Arash Vahdat Anima Anandkumar WIGM 195 410 0 16 May 2022
Rethinking Classifier and Adversarial Attack Youhuan Yang Lei Sun Leyu Dai Song Guo Xiuqing Mao Xiaoqin Wang Bayi Xu AAML 11 0 0 04 May 2022
CE-based white-box adversarial attacks will not work using super-fitting Youhuan Yang Lei Sun Leyu Dai Song Guo Xiuqing Mao Xiaoqin Wang Bayi Xu AAML 16 0 0 04 May 2022
Adversarial Robustness through the Lens of Convolutional Filters Paul Gavrikov J. Keuper 25 15 0 05 Apr 2022
FrequencyLowCut Pooling -- Plug & Play against Catastrophic Overfitting Julia Grabinski Steffen Jung J. Keuper M. Keuper AAML 6 22 0 01 Apr 2022
CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters Paul Gavrikov J. Keuper AAML 16 31 0 29 Mar 2022
Self-Ensemble Adversarial Training for Improved Robustness Hongjun Wang Yisen Wang OOD AAML 11 48 0 18 Mar 2022
On the benefits of knowledge distillation for adversarial robustness Javier Maroto Guillermo Ortiz-Jiménez P. Frossard AAML FedML 6 20 0 14 Mar 2022
LAS-AT: Adversarial Training with Learnable Attack Strategy Xiaojun Jia Yong Zhang Baoyuan Wu Ke Ma Jue Wang Xiaochun Cao AAML 12 131 0 13 Mar 2022
Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack Ye Liu Yaya Cheng Lianli Gao Xianglong Liu Qilong Zhang Jingkuan Song AAML 22 56 0 10 Mar 2022
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses Francesco Croce Sven Gowal T. Brunner Evan Shelhamer Matthias Hein A. Cemgil TTA AAML 170 67 0 28 Feb 2022
Understanding Adversarial Robustness from Feature Maps of Convolutional Layers Cong Xu Wei Zhang Jun Wang Min Yang AAML 18 2 0 25 Feb 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition Tianyu Pang Min-Bin Lin Xiao Yang Junyi Zhu Shuicheng Yan 6 119 0 21 Feb 2022
Fast Adversarial Training with Noise Augmentation: A Unified Perspective on RandStart and GradAlign Axi Niu Kang Zhang Chaoning Zhang Chenshuang Zhang In So Kweon Chang-Dong Yoo Yanning Zhang AAML 40 6 0 11 Feb 2022
NoisyMix: Boosting Model Robustness to Common Corruptions N. Benjamin Erichson S. H. Lim Winnie Xu Francisco Utrera Ziang Cao Michael W. Mahoney 11 17 0 02 Feb 2022
Probabilistically Robust Learning: Balancing Average- and Worst-case Performance Alexander Robey Luiz F. O. Chamon George J. Pappas Hamed Hassani AAML OOD 22 41 0 02 Feb 2022
Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks A. Harrington Arturo Deza OOD AAML 15 20 0 02 Feb 2022
Improving Robustness by Enhancing Weak Subnets Yong Guo David Stutz Bernt Schiele AAML 14 15 0 30 Jan 2022