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Bag of Tricks for Adversarial Training

Bag of Tricks for Adversarial Training

1 October 2020
Tianyu Pang
Xiao Yang
Yinpeng Dong
Hang Su
Jun Zhu
    AAML
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Papers citing "Bag of Tricks for Adversarial Training"

49 / 49 papers shown
Title
Evolution-based Region Adversarial Prompt Learning for Robustness Enhancement in Vision-Language Models
Evolution-based Region Adversarial Prompt Learning for Robustness Enhancement in Vision-Language Models
X. Jia
Sensen Gao
Simeng Qin
Ke Ma
X. Li
Yihao Huang
Wei Dong
Yang Liu
Xiaochun Cao
AAML
VLM
58
0
0
17 Mar 2025
Long-tailed Adversarial Training with Self-Distillation
Seungju Cho
Hongsin Lee
Changick Kim
AAML
TTA
118
0
0
09 Mar 2025
Dynamic Guidance Adversarial Distillation with Enhanced Teacher
  Knowledge
Dynamic Guidance Adversarial Distillation with Enhanced Teacher Knowledge
Hyejin Park
Dongbo Min
AAML
24
2
0
03 Sep 2024
Benchmarking the Robustness of Temporal Action Detection Models Against
  Temporal Corruptions
Benchmarking the Robustness of Temporal Action Detection Models Against Temporal Corruptions
Runhao Zeng
Xiaoyong Chen
Jiaming Liang
Huisi Wu
Guangzhong Cao
Yong Guo
AAML
32
3
0
29 Mar 2024
Indirect Gradient Matching for Adversarial Robust Distillation
Indirect Gradient Matching for Adversarial Robust Distillation
Hongsin Lee
Seungju Cho
Changick Kim
AAML
FedML
48
2
0
06 Dec 2023
SCAAT: Improving Neural Network Interpretability via Saliency
  Constrained Adaptive Adversarial Training
SCAAT: Improving Neural Network Interpretability via Saliency Constrained Adaptive Adversarial Training
Rui Xu
Wenkang Qin
Peixiang Huang
Hao Wang
Lin Luo
FAtt
AAML
17
2
0
09 Nov 2023
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from
  a Minimax Game Perspective
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective
Yifei Wang
Liangchen Li
Jiansheng Yang
Zhouchen Lin
Yisen Wang
16
11
0
30 Oct 2023
On the Importance of Backbone to the Adversarial Robustness of Object Detectors
On the Importance of Backbone to the Adversarial Robustness of Object Detectors
Xiao-Li Li
Hang Chen
Xiaolin Hu
AAML
34
4
0
27 May 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks &
  Defenses
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
48
0
18 May 2023
Beyond Empirical Risk Minimization: Local Structure Preserving
  Regularization for Improving Adversarial Robustness
Beyond Empirical Risk Minimization: Local Structure Preserving Regularization for Improving Adversarial Robustness
Wei Wei
Jiahuan Zhou
Yingying Wu
AAML
11
0
0
29 Mar 2023
CAT:Collaborative Adversarial Training
CAT:Collaborative Adversarial Training
Xingbin Liu
Huafeng Kuang
Xianming Lin
Yongjian Wu
Rongrong Ji
AAML
8
4
0
27 Mar 2023
Randomized Adversarial Training via Taylor Expansion
Randomized Adversarial Training via Taylor Expansion
Gao Jin
Xinping Yi
Dengyu Wu
Ronghui Mu
Xiaowei Huang
AAML
22
34
0
19 Mar 2023
A Comprehensive Study on Robustness of Image Classification Models:
  Benchmarking and Rethinking
A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking
Chang-Shu Liu
Yinpeng Dong
Wenzhao Xiang
X. Yang
Hang Su
Junyi Zhu
YueFeng Chen
Yuan He
H. Xue
Shibao Zheng
OOD
VLM
AAML
15
72
0
28 Feb 2023
Better Diffusion Models Further Improve Adversarial Training
Better Diffusion Models Further Improve Adversarial Training
Zekai Wang
Tianyu Pang
Chao Du
Min-Bin Lin
Weiwei Liu
Shuicheng Yan
DiffM
14
207
0
09 Feb 2023
A Data-Centric Approach for Improving Adversarial Training Through the
  Lens of Out-of-Distribution Detection
A Data-Centric Approach for Improving Adversarial Training Through the Lens of Out-of-Distribution Detection
Mohammad Azizmalayeri
Arman Zarei
Alireza Isavand
M. T. Manzuri
M. Rohban
OODD
24
0
0
25 Jan 2023
Scaling Adversarial Training to Large Perturbation Bounds
Scaling Adversarial Training to Large Perturbation Bounds
Sravanti Addepalli
Samyak Jain
Gaurang Sriramanan
R. Venkatesh Babu
AAML
13
22
0
18 Oct 2022
When Adversarial Training Meets Vision Transformers: Recipes from
  Training to Architecture
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture
Yi Mo
Dongxian Wu
Yifei Wang
Yiwen Guo
Yisen Wang
ViT
27
52
0
14 Oct 2022
Towards Out-of-Distribution Adversarial Robustness
Towards Out-of-Distribution Adversarial Robustness
Adam Ibrahim
Charles Guille-Escuret
Ioannis Mitliagkas
Irina Rish
David M. Krueger
P. Bashivan
OOD
23
6
0
06 Oct 2022
Inducing Data Amplification Using Auxiliary Datasets in Adversarial
  Training
Inducing Data Amplification Using Auxiliary Datasets in Adversarial Training
Saehyung Lee
Hyungyu Lee
AAML
19
2
0
27 Sep 2022
Bag of Tricks for FGSM Adversarial Training
Bag of Tricks for FGSM Adversarial Training
Zichao Li
Li Liu
Zeyu Wang
Yuyin Zhou
Cihang Xie
AAML
14
6
0
06 Sep 2022
Building Robust Ensembles via Margin Boosting
Building Robust Ensembles via Margin Boosting
Dinghuai Zhang
Hongyang R. Zhang
Aaron Courville
Yoshua Bengio
Pradeep Ravikumar
A. Suggala
AAML
UQCV
27
15
0
07 Jun 2022
Case-Aware Adversarial Training
Case-Aware Adversarial Training
Mingyuan Fan
Yang Liu
Ximeng Liu
AAML
14
1
0
20 Apr 2022
Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot
  Learning
Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning
Mathias Lechner
Alexander Amini
Daniela Rus
T. Henzinger
AAML
16
9
0
15 Apr 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights
Enhancing Adversarial Training with Second-Order Statistics of Weights
Gao Jin
Xinping Yi
Wei Huang
S. Schewe
Xiaowei Huang
AAML
10
46
0
11 Mar 2022
Towards Efficient Data-Centric Robust Machine Learning with Noise-based
  Augmentation
Towards Efficient Data-Centric Robust Machine Learning with Noise-based Augmentation
Xiaogeng Liu
Haoyu Wang
Yechao Zhang
Fangzhou Wu
Shengshan Hu
OOD
17
11
0
08 Mar 2022
Global-Local Regularization Via Distributional Robustness
Global-Local Regularization Via Distributional Robustness
Hoang Phan
Trung Le
Trung-Nghia Phung
Tu Bui
Nhat Ho
Dinh Q. Phung
OOD
9
12
0
01 Mar 2022
A Unified Wasserstein Distributional Robustness Framework for
  Adversarial Training
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training
Tu Bui
Trung Le
Quan Hung Tran
He Zhao
Dinh Q. Phung
AAML
OOD
18
42
0
27 Feb 2022
On the Effectiveness of Adversarial Training against Backdoor Attacks
On the Effectiveness of Adversarial Training against Backdoor Attacks
Yinghua Gao
Dongxian Wu
Jingfeng Zhang
Guanhao Gan
Shutao Xia
Gang Niu
Masashi Sugiyama
AAML
24
22
0
22 Feb 2022
Sparsity Winning Twice: Better Robust Generalization from More Efficient
  Training
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training
Tianlong Chen
Zhenyu (Allen) Zhang
Pengju Wang
Santosh Balachandra
Haoyu Ma
Zehao Wang
Zhangyang Wang
OOD
AAML
77
46
0
20 Feb 2022
Scale-Invariant Adversarial Attack for Evaluating and Enhancing
  Adversarial Defenses
Scale-Invariant Adversarial Attack for Evaluating and Enhancing Adversarial Defenses
Mengting Xu
Tao Zhang
Zhongnian Li
Daoqiang Zhang
AAML
28
1
0
29 Jan 2022
Can Model Compression Improve NLP Fairness
Can Model Compression Improve NLP Fairness
Guangxuan Xu
Qingyuan Hu
18
26
0
21 Jan 2022
On the Convergence and Robustness of Adversarial Training
On the Convergence and Robustness of Adversarial Training
Yisen Wang
Xingjun Ma
James Bailey
Jinfeng Yi
Bowen Zhou
Quanquan Gu
AAML
192
345
0
15 Dec 2021
LTD: Low Temperature Distillation for Robust Adversarial Training
LTD: Low Temperature Distillation for Robust Adversarial Training
Erh-Chung Chen
Che-Rung Lee
AAML
19
26
0
03 Nov 2021
Parameterizing Activation Functions for Adversarial Robustness
Parameterizing Activation Functions for Adversarial Robustness
Sihui Dai
Saeed Mahloujifar
Prateek Mittal
AAML
26
32
0
11 Oct 2021
Adversarial Token Attacks on Vision Transformers
Adversarial Token Attacks on Vision Transformers
Ameya Joshi
Gauri Jagatap
C. Hegde
ViT
22
19
0
08 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural
  Networks
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
Hanxun Huang
Yisen Wang
S. Erfani
Quanquan Gu
James Bailey
Xingjun Ma
AAML
TPM
44
100
0
07 Oct 2021
LibFewShot: A Comprehensive Library for Few-shot Learning
LibFewShot: A Comprehensive Library for Few-shot Learning
Wenbin Li
Ziyi
Ziyi Wang
Xuesong Yang
C. Dong
...
Jing Huo
Yinghuan Shi
Lei Wang
Yang Gao
Jiebo Luo
VLM
106
66
0
10 Sep 2021
Deep Image Destruction: Vulnerability of Deep Image-to-Image Models
  against Adversarial Attacks
Deep Image Destruction: Vulnerability of Deep Image-to-Image Models against Adversarial Attacks
Jun-Ho Choi
Huan Zhang
Jun-Hyuk Kim
Cho-Jui Hsieh
Jong-Seok Lee
VLM
19
7
0
30 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima
Relating Adversarially Robust Generalization to Flat Minima
David Stutz
Matthias Hein
Bernt Schiele
OOD
19
65
0
09 Apr 2021
Adversarial Robustness under Long-Tailed Distribution
Adversarial Robustness under Long-Tailed Distribution
Tong Wu
Ziwei Liu
Qingqiu Huang
Yu Wang
Dahua Lin
13
76
0
06 Apr 2021
On the Adversarial Robustness of Vision Transformers
On the Adversarial Robustness of Vision Transformers
Rulin Shao
Zhouxing Shi
Jinfeng Yi
Pin-Yu Chen
Cho-Jui Hsieh
ViT
18
137
0
29 Mar 2021
Consistency Regularization for Adversarial Robustness
Consistency Regularization for Adversarial Robustness
Jihoon Tack
Sihyun Yu
Jongheon Jeong
Minseon Kim
S. Hwang
Jinwoo Shin
AAML
23
57
0
08 Mar 2021
Dynamic Efficient Adversarial Training Guided by Gradient Magnitude
Dynamic Efficient Adversarial Training Guided by Gradient Magnitude
Fu Lee Wang
Yanghao Zhang
Yanbin Zheng
Wenjie Ruan
18
1
0
04 Mar 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training
Low Curvature Activations Reduce Overfitting in Adversarial Training
Vasu Singla
Sahil Singla
David Jacobs
S. Feizi
AAML
17
45
0
15 Feb 2021
Uncovering the Limits of Adversarial Training against Norm-Bounded
  Adversarial Examples
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples
Sven Gowal
Chongli Qin
J. Uesato
Timothy A. Mann
Pushmeet Kohli
AAML
17
323
0
07 Oct 2020
Adversarial Vertex Mixup: Toward Better Adversarially Robust
  Generalization
Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization
Saehyung Lee
Hyungyu Lee
Sungroh Yoon
AAML
151
113
0
05 Mar 2020
Instance adaptive adversarial training: Improved accuracy tradeoffs in
  neural nets
Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets
Yogesh Balaji
Tom Goldstein
Judy Hoffman
AAML
124
102
0
17 Oct 2019
Aggregated Residual Transformations for Deep Neural Networks
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Z. Tu
Kaiming He
261
10,196
0
16 Nov 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
250
5,830
0
08 Jul 2016
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