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Adversarial Vision Challenge

Adversarial Vision Challenge

6 August 2018
Wieland Brendel
Jonas Rauber
Alexey Kurakin
Nicolas Papernot
Behar Veliqi
M. Salathé
Sharada Mohanty
Matthias Bethge
    AAML
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Papers citing "Adversarial Vision Challenge"

17 / 17 papers shown
Title
Are Classification Robustness and Explanation Robustness Really Strongly
  Correlated? An Analysis Through Input Loss Landscape
Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape
Tiejin Chen
Wenwang Huang
Linsey Pang
Dongsheng Luo
Hua Wei
OOD
49
0
0
09 Mar 2024
Physical Adversarial Attacks on Deep Neural Networks for Traffic Sign
  Recognition: A Feasibility Study
Physical Adversarial Attacks on Deep Neural Networks for Traffic Sign Recognition: A Feasibility Study
Fabian Woitschek
G. Schneider
AAML
38
9
0
27 Feb 2023
Better Diffusion Models Further Improve Adversarial Training
Better Diffusion Models Further Improve Adversarial Training
Zekai Wang
Tianyu Pang
Chao Du
Min Lin
Weiwei Liu
Shuicheng Yan
DiffM
26
210
0
09 Feb 2023
Selecting Models based on the Risk of Damage Caused by Adversarial
  Attacks
Selecting Models based on the Risk of Damage Caused by Adversarial Attacks
Jona Klemenc
Holger Trittenbach
AAML
32
1
0
28 Jan 2023
Decision-based Black-box Attack Against Vision Transformers via
  Patch-wise Adversarial Removal
Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal
Yucheng Shi
Yahong Han
Yu-an Tan
Xiaohui Kuang
45
30
0
07 Dec 2021
Ensemble-in-One: Learning Ensemble within Random Gated Networks for
  Enhanced Adversarial Robustness
Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness
Yi Cai
Xuefei Ning
Huazhong Yang
Yu Wang
AAML
27
4
0
27 Mar 2021
RobustBench: a standardized adversarial robustness benchmark
RobustBench: a standardized adversarial robustness benchmark
Francesco Croce
Maksym Andriushchenko
Vikash Sehwag
Edoardo Debenedetti
Nicolas Flammarion
M. Chiang
Prateek Mittal
Matthias Hein
VLM
234
680
0
19 Oct 2020
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated
  Gradients
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated Gradients
Yifei Huang
Yaodong Yu
Hongyang R. Zhang
Yi Ma
Yuan Yao
AAML
37
26
0
28 Sep 2020
Random Smoothing Might be Unable to Certify $\ell_\infty$ Robustness for
  High-Dimensional Images
Random Smoothing Might be Unable to Certify ℓ∞\ell_\inftyℓ∞​ Robustness for High-Dimensional Images
Avrim Blum
Travis Dick
N. Manoj
Hongyang R. Zhang
AAML
31
79
0
10 Feb 2020
Benchmarking Adversarial Robustness
Benchmarking Adversarial Robustness
Yinpeng Dong
Qi-An Fu
Xiao Yang
Tianyu Pang
Hang Su
Zihao Xiao
Jun Zhu
AAML
28
36
0
26 Dec 2019
Design and Interpretation of Universal Adversarial Patches in Face
  Detection
Design and Interpretation of Universal Adversarial Patches in Face Detection
Xiao Yang
Fangyun Wei
Hongyang R. Zhang
Jun Zhu
AAML
CVBM
52
43
0
30 Nov 2019
Towards Large yet Imperceptible Adversarial Image Perturbations with
  Perceptual Color Distance
Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color Distance
Zhengyu Zhao
Zhuoran Liu
Martha Larson
AAML
18
142
0
06 Nov 2019
Curls & Whey: Boosting Black-Box Adversarial Attacks
Curls & Whey: Boosting Black-Box Adversarial Attacks
Yucheng Shi
Siyu Wang
Yahong Han
AAML
18
116
0
02 Apr 2019
Excessive Invariance Causes Adversarial Vulnerability
Excessive Invariance Causes Adversarial Vulnerability
J. Jacobsen
Jens Behrmann
R. Zemel
Matthias Bethge
AAML
33
166
0
01 Nov 2018
Humans can decipher adversarial images
Humans can decipher adversarial images
Zhenglong Zhou
C. Firestone
AAML
16
121
0
11 Sep 2018
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
296
3,113
0
04 Nov 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
308
5,847
0
08 Jul 2016
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