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SmoothFool: An Efficient Framework for Computing Smooth Adversarial
  Perturbations

SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations

8 October 2019
Ali Dabouei
Sobhan Soleymani
Fariborz Taherkhani
J. Dawson
Nasser M. Nasrabadi
    AAML
ArXivPDFHTML

Papers citing "SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations"

34 / 34 papers shown
Title
SuperMix: Supervising the Mixing Data Augmentation
SuperMix: Supervising the Mixing Data Augmentation
Ali Dabouei
Sobhan Soleymani
Fariborz Taherkhani
Nasser M. Nasrabadi
67
100
0
10 Mar 2020
Evading Defenses to Transferable Adversarial Examples by
  Translation-Invariant Attacks
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks
Yinpeng Dong
Tianyu Pang
Hang Su
Jun Zhu
SILM
AAML
88
847
0
05 Apr 2019
SparseFool: a few pixels make a big difference
SparseFool: a few pixels make a big difference
Apostolos Modas
Seyed-Mohsen Moosavi-Dezfooli
P. Frossard
AAML
53
199
0
06 Nov 2018
Fast Geometrically-Perturbed Adversarial Faces
Fast Geometrically-Perturbed Adversarial Faces
Ali Dabouei
Sobhan Soleymani
J. Dawson
Nasser M. Nasrabadi
CVBM
AAML
45
65
0
24 Sep 2018
Are adversarial examples inevitable?
Are adversarial examples inevitable?
Ali Shafahi
Wenjie Huang
Christoph Studer
Soheil Feizi
Tom Goldstein
SILM
62
282
0
06 Sep 2018
Physical Adversarial Examples for Object Detectors
Physical Adversarial Examples for Object Detectors
Kevin Eykholt
Ivan Evtimov
Earlence Fernandes
Yue Liu
Amir Rahmati
Florian Tramèr
Atul Prakash
Tadayoshi Kohno
D. Song
AAML
92
469
0
20 Jul 2018
With Friends Like These, Who Needs Adversaries?
With Friends Like These, Who Needs Adversaries?
Saumya Jetley
Nicholas A. Lord
Philip Torr
AAML
51
70
0
11 Jul 2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using
  Generative Models
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models
Pouya Samangouei
Maya Kabkab
Rama Chellappa
AAML
GAN
84
1,177
0
17 May 2018
Semantic Adversarial Examples
Semantic Adversarial Examples
Hossein Hosseini
Radha Poovendran
GAN
AAML
89
199
0
16 Mar 2018
Divide, Denoise, and Defend against Adversarial Attacks
Divide, Denoise, and Defend against Adversarial Attacks
Seyed-Mohsen Moosavi-Dezfooli
A. Shrivastava
Oncel Tuzel
AAML
55
45
0
19 Feb 2018
Deflecting Adversarial Attacks with Pixel Deflection
Deflecting Adversarial Attacks with Pixel Deflection
Aaditya (Adi) Prakash
N. Moran
Solomon Garber
Antonella DiLillo
J. Storer
AAML
61
303
0
26 Jan 2018
Spatially Transformed Adversarial Examples
Spatially Transformed Adversarial Examples
Chaowei Xiao
Jun-Yan Zhu
Yue Liu
Warren He
M. Liu
D. Song
AAML
74
522
0
08 Jan 2018
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text
Nicholas Carlini
D. Wagner
AAML
94
1,079
0
05 Jan 2018
Defense against Adversarial Attacks Using High-Level Representation
  Guided Denoiser
Defense against Adversarial Attacks Using High-Level Representation Guided Denoiser
Fangzhou Liao
Ming Liang
Yinpeng Dong
Tianyu Pang
Xiaolin Hu
Jun Zhu
83
886
0
08 Dec 2017
One pixel attack for fooling deep neural networks
One pixel attack for fooling deep neural networks
Jiawei Su
Danilo Vasconcellos Vargas
Kouichi Sakurai
AAML
117
2,325
0
24 Oct 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
304
12,063
0
19 Jun 2017
MagNet: a Two-Pronged Defense against Adversarial Examples
MagNet: a Two-Pronged Defense against Adversarial Examples
Dongyu Meng
Hao Chen
AAML
46
1,207
0
25 May 2017
Formal Guarantees on the Robustness of a Classifier against Adversarial
  Manipulation
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation
Matthias Hein
Maksym Andriushchenko
AAML
110
511
0
23 May 2017
Ensemble Adversarial Training: Attacks and Defenses
Ensemble Adversarial Training: Attacks and Defenses
Florian Tramèr
Alexey Kurakin
Nicolas Papernot
Ian Goodfellow
Dan Boneh
Patrick McDaniel
AAML
177
2,725
0
19 May 2017
Universal Adversarial Perturbations Against Semantic Image Segmentation
Universal Adversarial Perturbations Against Semantic Image Segmentation
J. H. Metzen
Mummadi Chaithanya Kumar
Thomas Brox
Volker Fischer
AAML
124
287
0
19 Apr 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation
Interpretable Explanations of Black Boxes by Meaningful Perturbation
Ruth C. Fong
Andrea Vedaldi
FAtt
AAML
74
1,519
0
11 Apr 2017
Adversarial Examples for Semantic Segmentation and Object Detection
Adversarial Examples for Semantic Segmentation and Object Detection
Cihang Xie
Jianyu Wang
Zhishuai Zhang
Yuyin Zhou
Lingxi Xie
Alan Yuille
GAN
AAML
104
931
0
24 Mar 2017
Adversarial Examples for Semantic Image Segmentation
Adversarial Examples for Semantic Image Segmentation
Volker Fischer
Mummadi Chaithanya Kumar
J. H. Metzen
Thomas Brox
SSeg
GAN
AAML
66
119
0
03 Mar 2017
Adversarial Attacks on Neural Network Policies
Adversarial Attacks on Neural Network Policies
Sandy Huang
Nicolas Papernot
Ian Goodfellow
Yan Duan
Pieter Abbeel
MLAU
AAML
89
837
0
08 Feb 2017
Universal adversarial perturbations
Universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
Omar Fawzi
P. Frossard
AAML
136
2,528
0
26 Oct 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
261
8,552
0
16 Aug 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
540
5,897
0
08 Jul 2016
Augmenting Supervised Neural Networks with Unsupervised Objectives for
  Large-scale Image Classification
Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification
Y. Zhang
Kibok Lee
Honglak Lee
SSL
84
143
0
21 Jun 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
193,878
0
10 Dec 2015
The Limitations of Deep Learning in Adversarial Settings
The Limitations of Deep Learning in Adversarial Settings
Nicolas Papernot
Patrick McDaniel
S. Jha
Matt Fredrikson
Z. Berkay Celik
A. Swami
AAML
102
3,960
0
24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks
DeepFool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
AAML
148
4,895
0
14 Nov 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
274
19,049
0
20 Dec 2014
Return of the Devil in the Details: Delving Deep into Convolutional Nets
Return of the Devil in the Details: Delving Deep into Convolutional Nets
Ken Chatfield
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
215
3,418
0
14 May 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
270
14,918
1
21 Dec 2013
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