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2012.00558
Cited By
Robustness Out of the Box: Compositional Representations Naturally Defend Against Black-Box Patch Attacks
1 December 2020
Christian Cosgrove
Adam Kortylewski
Chenglin Yang
Alan Yuille
AAML
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Papers citing
"Robustness Out of the Box: Compositional Representations Naturally Defend Against Black-Box Patch Attacks"
21 / 21 papers shown
Title
Compositional Convolutional Neural Networks: A Robust and Interpretable Model for Object Recognition under Occlusion
Adam Kortylewski
Qing Liu
Angtian Wang
Yihong Sun
Alan Yuille
51
78
0
28 Jun 2020
Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks
Francesco Croce
Maksym Andriushchenko
Naman D. Singh
Nicolas Flammarion
Matthias Hein
68
101
0
23 Jun 2020
Robust Object Detection under Occlusion with Context-Aware CompositionalNets
Angtian Wang
Yihong Sun
Adam Kortylewski
Alan Yuille
ObjD
78
114
0
24 May 2020
Adversarial Training against Location-Optimized Adversarial Patches
Sukrut Rao
David Stutz
Bernt Schiele
AAML
39
92
0
05 May 2020
PatchAttack: A Black-box Texture-based Attack with Reinforcement Learning
Chenglin Yang
Adam Kortylewski
Cihang Xie
Yinzhi Cao
Alan Yuille
AAML
66
109
0
12 Apr 2020
Certified Defenses for Adversarial Patches
Ping Yeh-Chiang
Renkun Ni
Ahmed Abdelkader
Chen Zhu
Christoph Studer
Tom Goldstein
AAML
39
171
0
14 Mar 2020
Compositional Convolutional Neural Networks: A Deep Architecture with Innate Robustness to Partial Occlusion
Adam Kortylewski
Ju He
Qing Liu
Alan Yuille
85
91
0
10 Mar 2020
Adversarial Examples Improve Image Recognition
Cihang Xie
Mingxing Tan
Boqing Gong
Jiang Wang
Alan Yuille
Quoc V. Le
AAML
114
565
0
21 Nov 2019
Combining Compositional Models and Deep Networks For Robust Object Classification under Occlusion
Adam Kortylewski
Qing Liu
Huiyu Wang
Zhishuai Zhang
Alan Yuille
59
62
0
28 May 2019
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
Sangdoo Yun
Dongyoon Han
Seong Joon Oh
Sanghyuk Chun
Junsuk Choe
Y. Yoo
OOD
604
4,766
0
13 May 2019
Robustness of Object Recognition under Extreme Occlusion in Humans and Computational Models
Hongru Zhu
Peng Tang
Jeongho Park
Soojin Park
Alan Yuille
58
49
0
11 May 2019
Theoretically Principled Trade-off between Robustness and Accuracy
Hongyang R. Zhang
Yaodong Yu
Jiantao Jiao
Eric Xing
L. Ghaoui
Michael I. Jordan
118
2,542
0
24 Jan 2019
Feature Denoising for Improving Adversarial Robustness
Cihang Xie
Yuxin Wu
Laurens van der Maaten
Alan Yuille
Kaiming He
102
908
0
09 Dec 2018
Adversarial Logit Pairing
Harini Kannan
Alexey Kurakin
Ian Goodfellow
AAML
92
628
0
16 Mar 2018
Adversarial Patch
Tom B. Brown
Dandelion Mané
Aurko Roy
Martín Abadi
Justin Gilmer
AAML
70
1,094
0
27 Dec 2017
Interpretable Convolutional Neural Networks
Quanshi Zhang
Ying Nian Wu
Song-Chun Zhu
FAtt
64
779
0
02 Oct 2017
Improved Regularization of Convolutional Neural Networks with Cutout
Terrance Devries
Graham W. Taylor
107
3,758
0
15 Aug 2017
Detecting Semantic Parts on Partially Occluded Objects
Jianyu Wang
Cihang Xie
Zhishuai Zhang
Jun Zhu
Lingxi Xie
Alan Yuille
51
34
0
25 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
267
12,029
0
19 Jun 2017
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
231
19,017
0
20 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.3K
100,213
0
04 Sep 2014
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