Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2303.16697
Cited By
Latent Feature Relation Consistency for Adversarial Robustness
29 March 2023
Xingbin Liu
Huafeng Kuang
Hong Liu
Xianming Lin
Yongjian Wu
Rongrong Ji
AAML
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Latent Feature Relation Consistency for Adversarial Robustness"
14 / 14 papers shown
Title
Robust Pre-Training by Adversarial Contrastive Learning
Ziyu Jiang
Tianlong Chen
Ting-Li Chen
Zhangyang Wang
87
231
0
26 Oct 2020
Geometry-aware Instance-reweighted Adversarial Training
Jingfeng Zhang
Jianing Zhu
Gang Niu
Bo Han
Masashi Sugiyama
Mohan Kankanhalli
AAML
53
276
0
05 Oct 2020
A Self-supervised Approach for Adversarial Robustness
Muzammal Naseer
Salman Khan
Munawar Hayat
Fahad Shahbaz Khan
Fatih Porikli
AAML
66
257
0
08 Jun 2020
Transferable, Controllable, and Inconspicuous Adversarial Attacks on Person Re-identification With Deep Mis-Ranking
Hongjun Wang
Guangrun Wang
Ya Li
Dongyu Zhang
Liang Lin
AAML
47
83
0
08 Apr 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Francesco Croce
Matthias Hein
AAML
211
1,837
0
03 Mar 2020
Square Attack: a query-efficient black-box adversarial attack via random search
Maksym Andriushchenko
Francesco Croce
Nicolas Flammarion
Matthias Hein
AAML
75
987
0
29 Nov 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack
Francesco Croce
Matthias Hein
AAML
84
488
0
03 Jul 2019
Model-free Deep Reinforcement Learning for Urban Autonomous Driving
Jianyu Chen
Bodi Yuan
Masayoshi Tomizuka
59
264
0
20 Apr 2019
Defensive Quantization: When Efficiency Meets Robustness
Ji Lin
Chuang Gan
Song Han
MQ
69
203
0
17 Apr 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 Risk and the Dangers of Evaluating Against Weak Attacks
J. Uesato
Brendan O'Donoghue
Aaron van den Oord
Pushmeet Kohli
AAML
145
601
0
15 Feb 2018
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
277
12,029
0
19 Jun 2017
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
237
8,548
0
16 Aug 2016
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
320
7,971
0
23 May 2016
1