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Defending Against Universal Perturbations With Shared Adversarial
  Training

Defending Against Universal Perturbations With Shared Adversarial Training

10 December 2018
Chaithanya Kumar Mummadi
Thomas Brox
J. H. Metzen
    AAML
ArXivPDFHTML

Papers citing "Defending Against Universal Perturbations With Shared Adversarial Training"

18 / 18 papers shown
Title
Robust Decentralized Learning with Local Updates and Gradient Tracking
Robust Decentralized Learning with Local Updates and Gradient Tracking
Sajjad Ghiasvand
Amirhossein Reisizadeh
Mahnoosh Alizadeh
Ramtin Pedarsani
28
3
0
02 May 2024
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
34
49
0
18 May 2023
AdaptGuard: Defending Against Universal Attacks for Model Adaptation
AdaptGuard: Defending Against Universal Attacks for Model Adaptation
Lijun Sheng
Jian Liang
R. He
Zilei Wang
Tien-Ping Tan
AAML
40
5
0
19 Mar 2023
Universal Adversarial Directions
Universal Adversarial Directions
Ching Lam Choi
Farzan Farnia
AAML
9
0
0
28 Oct 2022
Adversarial Vulnerability of Temporal Feature Networks for Object
  Detection
Adversarial Vulnerability of Temporal Feature Networks for Object Detection
Svetlana Pavlitskaya
Nikolai Polley
Michael Weber
J. Marius Zöllner
AAML
14
2
0
23 Aug 2022
Vector Quantisation for Robust Segmentation
Vector Quantisation for Robust Segmentation
Ainkaran Santhirasekaram
Avinash Kori
Mathias Winkler
A. Rockall
Ben Glocker
OOD
19
9
0
05 Jul 2022
Investigating Top-$k$ White-Box and Transferable Black-box Attack
Investigating Top-kkk White-Box and Transferable Black-box Attack
Chaoning Zhang
Philipp Benz
Adil Karjauv
Jae-Won Cho
Kang Zhang
In So Kweon
31
42
0
30 Mar 2022
Advances in adversarial attacks and defenses in computer vision: A
  survey
Advances in adversarial attacks and defenses in computer vision: A survey
Naveed Akhtar
Ajmal Saeed Mian
Navid Kardan
M. Shah
AAML
26
235
0
01 Aug 2021
Towards Robust General Medical Image Segmentation
Towards Robust General Medical Image Segmentation
Laura Alexandra Daza
Juan C. Pérez
Pablo Arbelaez
OOD
20
25
0
09 Jul 2021
Real-time Detection of Practical Universal Adversarial Perturbations
Real-time Detection of Practical Universal Adversarial Perturbations
Kenneth T. Co
Luis Muñoz-González
Leslie Kanthan
Emil C. Lupu
AAML
17
6
0
16 May 2021
Salient Feature Extractor for Adversarial Defense on Deep Neural
  Networks
Salient Feature Extractor for Adversarial Defense on Deep Neural Networks
Jinyin Chen
Ruoxi Chen
Haibin Zheng
Zhaoyan Ming
Wenrong Jiang
Chen Cui
AAML
11
10
0
14 May 2021
Universal Adversarial Training with Class-Wise Perturbations
Universal Adversarial Training with Class-Wise Perturbations
Philipp Benz
Chaoning Zhang
Adil Karjauv
In So Kweon
AAML
8
26
0
07 Apr 2021
A Survey On Universal Adversarial Attack
A Survey On Universal Adversarial Attack
Chaoning Zhang
Philipp Benz
Chenguo Lin
Adil Karjauv
Jing Wu
In So Kweon
AAML
21
90
0
02 Mar 2021
Locally optimal detection of stochastic targeted universal adversarial
  perturbations
Locally optimal detection of stochastic targeted universal adversarial perturbations
Amish Goel
P. Moulin
AAML
7
2
0
08 Dec 2020
Adversarial Ranking Attack and Defense
Adversarial Ranking Attack and Defense
Mo Zhou
Zhenxing Niu
Le Wang
Qilin Zhang
G. Hua
28
38
0
26 Feb 2020
A simple way to make neural networks robust against diverse image
  corruptions
A simple way to make neural networks robust against diverse image corruptions
E. Rusak
Lukas Schott
Roland S. Zimmermann
Julian Bitterwolf
Oliver Bringmann
Matthias Bethge
Wieland Brendel
19
64
0
16 Jan 2020
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
261
3,109
0
04 Nov 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
281
5,833
0
08 Jul 2016
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