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Physical Adversarial Examples for Object Detectors

Physical Adversarial Examples for Object Detectors

20 July 2018
Kevin Eykholt
Ivan Evtimov
Earlence Fernandes
Bo-wen Li
Amir Rahmati
Florian Tramèr
Atul Prakash
Tadayoshi Kohno
D. Song
    AAML
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Papers citing "Physical Adversarial Examples for Object Detectors"

36 / 86 papers shown
Title
On Robustness of Lane Detection Models to Physical-World Adversarial
  Attacks in Autonomous Driving
On Robustness of Lane Detection Models to Physical-World Adversarial Attacks in Autonomous Driving
Takami Sato
Qi Alfred Chen
AAML
ELM
35
6
0
06 Jul 2021
Improving Transferability of Adversarial Patches on Face Recognition
  with Generative Models
Improving Transferability of Adversarial Patches on Face Recognition with Generative Models
Zihao Xiao
Xianfeng Gao
Chilin Fu
Yinpeng Dong
Wei-zhe Gao
Xiaolu Zhang
Jun Zhou
Jun Zhu
AAML
CVBM
39
109
0
29 Jun 2021
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion
  based Perception in Autonomous Driving Under Physical-World Attacks
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks
Yulong Cao*
Ningfei Wang*
Chaowei Xiao
Dawei Yang
Jin Fang
Ruigang Yang
Qi Alfred Chen
Mingyan D. Liu
Bo-wen Li
AAML
24
217
0
17 Jun 2021
We Can Always Catch You: Detecting Adversarial Patched Objects WITH or
  WITHOUT Signature
We Can Always Catch You: Detecting Adversarial Patched Objects WITH or WITHOUT Signature
Binxiu Liang
Jiachun Li
Jianjun Huang
AAML
33
12
0
09 Jun 2021
3DB: A Framework for Debugging Computer Vision Models
3DB: A Framework for Debugging Computer Vision Models
Guillaume Leclerc
Hadi Salman
Andrew Ilyas
Sai H. Vemprala
Logan Engstrom
...
Pengchuan Zhang
Shibani Santurkar
Greg Yang
Ashish Kapoor
A. Madry
40
40
0
07 Jun 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
33
6
0
16 May 2021
LiBRe: A Practical Bayesian Approach to Adversarial Detection
LiBRe: A Practical Bayesian Approach to Adversarial Detection
Zhijie Deng
Xiao Yang
Shizhen Xu
Hang Su
Jun Zhu
BDL
AAML
20
61
0
27 Mar 2021
Robust and Accurate Object Detection via Adversarial Learning
Robust and Accurate Object Detection via Adversarial Learning
Xiangning Chen
Cihang Xie
Mingxing Tan
Li Zhang
Cho-Jui Hsieh
Boqing Gong
AAML
34
72
0
23 Mar 2021
"What's in the box?!": Deflecting Adversarial Attacks by Randomly
  Deploying Adversarially-Disjoint Models
"What's in the box?!": Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models
Sahar Abdelnabi
Mario Fritz
AAML
27
7
0
09 Feb 2021
Adversarial Attack on Facial Recognition using Visible Light
Adversarial Attack on Facial Recognition using Visible Light
Morgan Frearson
Kien Nguyen
AAML
19
7
0
25 Nov 2020
Dynamic Adversarial Patch for Evading Object Detection Models
Dynamic Adversarial Patch for Evading Object Detection Models
Shahar Hoory
T. Shapira
A. Shabtai
Yuval Elovici
AAML
18
40
0
25 Oct 2020
GreedyFool: Multi-Factor Imperceptibility and Its Application to
  Designing a Black-box Adversarial Attack
GreedyFool: Multi-Factor Imperceptibility and Its Application to Designing a Black-box Adversarial Attack
Hui Liu
Bo Zhao
Minzhi Ji
Peng Liu
AAML
29
6
0
14 Oct 2020
The Intriguing Relation Between Counterfactual Explanations and
  Adversarial Examples
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples
Timo Freiesleben
GAN
41
62
0
11 Sep 2020
SLAP: Improving Physical Adversarial Examples with Short-Lived
  Adversarial Perturbations
SLAP: Improving Physical Adversarial Examples with Short-Lived Adversarial Perturbations
Giulio Lovisotto
H.C.M. Turner
Ivo Sluganovic
Martin Strohmeier
Ivan Martinovic
AAML
19
101
0
08 Jul 2020
Drift with Devil: Security of Multi-Sensor Fusion based Localization in
  High-Level Autonomous Driving under GPS Spoofing (Extended Version)
Drift with Devil: Security of Multi-Sensor Fusion based Localization in High-Level Autonomous Driving under GPS Spoofing (Extended Version)
Junjie Shen
Jun Yeon Won
Zeyuan Chen
Qi Alfred Chen
AAML
16
122
0
18 Jun 2020
Blind Backdoors in Deep Learning Models
Blind Backdoors in Deep Learning Models
Eugene Bagdasaryan
Vitaly Shmatikov
AAML
FedML
SILM
46
298
0
08 May 2020
Adversarial Light Projection Attacks on Face Recognition Systems: A
  Feasibility Study
Adversarial Light Projection Attacks on Face Recognition Systems: A Feasibility Study
Luan Nguyen
Sunpreet S. Arora
Yuhang Wu
Hao Yang
AAML
19
88
0
24 Mar 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve
  Adversarial Robustness
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness
Ahmadreza Jeddi
M. Shafiee
Michelle Karg
C. Scharfenberger
A. Wong
OOD
AAML
67
63
0
02 Mar 2020
Understanding the Decision Boundary of Deep Neural Networks: An
  Empirical Study
Understanding the Decision Boundary of Deep Neural Networks: An Empirical Study
David Mickisch
F. Assion
Florens Greßner
W. Günther
M. Motta
AAML
19
34
0
05 Feb 2020
Safety Concerns and Mitigation Approaches Regarding the Use of Deep
  Learning in Safety-Critical Perception Tasks
Safety Concerns and Mitigation Approaches Regarding the Use of Deep Learning in Safety-Critical Perception Tasks
Oliver Willers
Sebastian Sudholt
Shervin Raafatnia
Stephanie Abrecht
28
80
0
22 Jan 2020
GhostImage: Remote Perception Attacks against Camera-based Image
  Classification Systems
GhostImage: Remote Perception Attacks against Camera-based Image Classification Systems
Yanmao Man
Ming Li
Ryan M. Gerdes
AAML
14
8
0
21 Jan 2020
Adversarial Example Generation using Evolutionary Multi-objective
  Optimization
Adversarial Example Generation using Evolutionary Multi-objective Optimization
Takahiro Suzuki
Shingo Takeshita
S. Ono
AAML
11
22
0
30 Dec 2019
Efficient Adversarial Training with Transferable Adversarial Examples
Efficient Adversarial Training with Transferable Adversarial Examples
Haizhong Zheng
Ziqi Zhang
Juncheng Gu
Honglak Lee
A. Prakash
AAML
24
108
0
27 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
Adversarial T-shirt! Evading Person Detectors in A Physical World
Adversarial T-shirt! Evading Person Detectors in A Physical World
Kaidi Xu
Gaoyuan Zhang
Sijia Liu
Quanfu Fan
Mengshu Sun
Hongge Chen
Pin-Yu Chen
Yanzhi Wang
Xue Lin
AAML
14
30
0
18 Oct 2019
Role of Spatial Context in Adversarial Robustness for Object Detection
Role of Spatial Context in Adversarial Robustness for Object Detection
Aniruddha Saha
Akshayvarun Subramanya
Koninika Patil
Hamed Pirsiavash
ObjD
AAML
32
53
0
30 Sep 2019
Defense Against Adversarial Attacks Using Feature Scattering-based
  Adversarial Training
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training
Haichao Zhang
Jianyu Wang
AAML
23
230
0
24 Jul 2019
Towards Adversarially Robust Object Detection
Towards Adversarially Robust Object Detection
Haichao Zhang
Jianyu Wang
AAML
ObjD
23
130
0
24 Jul 2019
Biometric Backdoors: A Poisoning Attack Against Unsupervised Template
  Updating
Biometric Backdoors: A Poisoning Attack Against Unsupervised Template Updating
Giulio Lovisotto
Simon Eberz
Ivan Martinovic
AAML
21
35
0
22 May 2019
Taking Care of The Discretization Problem: A Comprehensive Study of the
  Discretization Problem and A Black-Box Adversarial Attack in Discrete Integer
  Domain
Taking Care of The Discretization Problem: A Comprehensive Study of the Discretization Problem and A Black-Box Adversarial Attack in Discrete Integer Domain
Lei Bu
Yuchao Duan
Fu Song
Zhe Zhao
AAML
32
18
0
19 May 2019
Fooling automated surveillance cameras: adversarial patches to attack
  person detection
Fooling automated surveillance cameras: adversarial patches to attack person detection
Simen Thys
W. V. Ranst
Toon Goedemé
AAML
26
563
0
18 Apr 2019
SentiNet: Detecting Localized Universal Attacks Against Deep Learning
  Systems
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems
Edward Chou
Florian Tramèr
Giancarlo Pellegrino
AAML
173
287
0
02 Dec 2018
AdVersarial: Perceptual Ad Blocking meets Adversarial Machine Learning
AdVersarial: Perceptual Ad Blocking meets Adversarial Machine Learning
K. Makarychev
Pascal Dupré
Yury Makarychev
Giancarlo Pellegrino
Dan Boneh
AAML
29
64
0
08 Nov 2018
MeshAdv: Adversarial Meshes for Visual Recognition
MeshAdv: Adversarial Meshes for Visual Recognition
Chaowei Xiao
Dawei Yang
Bo-wen Li
Jia Deng
M. Liu
AAML
30
25
0
11 Oct 2018
ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object
  Detector
ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector
Shang-Tse Chen
Cory Cornelius
Jason Martin
Duen Horng Chau
ObjD
162
424
0
16 Apr 2018
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,842
0
08 Jul 2016
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