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Defending Against Physically Realizable Attacks on Image Classification

Defending Against Physically Realizable Attacks on Image Classification

20 September 2019
Tong Wu
Liang Tong
Yevgeniy Vorobeychik
    AAML
ArXivPDFHTML

Papers citing "Defending Against Physically Realizable Attacks on Image Classification"

21 / 21 papers shown
Title
Fast Adversarial Training with Weak-to-Strong Spatial-Temporal Consistency in the Frequency Domain on Videos
Fast Adversarial Training with Weak-to-Strong Spatial-Temporal Consistency in the Frequency Domain on Videos
Songping Wang
Hanqing Liu
Yueming Lyu
Xiantao Hu
Ziwen He
W. Wang
Caifeng Shan
L. Wang
AAML
88
0
0
21 Apr 2025
Fall Leaf Adversarial Attack on Traffic Sign Classification
Fall Leaf Adversarial Attack on Traffic Sign Classification
Anthony Etim
Jakub Szefer
AAML
71
3
0
27 Nov 2024
PatchCURE: Improving Certifiable Robustness, Model Utility, and
  Computation Efficiency of Adversarial Patch Defenses
PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses
Chong Xiang
Tong Wu
Sihui Dai
Jonathan Petit
Suman Jana
Prateek Mittal
45
2
0
19 Oct 2023
Group-based Robustness: A General Framework for Customized Robustness in
  the Real World
Group-based Robustness: A General Framework for Customized Robustness in the Real World
Weiran Lin
Keane Lucas
Neo Eyal
Lujo Bauer
Michael K. Reiter
Mahmood Sharif
OOD
AAML
22
1
0
29 Jun 2023
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
37
49
0
18 May 2023
Self-recoverable Adversarial Examples: A New Effective Protection
  Mechanism in Social Networks
Self-recoverable Adversarial Examples: A New Effective Protection Mechanism in Social Networks
Jiawei Zhang
Jinwei Wang
Hao Wang
X. Luo
AAML
25
28
0
26 Apr 2022
Why adversarial training can hurt robust accuracy
Why adversarial training can hurt robust accuracy
Jacob Clarysse
Julia Hörrmann
Fanny Yang
AAML
13
18
0
03 Mar 2022
Segment and Complete: Defending Object Detectors against Adversarial
  Patch Attacks with Robust Patch Detection
Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detection
Jiangjiang Liu
Alexander Levine
Chun Pong Lau
Ramalingam Chellappa
S. Feizi
AAML
24
76
0
08 Dec 2021
Towards Practical Deployment-Stage Backdoor Attack on Deep Neural
  Networks
Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks
Xiangyu Qi
Tinghao Xie
Ruizhe Pan
Jifeng Zhu
Yong-Liang Yang
Kai Bu
AAML
25
57
0
25 Nov 2021
TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep
  Neural Network Systems
TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep Neural Network Systems
Bao Gia Doan
Minhui Xue
Shiqing Ma
Ehsan Abbasnejad
D. Ranasinghe
AAML
35
53
0
19 Nov 2021
Generative Dynamic Patch Attack
Generative Dynamic Patch Attack
Xiang Li
Shihao Ji
AAML
19
22
0
08 Nov 2021
Trustworthy AI: From Principles to Practices
Trustworthy AI: From Principles to Practices
Bo-wen Li
Peng Qi
Bo Liu
Shuai Di
Jingen Liu
Jiquan Pei
Jinfeng Yi
Bowen Zhou
117
355
0
04 Oct 2021
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
Removing Adversarial Noise in Class Activation Feature Space
Removing Adversarial Noise in Class Activation Feature Space
Dawei Zhou
N. Wang
Chunlei Peng
Xinbo Gao
Xiaoyu Wang
Jun Yu
Tongliang Liu
AAML
25
28
0
19 Apr 2021
Adversarial YOLO: Defense Human Detection Patch Attacks via Detecting
  Adversarial Patches
Adversarial YOLO: Defense Human Detection Patch Attacks via Detecting Adversarial Patches
Nan Ji
YanFei Feng
Haidong Xie
Xueshuang Xiang
Naijin Liu
AAML
39
33
0
16 Mar 2021
Error Diffusion Halftoning Against Adversarial Examples
Error Diffusion Halftoning Against Adversarial Examples
Shao-Yuan Lo
Vishal M. Patel
DiffM
10
4
0
23 Jan 2021
Optimism in the Face of Adversity: Understanding and Improving Deep
  Learning through Adversarial Robustness
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness
Guillermo Ortiz-Jiménez
Apostolos Modas
Seyed-Mohsen Moosavi-Dezfooli
P. Frossard
AAML
29
48
0
19 Oct 2020
MultAV: Multiplicative Adversarial Videos
MultAV: Multiplicative Adversarial Videos
Shao-Yuan Lo
Vishal M. Patel
AAML
26
8
0
17 Sep 2020
Stylized Adversarial Defense
Stylized Adversarial Defense
Muzammal Naseer
Salman Khan
Munawar Hayat
F. Khan
Fatih Porikli
GAN
AAML
20
16
0
29 Jul 2020
PatchGuard: A Provably Robust Defense against Adversarial Patches via
  Small Receptive Fields and Masking
PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking
Chong Xiang
A. Bhagoji
Vikash Sehwag
Prateek Mittal
AAML
22
29
0
17 May 2020
Minority Reports Defense: Defending Against Adversarial Patches
Minority Reports Defense: Defending Against Adversarial Patches
Michael McCoyd
Won Park
Steven Chen
Neil Shah
Ryan Roggenkemper
Minjune Hwang
J. Liu
David A. Wagner
AAML
6
54
0
28 Apr 2020
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