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RADAP: A Robust and Adaptive Defense Against Diverse Adversarial Patches
  on Face Recognition

RADAP: A Robust and Adaptive Defense Against Diverse Adversarial Patches on Face Recognition

29 November 2023
Xiaoliang Liu
Shen Furao
Jian Zhao
Changhai Nie
    AAML
ArXivPDFHTML

Papers citing "RADAP: A Robust and Adaptive Defense Against Diverse Adversarial Patches on Face Recognition"

5 / 5 papers shown
Title
Benchmarking the Spatial Robustness of DNNs via Natural and Adversarial Localized Corruptions
Benchmarking the Spatial Robustness of DNNs via Natural and Adversarial Localized Corruptions
Giulia Marchiori Pietrosanti
Giulio Rossolini
Alessandro Biondi
Giorgio Buttazzo
AAML
80
0
0
02 Apr 2025
RSTAM: An Effective Black-Box Impersonation Attack on Face Recognition
  using a Mobile and Compact Printer
RSTAM: An Effective Black-Box Impersonation Attack on Face Recognition using a Mobile and Compact Printer
Xiaoliang Liu
S. Furao
Jian Zhao
Changhai Nie
AAML
CVBM
23
5
0
25 Jun 2022
A Survey of Robust Adversarial Training in Pattern Recognition:
  Fundamental, Theory, and Methodologies
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies
Zhuang Qian
Kaizhu Huang
Qiufeng Wang
Xu-Yao Zhang
OOD
AAML
ObjD
49
71
0
26 Mar 2022
Robust Physical-World Attacks on Face Recognition
Robust Physical-World Attacks on Face Recognition
Xin-Yang Zheng
Yanbo Fan
Baoyuan Wu
Yong Zhang
Jue Wang
Shirui Pan
AAML
CVBM
30
40
0
20 Sep 2021
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
288
75,800
0
18 May 2015
1