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Two-Face: Adversarial Audit of Commercial Face Recognition Systems

Two-Face: Adversarial Audit of Commercial Face Recognition Systems

17 November 2021
S. Jaiswal
K. Duggirala
A. Dash
Animesh Mukherjee
    MLAU
    AAML
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Papers citing "Two-Face: Adversarial Audit of Commercial Face Recognition Systems"

4 / 4 papers shown
Title
HateProof: Are Hateful Meme Detection Systems really Robust?
HateProof: Are Hateful Meme Detection Systems really Robust?
Piush Aggarwal
Pranit Chawla
Mithun Das
Punyajoy Saha
Binny Mathew
Torsten Zesch
Animesh Mukherjee
AAML
34
8
0
11 Feb 2023
Learning Transferable 3D Adversarial Cloaks for Deep Trained Detectors
Learning Transferable 3D Adversarial Cloaks for Deep Trained Detectors
Arman Maesumi
Mingkang Zhu
Yi Wang
Tianlong Chen
Zhangyang Wang
Chandrajit L. Bajaj
24
8
0
22 Apr 2021
Adversarial Camouflage: Hiding Physical-World Attacks with Natural
  Styles
Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles
Ranjie Duan
Xingjun Ma
Yisen Wang
James Bailey
•. A. K. Qin
Yun Yang
AAML
167
224
0
08 Mar 2020
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
323
4,212
0
23 Aug 2019
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