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AFLOW: Developing Adversarial Examples under Extremely Noise-limited
  Settings

AFLOW: Developing Adversarial Examples under Extremely Noise-limited Settings

15 October 2023
Renyang Liu
Jinhong Zhang
Haoran Li
Jin Zhang
Yuanyu Wang
Wei Zhou
    AAML
ArXivPDFHTML

Papers citing "AFLOW: Developing Adversarial Examples under Extremely Noise-limited Settings"

6 / 6 papers shown
Title
STBA: Towards Evaluating the Robustness of DNNs for Query-Limited
  Black-box Scenario
STBA: Towards Evaluating the Robustness of DNNs for Query-Limited Black-box Scenario
Renyang Liu
Kwok-Yan Lam
Wei Zhou
Sixing Wu
Jun Zhao
Dongting Hu
Mingming Gong
AAML
28
0
0
30 Mar 2024
SSTA: Salient Spatially Transformed Attack
SSTA: Salient Spatially Transformed Attack
Renyang Liu
Wei Zhou
Sixing Wu
Jun Zhao
Kwok-Yan Lam
AAML
26
0
0
12 Dec 2023
RobustBench: a standardized adversarial robustness benchmark
RobustBench: a standardized adversarial robustness benchmark
Francesco Croce
Maksym Andriushchenko
Vikash Sehwag
Edoardo Debenedetti
Nicolas Flammarion
M. Chiang
Prateek Mittal
Matthias Hein
VLM
234
677
0
19 Oct 2020
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
Deep Reinforcement Learning for Autonomous Driving: A Survey
Deep Reinforcement Learning for Autonomous Driving: A Survey
B. R. Kiran
Ibrahim Sobh
V. Talpaert
Patrick Mannion
A. A. Sallab
S. Yogamani
P. Pérez
165
1,632
0
02 Feb 2020
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,837
0
08 Jul 2016
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