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Boosting the Transferability of Adversarial Examples via Local Mixup and
  Adaptive Step Size

Boosting the Transferability of Adversarial Examples via Local Mixup and Adaptive Step Size

24 January 2024
Junlin Liu
Xinchen Lyu
    AAML
ArXivPDFHTML

Papers citing "Boosting the Transferability of Adversarial Examples via Local Mixup and Adaptive Step Size"

4 / 4 papers shown
Title
Beyond ImageNet Attack: Towards Crafting Adversarial Examples for
  Black-box Domains
Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains
Qilong Zhang
Xiaodan Li
YueFeng Chen
Jingkuan Song
Lianli Gao
Yuan He
Hui Xue
AAML
62
64
0
27 Jan 2022
Aggregated Residual Transformations for Deep Neural Networks
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Z. Tu
Kaiming He
261
10,196
0
16 Nov 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
L. V. D. van der Maaten
Kilian Q. Weinberger
PINN
3DV
247
36,237
0
25 Aug 2016
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
282
39,170
0
01 Sep 2014
1