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Improving Transferable Targeted Adversarial Attack via Normalized Logit
  Calibration and Truncated Feature Mixing

Improving Transferable Targeted Adversarial Attack via Normalized Logit Calibration and Truncated Feature Mixing

10 May 2024
Juanjuan Weng
Zhiming Luo
Shaozi Li
    AAML
ArXivPDFHTML

Papers citing "Improving Transferable Targeted Adversarial Attack via Normalized Logit Calibration and Truncated Feature Mixing"

4 / 4 papers shown
Title
Logit Margin Matters: Improving Transferable Targeted Adversarial Attack
  by Logit Calibration
Logit Margin Matters: Improving Transferable Targeted Adversarial Attack by Logit Calibration
Juanjuan Weng
Zhiming Luo
Zhun Zhong
Shaozi Li
N. Sebe
AAML
34
16
0
07 Mar 2023
RankFeat: Rank-1 Feature Removal for Out-of-distribution Detection
RankFeat: Rank-1 Feature Removal for Out-of-distribution Detection
Yue Song
N. Sebe
Wei Wang
OODD
58
52
0
18 Sep 2022
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,835
0
08 Jul 2016
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
294
75,834
0
18 May 2015
1