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Benchmarks
Image Classification on CIFAR-10 AdvP
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70.81
Accuracy
defensive patch generation framework
17.7596
31.5323
45.305
59.0777
Apr 13, 2022
Accuracy
Updated 3mo ago
Evaluation Results
Method
Method
Links
Accuracy
defensive patch generation framework
Model=RNet, Setting=Fo...
2022.04
70.81
defensive patch generation framework
Model=SNet, Setting=Fo...
2022.04
67.67
defensive patch generation framework
Model=MNet, Setting=Fo...
2022.04
64.82
Trans
Model=RNet, Setting=Fo...
2022.04
59.52
Vanilla
Model=RNet, Setting=Fo...
2022.04
53.51
Trans
Model=MNet, Setting=Fo...
2022.04
53.17
Trans
Model=SNet, Setting=Fo...
2022.04
52.91
UnAdv
Model=RNet, Setting=Fo...
2022.04
49.39
Vanilla
Model=MNet, Setting=Fo...
2022.04
46.76
Vanilla
Model=SNet, Setting=Fo...
2022.04
43.76
defensive patch generation framework
Model=VGG, Setting=Fou...
2022.04
40.83
Trans
Model=VGG, Setting=Fou...
2022.04
33.18
UnAdv
Model=SNet, Setting=Fo...
2022.04
31.71
UnAdv
Model=VGG, Setting=Fou...
2022.04
29.24
Vanilla
Model=VGG, Setting=Fou...
2022.04
19.99
UnAdv
Model=MNet, Setting=Fo...
2022.04
19.8
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