QwQ2000 / Activation-Attack-Pytorch

CVPR 2019 Paper——Feature Space Perturbations Yield More Transferable Adversarial Examples re-implementation.
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adversarial computer-vision deep-learning machine-learning pytorch

Activation-Attack-Pytorch

Apply targeted attacks on black box ViT with the activation attack method. The white box model is ResNet-18.

Based on CVPR 2019 Paper Feature Space Perturbations Yield More Transferable Adversarial Examples.

My additional expreriment proves that the transferablitiy is low between heterogeneous deep models.

All the models are finetuned on CIFAR-10 with the Adam optimizer with lr = 1e-5.

Pretrained models

Model Name CIFAR-10 Test Accuracy ImageNet-1K Pretrain
ResNet-18 0.9435 Yes
DenseNet-121 0.9571 Yes
ViT-B/16 0.9838 Yes

Results

Model Error uTr tSuc tTr
ResNet-18 96.39 / 75.48 /
DenseNet-121 80.16 82.27 9.39 10.65
ViT 22.33 22.78 2.5 4.2