Comments (4)
HanxunH
commented on July 2, 2024
Yes, the noise should be added first. This could improve the protection performance. Keep me updated if you notice any difference in the results.
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Nonbiuld
commented on July 2, 2024
训练生成噪声的代码似乎也有一点小问题，images[i] = images[i] + sample_noise，比如这里这个image加了sample_noise之后，是不是需要再clamp到(0,1)会更加合理一点，如果更改后效果有所提升我会告诉你的。
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HanxunH
commented on July 2, 2024
Good catch, thanks!
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pzs19
commented on July 2, 2024
@Nonbiuld 老哥，我也注意到这个问题了，请问更改之后效果如何？
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Related Issues (19)
- Why use custom models? Cannot reproduce with torchvision model HOT 3
- KeyError: 'train_subset' HOT 4
- A problem when training model on ImageNetMini HOT 1
- Mismatch of the training data augmentation between QuickStart.ipynb and main.py HOT 1
- Two problems in training code of ImageNetMini HOT 1
- A problem with bi-level optimization in the article HOT 6
- Several questions about this article HOT 4
- Some questions about training Inception-ResNet HOT 11
- Questions about training casia-webface dataset HOT 1
- Some questions about face recognition poisoning attack HOT 5
- A problem about noise generating. HOT 1
- keyerror报错 HOT 1
- Generating examples using CelebA HOT 1
- Can you share your experience with fast-autoaugment HOT 2
- bugs when generating sample wise perturbation HOT 1
- About the plot setting in the paper HOT 2
- About visualizing the results according to log file HOT 1
- 应用场景与设定变更时，该如何保证不可学效果 HOT 4
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