[Guided Diffusion Models for Adversarial Purification](arxiv.org/abs/2205.0746) [Guided Diffusion Model for Adversarial Purification](http://arxiv.org/abs/2106.09667)比较有意思的是,两篇文章都是用diffusion来做对抗样本防御(去噪)的,论文标题就差了一个字(笑),意外碰上了,让我们来看看上交和英伟达的论文...
However, their performance currently falls behind adversarial training methods. In this work, we propose DiffPure that uses diffusion models for adversarial purification: Given an adversarial example, we first diffuse it with a small amount of noise following a forward diffusion process, and then ...
Data Purification Diffusion Models for Adversarial Purification Adversarial purification with score-based generative models Threat Model-Agnostic Adversarial Defense using Diffusion Models Guided Diffusion Model for Adversarial Purification Guided Diffusion Model for Adversarial Purification from Random Noise PointDP...
Diffusion models for adversarial purification. In International Conference on Ma- chine Learning, pages 16805–16827. PMLR, 2022. 1, 2, 3, 6, 7, 8 [22] Tianyu Pang, Min Lin, Xiao Yang, Jun Zhu, and Shuicheng Yan. Robustness and accuracy could...
mkdir -p clf_models/run/logs/cifar10 For starting the purification process, execute python main.py --config default.yml Example ImageNet Download thepretrained weightsand copy them to the foldermodels. For example, we provide the example configuration fileconfigs/ImageNet_PGD.ymlin the repository...
002 (2023-11-29) Visual Anagrams Generating Multi-View Optical Illusions with Diffusion Models https://arxiv.org/pdf/2311.17919.pdf 003 (2023-11-29) SODA Bottleneck Diffusion Models for Representation Learning https://arxiv.org/pdf/2311.17901.pdf ...
In this work, we propose DiffPure that uses diffusion models for adversarial purification: Given an adversarial example, we first diffuse it with a small amount of noise following a forward diffusion process, and then recover the clean image through a reverse generative process. To evaluate our ...
Purification spaceDeep neural networks (DNNs) have been demonstrated to be vulnerable to adversarial samples and many powerful defense methods have been proposed to enhance the adversarial robustness of DNNs. However, these defenses often require adding regularization terms to the loss function or ...
source: DensePure: Understanding Diffusion Models Towards Adversarial Robustness 而我们直接去maximize ...
Bob alters the image to remove the watermark with deep learning techniques, like methods used for adversarial purification [78, 94] or neural auto- encoders [1, 48]. Note that this kind of attacks has not been explored in the image watermarking literature to ...