Recently, adversarial-based method [6] is proposed to further improve distillation performance. It consists of an adversarial phase consisting of GANs to generate the divergent examples and a co-distillation phase consisting of multiple classifiers to learn the divergent examples. Show abstract Certainty...
Adversarial examples in the physical world (CVPR 2016):提出BIM方法,即优化时用若干小步代替一大步,进一步提出non-targeted版本,Iterative Least-likely Class Method (ILCM). 作者单位: Google. Jacobian-based Saliency Map Attack (JSMA): The Limitations of Deep Learning in Adversarial Settings (EURO S&P):...
相反,我们关注于攻击RPN(基于提议的模型的一个常见组件),以在不了解其架构细节的情况下普遍降低其性能。 3.Method 该方法通过在输入图像中加入最小的对抗噪声,有效地干扰区域建议网络(RPN)的预测,从而攻击了基于深度建议的目标检测和实例分割算法。给定一个输入图像和一个预先训练的RPN,我们设计了一个特定的目标函数...
Goodfellow等人提出来快速梯度符号方法(FGSM--- Fast Gradient Sign Method)攻击, 利用cost函数反推出梯度, 然后对样本进行扰动. **I. J. Goodfellow, J. Shlens, and C. Szegedy, “Explaining and Harnessing Adversarial Examples,” arXiv preprint arXiv:1412.6572, 2014. ** 虽然, 这些方法依赖于近似, 但...
In this paper, we introduced GAIL-VR, a simple method to improve the convergence ability of GAIL, especially in complex environments. The principle behind GAIL-VR is to alter the role of discriminator from competitor to teacher by optimizing the discriminator to maximize the variance of the advan...
In[227], adversarial examples were generated and fed back to the training set. This is a type of regularization via data generation. However, in[118], it is argued that in the case of music data the method did not really improve performance. ...
Ledig等[1]提出SRGAN模型,使用感知损失和对抗损失来支持位于自然图像流形的输出。Sajjadi等[16]开发了类似的方法并进一步探索了局部纹理匹配损失。基于这些工作,Wang等[17]提出空间特征变换来有效地将语义先验合并到图像中并改进恢复的纹理。 在整个文献中,通常通过与GAN[15]的对抗训练来获得写实主义照片。最近有很多...
2022-TPAMI【AdvSticker】Adversarial Sticker: A Stealthy Attack Method in the Physical Worldpaper|[code](https://github.com/jinyugy21/Adv-StickersRHDE)Black-boxFace RecognitionBendingStickerTargeted NontargetedStatic3D 2022-TPAMI【SOPP】Simultaneously Optimizing Perturbations and Positions for Black-box Adve...
Proposed Debiasing Method 本文的方法主要针对减轻lead bias的效果,确保摘要器更注重句子语义内容来做摘要。如下图所示,本文的方法分成两个元件,一个是用于摘要,一个用于句子位置预测。 摘要部分 根据前人的工作,本文把抽取式摘要定义成序列标注任务,对于文本中的每个句子,都进行一个0-1的打分,最后选择分数较高的一些...
作者将这种攻击称为单步目标类别方法(One-step Target Class Method, OTCM)。 [84] 发现,由于梯度掩蔽(gradient masking),经过对抗训练的FGSM对白盒攻击比对黑盒攻击更鲁棒。他们提出了一种新的攻击方法,RAND-FGSM,在更新对抗样本时加入随机性来击败对抗训练: ...