推荐理事:林宙辰 原文标题:Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal 原文链接:https://openreview.net/pdf?id=CwQCeJnteii 原文代码链接:https://github.com/shiyuchengTJU/PAR ◆...
针对ViT做的hard-label attack,考虑ViT是基于划分图像patch进行识别,所以将图像划分,根据模型对每个patch的敏感度进行噪声消除,相比全图或者局部噪声消减,效率更高。算法名为Patch-wise Adversarial Removal (PAR)。 1 Introduction 随着ViT在CV领域的火热,对抗攻击也被应用在ViT上评估鲁棒性。现有的针对ViT的攻击主要是白...
In targeted attack case, we extend our Patch-wise iterative method to Patch-wise++ iterative method. More details can be found from here. Implementation Tensorflow 1.14, gast 0.2.2, Python3.7 Download the models Normlly trained models (DenseNet can be found in here) Ensemble adversarial trained...
In general, using patch-wise samples helps to extract the spatial relationship between pixels and local contextual information. However, the presence of background or other category information in an image patch that is inconsistent with the central target category has a negative effect on ...
In other words, the image patch Iw(k, l) is arranged into a vector Iw, taking all elements from matrix Iw in a row-wise fashion. The vectors Iw are normalised to zero mean, to avoid the possible bias of the local greyscale levels. Assume that we have a population of patches Iw, ...
SAR-to-optical image translation using supervised cycle-consistent adversarial networks IEEE Access, 7 (2019), pp. 129136-129149 CrossrefView in ScopusGoogle Scholar Winder and Brown, 2007 Winder S.A., Brown M. Learning local image descriptors Proceedings of the IEEE Conference on Computer Vision...
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underwater image enhancement; cycle-consistent generative adversarial networks; multi-scale adaptive fusion attention; learned perceptual image patch similarity1. Introduction Underwater imaging plays a crucial role across various fields, including marine ecology research, underwater archaeology, underwater ...