English(EN) Unleashing the Representational Power of Fourier Shapes for Attacking Infrared Object Detection

傅里叶形状攻击红外目标检测系统

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-18 03:51

研究人员开发了一种新颖的方法，通过操纵几何形状的热特征来攻击红外目标检测系统。他们的方法使用可学习的傅里叶系数来定义形状边界，然后使用环绕数定理将其映射到像素掩码。这使得能够进行有效的、基于梯度的优化，以创建能够规避检测的形状，在物理实验中，在25米以上的距离上实现了超过88%的攻击成功率。 AI

影响这项研究揭示了红外目标检测的一个新漏洞，可能影响自动驾驶和监控系统。

排序理由该集群包含一篇详细介绍攻击红外目标检测系统新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Fan Li · 2026-05-18 03:51

释放傅里叶形状的表征能力以攻击红外目标检测

Infrared object detection is crucial for perception in autonomous driving and surveillance but remains vulnerable to physical adversarial attacks. Unlike in the RGB domain, where attacks rely on color texture, infrared attacks must manipulate thermal signatures, making the geomet…