Hiding in Plain Sight: An Effective Physical Adversarial Patch Attack against Visual-Infrared Fused Face Detection

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arXiv:2607.23292v1 Announce Type: new Abstract: Deep learning-based visual-infrared fused face detection models are increasingly deployed across a wide range of applications, yet they remain susceptible to adversarial patch attacks. Most prior attacks target either the visual or the infrared image alone in the digital domain, which renders them ineffective against fused models in the physical world. Moreover, many of these methods are readily noticeable, as their patch patterns deviate substant