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New adversarial clothing fools thermal person detectors using 3D modeling

By PulseAugur Editorial · [1 sources] ·

Researchers have developed physical adversarial clothing designed to fool thermal person detectors, a technology used in applications like autonomous driving and medical diagnostics. The clothing utilizes 3D modeling to simulate multi-angle scenarios and is constructed with aerogel patches that appear as black squares in thermal images. This method achieved an 80.11% attack success rate indoors and 76.85% outdoors against the YOLOv9 detector, significantly outperforming randomly placed patches. AI

IMPACT This research highlights potential security vulnerabilities in AI systems used for thermal detection, impacting safety-critical applications like autonomous driving.

RANK_REASON Academic paper detailing a new method for creating adversarial examples. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New adversarial clothing fools thermal person detectors using 3D modeling

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20 / 100
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Academic paper detailing a new method for creating adversarial examples. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Xiaopei Zhu, Siyuan Huang, Zhanhao Hu, Jianmin Li, Jun Zhu, Xiaolin Hu ·

    Physical Adversarial Examples for Person Detectors in Thermal Images Based on 3D Modeling

    arXiv:2608.30839v1 Announce Type: new Abstract: Thermal Infrared detection is widely used in autonomous driving, medical AI, etc., but its security has only attracted attention recently. We propose infrared adversarial clothing designed to evade thermal person detectors in real-w…

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