# Thermally Activated Dual-Modal Adversarial Clothing against AI Surveillance Systems

arXiv: https://arxiv.org/abs/2511.09829 · HTML: https://mlsanity.com/paper/2511.09829/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 33 of its 65 references that are in the map.
- First posted on arXiv 13 Nov 2025.

## Builds on (most cited first, 30 of 33)

- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://mlsanity.com/paper/1506.01497/) (2015)
- [End-to-End Object Detection with Transformers](https://mlsanity.com/paper/2005.12872/) (2020)
- [YOLOv3: An Incremental Improvement](https://mlsanity.com/paper/1804.02767/) (2018)
- [Adversarial Patch](https://mlsanity.com/paper/1712.09665/) (2017)
- [Fooling automated surveillance cameras: adversarial patches to attack person detection](https://mlsanity.com/paper/1904.08653/) (2019)
- [LLVIP: A Visible-infrared Paired Dataset for Low-light Vision](https://mlsanity.com/paper/2108.10831/) (2021)
- [Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors](https://mlsanity.com/paper/1910.14667/) (2019)
- [DPatch: An Adversarial Patch Attack on Object Detectors](https://mlsanity.com/paper/1806.02299/) (2018)
- [Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World](https://mlsanity.com/paper/2103.01050/) (2021)
- [Adversarial Texture for Fooling Person Detectors in the Physical World](https://mlsanity.com/paper/2203.03373/) (2022)
- [Adversarial Sticker: A Stealthy Attack Method in the Physical World](https://mlsanity.com/paper/2104.06728/) (2021)
- [Artificial Intelligence Index Report 2025](https://mlsanity.com/paper/2504.07139/) (2025)
- [T-SEA: Transfer-based Self-Ensemble Attack on Object Detection](https://mlsanity.com/paper/2211.09773/) (2022)
- [Exploring Frequency Adversarial Attacks for Face Forgery Detection](https://mlsanity.com/paper/2203.15674/) (2022)
- [Physically Realizable Natural-Looking Clothing Textures Evade Person Detectors via 3D Modeling](https://mlsanity.com/paper/2307.01778/) (2023)
- [Physically Adversarial Infrared Patches with Learnable Shapes and Locations](https://mlsanity.com/paper/2303.13868/) (2023)
- [Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous Driving](https://mlsanity.com/paper/2403.17301/) (2024)
- [Unified Adversarial Patch for Cross-modal Attacks in the Physical World](https://mlsanity.com/paper/2307.07859/) (2023)
- [IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object Tracking](https://mlsanity.com/paper/2103.14938/) (2021)
- [Towards Transferable Targeted 3D Adversarial Attack in the Physical World](https://mlsanity.com/paper/2312.09558/) (2023)
- [Eva-VLA: Evaluating Vision-Language-Action Models' Robustness Under Real-World Physical Variations](https://mlsanity.com/paper/2509.18953/) (2025)
- [REAP: A Large-Scale Realistic Adversarial Patch Benchmark](https://mlsanity.com/paper/2212.05680/) (2022)
- [Adversarial Infrared Blocks: A Multi-view Black-box Attack to Thermal Infrared Detectors in Physical World](https://mlsanity.com/paper/2304.10712/) (2023)
- [When Lighting Deceives: Exposing Vision-Language Models' Illumination Vulnerability Through Illumination Transformation Attack](https://mlsanity.com/paper/2503.06903/) (2025)
- [Adversarial Infrared Curves: An Attack on Infrared Pedestrian Detectors in the Physical World](https://mlsanity.com/paper/2312.14217/) (2023)
- [Understanding Policy and Technical Aspects of AI-Enabled Smart Video Surveillance to Address Public Safety](https://mlsanity.com/paper/2302.04310/) (2023)
- [Infrared Adversarial Car Stickers](https://mlsanity.com/paper/2405.09924/) (2024)
- [CDUPatch: Color-Driven Universal Adversarial Patch Attack for Dual-Modal Visible-Infrared Detectors](https://mlsanity.com/paper/2504.10888/) (2025)
- [Two-stage optimized unified adversarial patch for attacking visible-infrared cross-modal detectors in the physical world](https://mlsanity.com/paper/2312.01789/) (2023)

## Built on by (most cited first, 2 of 2)

- [Physical Adversarial Attacks on AI Surveillance Systems:Detection, Tracking, and Visible--Infrared Evasion](https://mlsanity.com/paper/2604.06865/) (2026)
- [AdvTiles: Physical Adversarial Camouflage Clothing against Person Detectors via Learnable Tiles](https://mlsanity.com/paper/2608.06801/) (2026)

## Abstract (arXiv)

Adversarial patches have emerged as a popular privacy-preserving approach for resisting AI-driven surveillance systems. However, their conspicuous appearance makes them difficult to deploy in real-world scenarios. In this paper, we propose a thermally activated adversarial wearable designed to ensure adaptability and effectiveness in complex real-world environments. The system integrates thermochromic dyes with flexible heating units to induce visually dynamic adversarial patterns on clothing surfaces. In its default state, the clothing appears as an ordinary black T-shirt. Upon heating via an embedded thermal unit, hidden adversarial patterns on the fabric are activated, allowing the wearer to effectively evade detection across both visible and infrared modalities. Physical experiments demonstrate that the adversarial wearable achieves rapid texture activation within 50 seconds and maintains an adversarial success rate above 80% across diverse real-world surveillance environments. This work demonstrates a new pathway toward physically grounded, user-controllable anti-AI systems, highlighting the growing importance of proactive adversarial techniques for privacy protection in the age of ubiquitous AI surveillance.