mlsanityData to 14 Oct 2026

Infrared Invisible Clothing:Hiding from Infrared Detectors at Multiple Angles in Real World

arXiv 2205.05909 ↗First posted 12 May 2022cs.CV cs.AIcited by 42

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Abstract (arXiv)

Thermal infrared imaging is widely used in body temperature measurement, security monitoring, and so on, but its safety research attracted attention only in recent years. We proposed the infrared adversarial clothing, which could fool infrared pedestrian detectors at different angles. We simulated the process from cloth to clothing in the digital world and then designed the adversarial "QR code" pattern. The core of our method is to design a basic pattern that can be expanded periodically, and make the pattern after random cropping and deformation still have an adversarial effect, then we can process the flat cloth with an adversarial pattern into any 3D clothes. The results showed that the optimized "QR code" pattern lowered the Average Precision (AP) of YOLOv3 by 87.7%, while the random "QR code" pattern and blank pattern lowered the AP of YOLOv3 by 57.9% and 30.1%, respectively, in the digital world. We then manufactured an adversarial shirt with a new material: aerogel. Physical-world experiments showed that the adversarial "QR code" pattern clothing lowered the AP of YOLOv3 by 64.6%, while the random "QR code" pattern clothing and fully heat-insulated clothing lowered the AP of YOLOv3 by 28.3% and 22.8%, respectively. We used the model ensemble technique to improve the attack transferability to unseen models.

Key facts. Cited by 42 papers in the map (data through 14 Oct 2026). Builds on 26 of its 40 references that are in the map. First posted on arXiv 12 May 2022.

Builds on

26 of 40 references.

References · 26

  1. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  2. 2014Explaining and Harnessing Adversarial Examplescited by 7,364
  3. 2017Mask R-CNNcited by 7,277
  4. 2017Towards Deep Learning Models Resistant to Adversarial Attackscited by 6,415
  5. 2013Intriguing properties of neural networkscited by 5,155
  6. 2015SSD: Single Shot MultiBox Detectorcited by 3,130
  7. 2016Towards Evaluating the Robustness of Neural Networkscited by 2,998
  8. 2016Categorical Reparameterization with Gumbel-Softmaxcited by 2,739
  9. 2018YOLOv3: An Incremental Improvementcited by 2,659
  10. 2016YOLO9000: Better, Faster, Strongercited by 1,431
  11. 2015DeepFool: a simple and accurate method to fool deep neural networkscited by 1,318
  12. 2017Cascade R-CNN: Delving into High Quality Object Detectioncited by 1,276
14 more
  1. 2016Adversarial Machine Learning at Scalecited by 936
  2. 2017ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Modelscited by 666
  3. 2016Delving into Transferable Adversarial Examples and Black-box Attackscited by 536
  4. 2017Countering Adversarial Images using Input Transformationscited by 520
  5. 2017Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networkscited by 486
  6. 2019Fooling automated surveillance cameras: adversarial patches to attack person detectioncited by 268
  7. 2018Generating Adversarial Examples with Adversarial Networkscited by 258
  8. 2020Physically Realizable Adversarial Examples for LiDAR Object Detectioncited by 137
  9. 2021Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attackscited by 101
  10. 2019Universal Physical Camouflage Attacks on Object Detectorscited by 91
  11. 2021Adversarial Laser Beam: Effective Physical-World Attack to DNNs in a Blinkcited by 75
  12. 2019AdvFaces: Adversarial Face Synthesiscited by 60
  13. 2021Fooling thermal infrared pedestrian detectors in real world using small bulbscited by 51
  14. 2020Can 3D Adversarial Logos Cloak Humans?cited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 4; 2023: 16; 2024: 7; 2025: 5; 2026: 10.

42 papers.

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  1. 2022Physical Adversarial Attack meets Computer Vision: A Decade Surveycited by 67
  2. 2023X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detectioncited by 59
  3. 2023Physically Realizable Natural-Looking Clothing Textures Evade Person Detectors via 3D Modelingcited by 41
  4. 2023Physically Adversarial Infrared Patches with Learnable Shapes and Locationscited by 39
  5. 2022HOTCOLD Block: Fooling Thermal Infrared Detectors with a Novel Wearable Designcited by 27
  6. 2023Unified Adversarial Patch for Cross-modal Attacks in the Physical Worldcited by 27
  7. 2022A Survey on Physical Adversarial Attack in Computer Visioncited by 25
  8. 2024SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environmentscited by 22
  9. 2023Unified Adversarial Patch for Visible-Infrared Cross-modal Attacks in the Physical Worldcited by 21
  10. 2023Physical Adversarial Attacks For Camera-based Smart Systems: Current Trends, Categorization, Applications, Research Challenges, and Future Outlookcited by 20
  11. 2023Physical Adversarial Attacks for Surveillance: A Surveycited by 15
  12. 2022Visual Adversarial Attacks and Defenses in the Physical World: A Surveycited by 11
30 more
  1. 2023Adversarial Infrared Blocks: A Multi-view Black-box Attack to Thermal Infrared Detectors in Physical Worldcited by 11
  2. 2023Adversarial Examples in the Physical World: A Surveycited by 10
  3. 2023Adversarial Infrared Curves: An Attack on Infrared Pedestrian Detectors in the Physical Worldcited by 10
  4. 2024Infrared Adversarial Car Stickerscited by 8
  5. 2023CBA: Contextual Background Attack against Optical Aerial Detection in the Physical Worldcited by 7
  6. 2025CDUPatch: Color-Driven Universal Adversarial Patch Attack for Dual-Modal Visible-Infrared Detectorscited by 6
  7. 2023A Comprehensive Study on the Robustness of Image Classification and Object Detection in Remote Sensing: Surveying and Benchmarkingcited by 5
  8. 2024Real-world Adversarial Defense against Patch Attacks based on Diffusion Modelcited by 5
  9. 2025Adversarial Attacks on Event-Based Pedestrian Detectors: A Physical Approachcited by 5
  10. 2023Defending Against Physical Adversarial Patch Attacks on Infrared Human Detectioncited by 4
  11. 2023Two-stage optimized unified adversarial patch for attacking visible-infrared cross-modal detectors in the physical worldcited by 4
  12. 2024Physics-Based Adversarial Attack on Near-Infrared Human Detector for Nighttime Surveillance Camera Systemscited by 3
  13. 2023Eigenpatches -- Adversarial Patches from Principal Componentscited by 1
  14. 2024Multi-View Black-Box Physical Attacks on Infrared Pedestrian Detectors Using Adversarial Infrared Gridcited by 1
  15. 2025A Survey of Adversarial Defenses in Vision-based Systems: Categorization, Methods and Challengescited by 1
  16. 2025Learning Fourier shapes to probe the geometric world of deep neural networkscited by 1
  17. 2026Knowledge-Guided Adversarial Training for Infrared Object Detection via Thermal Radiation Modelingcited by 1
  18. 2026Physical Adversarial Clothing Evades Visible-Thermal Detectors via Non-Overlapping RGB-T Patterncited by 1
  19. 2023Neural Lithography: Close the Design-to-Manufacturing Gap in Computational Optics with a 'Real2Sim' Learned Photolithography Simulatorcited by 0
  20. 2024Adversarial Infrared Geometry: Using Geometry to Perform Adversarial Attack against Infrared Pedestrian Detectorscited by 0
  21. 2024PADetBench: Towards Benchmarking Physical Attacks against Object Detectioncited by 0
  22. 2025Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical Worldcited by 0
  23. 2026Robust Vision Systems for Connected and Autonomous Vehicles: Security Challenges and Attack Vectorscited by 0
  24. 2026Thermal Topology Collapse: Universal Physical Patch Attacks on Infrared Vision Systemscited by 0
  25. 2026Revealing Physical-World Semantic Vulnerabilities: Universal Adversarial Patch for Infrared Vision-Language Modelscited by 0
  26. 2026Physical Adversarial Attacks on AI Surveillance Systems:Detection, Tracking, and Visible--Infrared Evasioncited by 0
  27. 2026Unleashing the Representational Power of Fourier Shapes for Attacking Infrared Object Detectioncited by 0
  28. 2026AirflowAttack: Thermal-Airflow Adversarial Perturbations against Infrared Remote-Sensing Vision-Language Modelscited by 0
  29. 2026Physical Adversarial Examples for Person Detectors in Thermal Images Based on 3D Modelingcited by 0
  30. 2026Stealthy in Semantics, Antagonistic in Space: Attacking Visible-Infrared Object Detectors via Object-Level Misalignmentcited by 0