mlsanityData to 7 Oct 2026

Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors

arXiv 1910.14667 ↗First posted 31 Oct 2019cs.CV cs.CR cs.LGcited by 155

Not on the map. Why?

Abstract (arXiv)

We present a systematic study of adversarial attacks on state-of-the-art object detection frameworks. Using standard detection datasets, we train patterns that suppress the objectness scores produced by a range of commonly used detectors, and ensembles of detectors. Through extensive experiments, we benchmark the effectiveness of adversarially trained patches under both white-box and black-box settings, and quantify transferability of attacks between datasets, object classes, and detector models. Finally, we present a detailed study of physical world attacks using printed posters and wearable clothes, and rigorously quantify the performance of such attacks with different metrics.

Key facts. Cited by 155 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Oct 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 27; 2022: 40; 2023: 41; 2024: 23; 2025: 14; 2026: 10.

155 papers.

Sort:

By area:

  1. 2023Baseline Defenses for Adversarial Attacks Against Aligned Language Modelscited by 608
  2. 2021Advances in adversarial attacks and defenses in computer vision: A surveycited by 127
  3. 2022Adversarial Texture for Fooling Person Detectors in the Physical Worldcited by 96
  4. 2021LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognitioncited by 92
  5. 2021Adversarial Sticker: A Stealthy Attack Method in the Physical Worldcited by 92
  6. 2021Improving Transferability of Adversarial Patches on Face Recognition with Generative Modelscited by 80
  7. 2021FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attackcited by 74
  8. 2021Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detectioncited by 67
  9. 2022Physical Adversarial Attack meets Computer Vision: A Decade Surveycited by 66
  10. 2023Black Box Adversarial Prompting for Foundation Modelscited by 62
  11. 2022T-SEA: Transfer-based Self-Ensemble Attack on Object Detectioncited by 59
  12. 2021Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch Attackscited by 55
38 more
  1. 2021Exploring Adversarial Robustness of Multi-Sensor Perception Systems in Self Drivingcited by 45
  2. 2021Certified Patch Robustness via Smoothed Vision Transformerscited by 44
  3. 2022Towards Practical Certifiable Patch Defense with Vision Transformercited by 44
  4. 2023Physically Realizable Natural-Looking Clothing Textures Evade Person Detectors via 3D Modelingcited by 41
  5. 2023DAP: A Dynamic Adversarial Patch for Evading Person Detectorscited by 40
  6. 2023Does Physical Adversarial Example Really Matter to Autonomous Driving? Towards System-Level Effect of Adversarial Object Evasion Attackcited by 37
  7. 2021Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safetycited by 35
  8. 2021Physical Adversarial Attacks on an Aerial Imagery Object Detectorcited by 35
  9. 2024PAD: Patch-Agnostic Defense against Adversarial Patch Attackscited by 31
  10. 2022On the Real-World Adversarial Robustness of Real-Time Semantic Segmentation Models for Autonomous Drivingcited by 30
  11. 2021DetectorGuard: Provably Securing Object Detectors against Localized Patch Hiding Attackscited by 28
  12. 2022Phantom Sponges: Exploiting Non-Maximum Suppression to Attack Deep Object Detectorscited by 28
  13. 2022Gradient Methods Provably Converge to Non-Robust Networkscited by 27
  14. 2022HOTCOLD Block: Fooling Thermal Infrared Detectors with a Novel Wearable Designcited by 27
  15. 2022A Survey on Physical Adversarial Attack in Computer Visioncited by 24
  16. 2023The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networkscited by 23
  17. 2022ObjectSeeker: Certifiably Robust Object Detection against Patch Hiding Attacks via Patch-agnostic Maskingcited by 22
  18. 2022SoK: On the Semantic AI Security in Autonomous Drivingcited by 22
  19. 2022Benchmarking Adversarial Patch Against Aerial Detectioncited by 21
  20. 2022Dangerous Cloaking: Natural Trigger based Backdoor Attacks on Object Detectors in the Physical Worldcited by 20
  21. 2023Physical Adversarial Attacks For Camera-based Smart Systems: Current Trends, Categorization, Applications, Research Challenges, and Future Outlookcited by 20
  22. 2021Adversarial Mask: Real-World Universal Adversarial Attack on Face Recognition Modelcited by 19
  23. 2023Attacks in Adversarial Machine Learning: A Systematic Survey from the Life-cycle Perspectivecited by 19
  24. 2023Query-Efficient Decision-based Black-Box Patch Attackcited by 19
  25. 2021Context-Aware Transfer Attacks for Object Detectioncited by 18
  26. 2022Zero-Query Transfer Attacks on Context-Aware Object Detectorscited by 17
  27. 2022REAP: A Large-Scale Realistic Adversarial Patch Benchmarkcited by 17
  28. 2023Adversarial Training of Self-supervised Monocular Depth Estimation against Physical-World Attackscited by 17
  29. 2021Shift Invariance Can Reduce Adversarial Robustnesscited by 16
  30. 2021SoK: Anti-Facial Recognition Technologycited by 16
  31. 2023Ensemble-based Blackbox Attacks on Dense Predictioncited by 16
  32. 2021ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layerscited by 15
  33. 2023FACE-AUDITOR: Data Auditing in Facial Recognition Systemscited by 15
  34. 2023Physical Adversarial Attacks for Surveillance: A Surveycited by 15
  35. 2021Differentially Private Imaging via Latent Space Manipulationcited by 13
  36. 2021DeepBlur: A Simple and Effective Method for Natural Image Obfuscationcited by 13
  37. 2022Feasibility of Inconspicuous GAN-generated Adversarial Patches against Object Detectioncited by 13
  38. 2022Blackbox Attacks via Surrogate Ensemble Searchcited by 13

50 most cited of 155 All 155 (JSON)