Adversarial Patch Attacks

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Overview

Adversarial patch attacks study how small, localized patterns can make vision systems misclassify objects, miss detections, or produce attacker-chosen outputs. Researchers optimize patches with gradient-based or black-box methods, often making them universal or targeted and testing robustness to changes in scale, viewpoint, lighting, and printing. Applications range from object detection in autonomous driving and infrared imaging to vision-language models and robots, where visual errors can propagate into actions. Defenses include patch detection and masking, spectral methods, adversarial training, and certification, but a central tension is whether digital robustness transfers to physical, changing scenes and prevents failures across an entire system.

Latest papers

CardsList

49 papers4 papers in the last four weeks, down 33% on the four weeks before. 0.0% of all new papers.

  1. STROKE: Simple Sparse Structural Occlusions for Black-Box Adversarial Attacks

    Oct 23, 2026Ankit Gupta, Akshat Pandya, Paul Lin +2Black-Box Adversarial AttacksAdversarial Patch Attacks

    Department of Computer Science & Engineering Michigan State University · Coco Robotics · Program in Evolution, Ecology, & Behavior Michigan State University +2

  2. MRCert: Towards Post-deployment Patch Robustness Certification for Adversarially Patched Samples via Type-specific Masking

    Oct 7, 2026Qilin Zhou, Zhengyuan Wei, Haipeng Wang +3Adversarial RobustnessCertified Robustness

    City University of Hong Kong · The Education University of Hong Kong

  3. TAPDreamer: Transferable Adversarial Patches for World Action Models

    Oct 5, 2026Xuanyu Lu, Fengqing Jiang, Kaiyuan Zheng +8Adversarial Patch AttacksAdversarial Attacks

    University of Washington · University of Georgia · Western Washington University +2

  4. Detect and Suppress: A Mechanistic Defense against Adversarial Patches in VLA Models

    Oct 2, 2026Yukiya Horiba, Koshiro Aoki, Shunsuke Yasuki +2Robustness of VLA ModelsAdversarial Patch Attacks

    Keio University · Waseda University · The University of Tokyo

  5. Printability-Constrained Adversarial Decals for Near-Nadir Aerial Perception: Measured Ink Gamuts, Nested Realism Constraints, and a Physical-World Bound

    Sep 27, 2026Sandesh Shrestha, K. T. Yasas Mahima, Asanka G. PereraAdversarial Patch AttacksAdversarial Attacks

    Industrial Systems Engineering (ISE), Asian Institute of Technology (AIT), Pathum Thani 12120, Thailand

  6. Beyond Patch Removal: Persistent Adversarial Effects in Vision-Language-Action Policies

    Sep 17, 2026Enhao Wu, Fusen Guo, Yuxin Cao +3Adversarial Patch AttacksAdversarial Attacks on VLA Models

    UNSW Sydney, Australia · UNSW Canberra, Australia · National University of Singapore, Singapore +2

  7. Stealthy in Semantics, Antagonistic in Space: Attacking Visible-Infrared Object Detectors via Object-Level Misalignment

    Sep 16, 2026Yueqi Zhu, Qi Ming, Guo Cheng +6Physical Adversarial AttacksAdversarial Patch Attacks

    Beijing University of Technology · Peking University · National Key Laboratory of Space Integrated Information System, Institute of Software, Chinese Academy of Sciences +1

  8. AgentHijack: Visual Patch Attacks on Multimodal Computer-Use Agents

    Sep 6, 2026Zhihao Liu, Hongyu Sun, Zhiyuan Fu +7Adversarial Patch AttacksComputer-Use Agents

    Hainan University, Hainan 570228, China · University of Chinese Academy of Sciences National Computer Network Intrusion Protection Center, Beijing 101408, China · School of Computing and Communications, Lancaster University, Lancaster, United Kingdom

  9. InfraPatch: Cross-Task Targeted Grayscale Patch Attacks on Infrared-Adapted Vision-Language Models

    Sep 2, 2026Chengyin Hu, Dingyi Lu, Jiaju Han +5Adversarial Patch AttacksLarge Vision-Language Models

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

    Aug 31, 2026Xiaopei Zhu, Siyuan Huang, Zhanhao Hu +3Thermal ImagingAdversarial Patch Attacks

    Department of Computer Science and Technology, Institute for Artificial Intelligence, BNRist, Tsinghua University, Beijing 100084, China · Chinese Institute for Brain Research (CIBR), Beijing 100010, China

  11. ARMOR: Manifold-Oriented Training for Adversarially Robust Aerial Object Detection under Data Scarcity

    Aug 30, 2026Haoran Wang, Matthew Lau, Alec Helbling +7Adversarial RobustnessAdversarial Training

    Georgia Institute of Technology, Atlanta, GA, USA · Khalifa University, Abu Dhabi, UAE · Technology Innovation Institute, Abu Dhabi, UAE

  12. CertVLA: Certified Defense against Physical Visual Attacks for Vision-Language-Action Models

    Aug 21, 2026Hui Lu, Zhijie Peng, Yuqi Lin +8Robustness of VLA ModelsAdversarial Attacks on VLA Models

  13. A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization

    Aug 5, 2026Anadi Goyal, Nandish Chattopadhyay, Anupam Chattopadhyay +1Adversarial Patch AttacksAdversarial Attacks

    Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India · Nanyang Technological University, 50 Nanyang Ave, Singapore 639798

  14. ColorFD: A Finite-Difference Guided Black-Box Physical Adversarial Attack for Remote Sensing Object Detection

    Aug 5, 2026Tiannuo Guo, Guhang Qiu, Yuzhen Xie +3Remote Sensing Image UnderstandingAdversarial Patch Attacks

    College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China

  15. DRIFT: Derailing Denoising Trajectories of Flow-Matching VLAs with Adversarial Patch Attack

    Aug 4, 2026Hoseong Tae, Jong-Seok LeeAdversarial Patch AttacksAdversarial Attacks on VLA Models

    School of Integrated Technology, Yonsei University

  16. VLAGuard: A Framework for Evaluating and Mitigating Physical Attention Hijacking in Vision-Language-Action Robots within Wireless Sensor Networks

    Aug 2, 2026Dongfu Yin, Jinquan ZhangAdversarial Patch AttacksAdversarial Attacks on VLA Models

    Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China · Shenzhen University, Shenzhen, China

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

    Jul 25, 2026Qiucheng Yu, Tao Ni, Yihe Zhou +2Adversarial Patch AttacksFace Recognition

    City University of Hong Kong · King Abdullah University of Science and Technology (KAUST)

  18. AdvSerial: Physical Adversarial Attacks on Infrastructure-mounted Pedestrian Detectors via Semantic Feature Suppression

    Jul 19, 2026Yuanhao Huang, Yilong Ren, Jinlei Wang +3Adversarial Patch AttacksAdversarial Attacks

    School of Transportation Science and Engineering, Beihang University, 100191, Beijing, P.R China · Zhongguancun Laboratory, 100191, Beijing, P.R China · School of Systems Science and Engineering, Sun Yat-Sen University, 510006, Guangzhou, P.R China +1

  19. Adversarial Decoys: Misdirecting Attention-Based Defenses in ViT

    Jul 8, 2026Giulia Marchiori Pietrosanti, Giulio Rossolini, Giorgio ButtazzoAdversarial Patch AttacksAdversarial Attacks

    Department of Excellence in Robotics and AI, Sant’Anna School of Advanced Study, Italy

  20. InfraQR: Edge-Placed QR-Inspired Structured Patch Attacks on Infrared Vision-Language Models

    Jul 8, 2026Xin Li, Jiaju Han, Ma Yaqi +5VLM RobustnessAdversarial Patch Attacks

    China University of Petroleum-Beijing at Karamay, Karamay, Xinjiang, China · Shenzhen Research Institute of Big Data, Shenzhen, China · Guizhou University, Guiyang, China +1

  21. Budget-Aware Adaptive Adversarial Patches for Black-Box Object Detection

    Jun 16, 2026Pedram MohajerAnsari, Amir Salarpour, David Fernandez +1Adversarial Patch AttacksObject Detection

    School of Computing, Clemson University, USA

  22. Structured Adversarial Camouflage via Voronoi Diagrams

    Jun 16, 2026Jens Bayer, Stefan Becker, David Münch +2Adversarial Patch AttacksObject Detection

    Fraunhofer IOSB and Fraunhofer Center for Machine Learning · Karlsruhe Institute of Technology

  23. Detecting Aimbot Cheaters in MOGs

    Jun 2, 2026Salman Shaikh, Tao Ni, Marc DacierAdversarial Patch AttacksAdversarial Examples

  24. Partially Observable Adversarial Patch Attacks on Vision-Language-Action Models in Robotics

    Jun 2, 2026Xiaofei Wang, Mingliang Han, Tianyu Hao +3VLM RobustnessAdversarial Patch Attacks

    Department of Automation, University of Science and Technology of China, Hefei, China · SmartMore Corporation · Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou, China +2

  25. Digital-to-Physical Transfer of Adversarial Patches for Aerial Vehicle Detection

    May 29, 2026Jung Heum Woo, Eun-Kyu LeeAdversarial Patch AttacksAdversarial Robustness

    School of Information Technology Incheon National University Incheon 22012, Republic of Korea

  26. AdvScene: Rethinking Adversarial Patch Evaluation Through Scene Robustness

    May 28, 2026Xiaoyong, Yuan, Lan +1Adversarial Patch AttacksAdversarial Robustness

    Brian · Clemson University · Clemson, SC, USA +1

  27. VLA-Hijack: A Transferable Patch Attack against Vision-Language-Action Models via Visual Proprioception Hijacking

    May 27, 2026Jiyuan Fu, Kaixun Jiang, Jingkai Jia +7Adversarial Patch AttacksAdversarial Attacks on VLA Models

    Fudan University · The Hong Kong Polytechnic University

  28. Exposing Vulnerabilities in Visible-Infrared VLMs: A Unified Geometric Adversarial Framework with Cross-Task Transferability

    May 21, 2026Xiang Chen, Yuxian Dong, Chao Li +6VLM RobustnessAdversarial Patch Attacks

  29. The Unseen Adversaries: Robust and Generalized Defense Against Adversarial Patches

    Apr 29, 2026Vishesh Kumar, Akshay AgarwalAdversarial Patch AttacksOOD Detection

    Trustworthy BiometraVision Lab, Indian Institute of Science Education and Research Bhopal, India

  30. Transferable Physical-World Adversarial Patches Against Object Detection in Autonomous Driving

    Apr 25, 2026Zihui Zhu, Ziqi Zhou, Yichen Wang +3Adversarial Patch AttacksAutonomous Driving Perception

    Huazhong University of Science and Technology