{"total":75,"rows":[{"id":"2110.01167","title":"Trustworthy AI: From Principles to Practices","created":"2021-10-04","cited_by_count":207,"area":null},{"id":"2108.00401","title":"Advances in adversarial attacks and defenses in computer vision: A survey","created":"2021-08-01","cited_by_count":127,"area":null},{"id":"2105.03162","title":"Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition","created":"2021-05-07","cited_by_count":97,"area":null},{"id":"2104.06728","title":"Adversarial Sticker: A Stealthy Attack Method in the Physical World","created":"2021-04-14","cited_by_count":93,"area":null},{"id":"2209.15179","title":"Physical Adversarial Attack meets Computer Vision: A Decade Survey","created":"2022-09-30","cited_by_count":67,"area":null},{"id":"2106.14948","title":"Deep Learning for Face Anti-Spoofing: A Survey","created":"2021-06-28","cited_by_count":65,"area":null},{"id":"2306.10008","title":"CLIP2Protect: Protecting Facial Privacy using Text-Guided Makeup via Adversarial Latent Search","created":"2023-06-16","cited_by_count":43,"area":null},{"id":"2212.12995","title":"Simultaneously Optimizing Perturbations and Positions for Black-box Adversarial Patch Attacks","created":"2022-12-26","cited_by_count":42,"area":null},{"id":"2207.13129","title":"LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity","created":"2022-07-26","cited_by_count":39,"area":null},{"id":"2111.09999","title":"TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep Neural Network Systems","created":"2021-11-19","cited_by_count":36,"area":null},{"id":"2109.09320","title":"Robust Physical-World Attacks on Face Recognition","created":"2021-09-20","cited_by_count":26,"area":null},{"id":"2209.14262","title":"A Survey on Physical Adversarial Attack in Computer Vision","created":"2022-09-28","cited_by_count":25,"area":null},{"id":"2307.07653","title":"RFLA: A Stealthy Reflected Light Adversarial Attack in the Physical World","created":"2023-07-14","cited_by_count":23,"area":null},{"id":"2210.16765","title":"Benchmarking Adversarial Patch Against Aerial Detection","created":"2022-10-30","cited_by_count":21,"area":null},{"id":"2302.09457","title":"Attacks in Adversarial Machine Learning: A Systematic Survey from the Life-cycle Perspective","created":"2023-02-19","cited_by_count":20,"area":null},{"id":"2308.06173","title":"Physical Adversarial Attacks For Camera-based Smart Systems: Current Trends, Categorization, Applications, Research Challenges, and Future Outlook","created":"2023-08-11","cited_by_count":20,"area":null},{"id":"2111.10759","title":"Adversarial Mask: Real-World Universal Adversarial Attack on Face Recognition Model","created":"2021-11-21","cited_by_count":19,"area":null},{"id":"2310.00633","title":"A Survey of Robustness and Safety of 2D and 3D Deep Learning Models Against Adversarial Attacks","created":"2023-10-01","cited_by_count":19,"area":null},{"id":"2305.12863","title":"Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attacks","created":"2023-05-22","cited_by_count":18,"area":null},{"id":"2109.06467","title":"Dodging Attack Using Carefully Crafted Natural Makeup","created":"2021-09-14","cited_by_count":17,"area":null},{"id":"2209.14692","title":"Digital and Physical Face Attacks: Reviewing and One Step Further","created":"2022-09-29","cited_by_count":17,"area":null},{"id":"2305.01074","title":"Physical Adversarial Attacks for Surveillance: A Survey","created":"2023-05-01","cited_by_count":15,"area":null},{"id":"2105.08619","title":"On the Robustness of Domain Constraints","created":"2021-05-18","cited_by_count":11,"area":null},{"id":"2211.01671","title":"Visual Adversarial Attacks and Defenses in the Physical World: A Survey","created":"2022-11-03","cited_by_count":11,"area":null},{"id":"2105.00249","title":"A Master Key Backdoor for Universal Impersonation Attack against DNN-based Face Verification","created":"2021-05-01","cited_by_count":10,"area":null},{"id":"2311.01473","title":"Adversarial Examples in the Physical World: A Survey","created":"2023-11-01","cited_by_count":10,"area":null},{"id":"2312.14217","title":"Adversarial Infrared Curves: An Attack on Infrared Pedestrian Detectors in the Physical World","created":"2023-12-21","cited_by_count":10,"area":null},{"id":"2408.12387","title":"Makeup-Guided Facial Privacy Protection via Untrained Neural Network Priors","created":"2024-08-20","cited_by_count":8,"area":null},{"id":"2511.14074","title":"Dynamic Black-box Backdoor Attacks on IoT Sensory Data","created":"2025-11-18","cited_by_count":8,"area":null},{"id":"2206.12590","title":"RSTAM: An Effective Black-Box Impersonation Attack on Face Recognition using a Mobile and Compact Printer","created":"2022-06-25","cited_by_count":7,"area":null},{"id":"2106.05261","title":"We Can Always Catch You: Detecting Adversarial Patched Objects WITH or WITHOUT Signature","created":"2021-06-09","cited_by_count":6,"area":null},{"id":"2204.00853","title":"Adversarial Neon Beam: A Light-based Physical Attack to DNNs","created":"2022-04-02","cited_by_count":6,"area":null},{"id":"2212.06776","title":"Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection","created":"2022-12-13","cited_by_count":5,"area":null},{"id":"2303.04238","title":"Patch of Invisibility: Naturalistic Physical Black-Box Adversarial Attacks on Object Detectors","created":"2023-03-07","cited_by_count":5,"area":null},{"id":"2306.12111","title":"A Comprehensive Study on the Robustness of Image Classification and Object Detection in Remote Sensing: Surveying and Benchmarking","created":"2023-06-21","cited_by_count":5,"area":null},{"id":"2410.16317","title":"A Survey on Physical Adversarial Attacks against Face Recognition Systems","created":"2024-10-10","cited_by_count":4,"area":null},{"id":"2112.11290","title":"Review of Face Presentation Attack Detection Competitions","created":"2021-12-21","cited_by_count":3,"area":null},{"id":"2202.02751","title":"Tubes Among Us: Analog Attack on Automatic Speaker Identification","created":"2022-02-06","cited_by_count":3,"area":null},{"id":"2305.13548","title":"Attribute-Guided Encryption with Facial Texture Masking","created":"2023-05-22","cited_by_count":3,"area":null},{"id":"2306.16131","title":"Distributional Modeling for Location-Aware Adversarial Patches","created":"2023-06-28","cited_by_count":3,"area":null},{"id":"2402.19027","title":"How to Train your Antivirus: RL-based Hardening through the Problem-Space","created":"2024-02-29","cited_by_count":3,"area":null},{"id":"2404.14693","title":"DIP-Watermark: A Double Identity Protection Method Based on Robust Adversarial Watermark","created":"2024-04-23","cited_by_count":3,"area":null},{"id":"2208.00539","title":"Is current research on adversarial robustness addressing the right problem?","created":"2022-07-31","cited_by_count":2,"area":null},{"id":"2211.07383","title":"Attacking Face Recognition with T-shirts: Database, Vulnerability Assessment and Detection","created":"2022-11-14","cited_by_count":2,"area":null},{"id":"2406.03684","title":"Principles of Designing Robust Remote Face Anti-Spoofing Systems","created":"2024-06-06","cited_by_count":2,"area":null},{"id":"2501.06533","title":"DivTrackee versus DynTracker: Promoting Diversity in Anti-Facial Recognition against Dynamic FR Strategy","created":"2025-01-11","cited_by_count":2,"area":null},{"id":"2202.08892","title":"Developing Imperceptible Adversarial Patches to Camouflage Military Assets From Computer Vision Enabled Technologies","created":"2022-02-17","cited_by_count":1,"area":null},{"id":"2205.14629","title":"Superclass Adversarial Attack","created":"2022-05-29","cited_by_count":1,"area":null},{"id":"2208.02430","title":"A New Kind of Adversarial Example","created":"2022-08-04","cited_by_count":1,"area":null},{"id":"2301.12046","title":"Semantic Adversarial Attacks on Face Recognition through Significant Attributes","created":"2023-01-28","cited_by_count":1,"area":null},{"id":"2306.16614","title":"Group-based Robustness: A General Framework for Customized Robustness in the Real World","created":"2023-06-29","cited_by_count":1,"area":null},{"id":"2307.13294","title":"Imperceptible Physical Attack against Face Recognition Systems via LED Illumination Modulation","created":"2023-07-25","cited_by_count":1,"area":null},{"id":"2310.00438","title":"Human-Producible Adversarial Examples","created":"2023-09-30","cited_by_count":1,"area":null},{"id":"2505.08423","title":"DArFace: Deformation Aware Robustness for Low Quality Face Recognition","created":"2025-05-13","cited_by_count":1,"area":null},{"id":"2507.06856","title":"IAP: Invisible Adversarial Patch Attack through Perceptibility-Aware Localization and Perturbation Optimization","created":"2025-07-09","cited_by_count":1,"area":null},{"id":"2507.07776","title":"SCOOTER: A Human Evaluation Framework for Unrestricted Adversarial Examples","created":"2025-07-10","cited_by_count":1,"area":null},{"id":"2509.17457","title":"Explainable AI for Analyzing Person-Specific Patterns in Facial Recognition Tasks","created":"2025-09-22","cited_by_count":1,"area":null},{"id":"2107.12473","title":"Adversarial Attacks with Time-Scale Representations","created":"2021-07-26","cited_by_count":0,"area":null},{"id":"2202.04978","title":"Towards Assessing and Characterizing the Semantic Robustness of Face Recognition","created":"2022-02-10","cited_by_count":0,"area":null},{"id":"2210.09153","title":"Face Pasting Attack","created":"2022-10-17","cited_by_count":0,"area":null},{"id":"2211.16253","title":"Advancing Deep Metric Learning Through Multiple Batch Norms And Multi-Targeted Adversarial Examples","created":"2022-11-29","cited_by_count":0,"area":null},{"id":"2301.03966","title":"AdvBiom: Adversarial Attacks on Biometric Matchers","created":"2023-01-10","cited_by_count":0,"area":null},{"id":"2304.05048","title":"Simultaneous Adversarial Attacks On Multiple Face Recognition System Components","created":"2023-04-11","cited_by_count":0,"area":null},{"id":"2309.05879","title":"Generalized Attacks on Face Verification Systems","created":"2023-09-12","cited_by_count":0,"area":null},{"id":"2309.16710","title":"General Lipschitz: Certified Robustness Against Resolvable Semantic Transformations via Transformation-Dependent Randomized Smoothing","created":"2023-08-17","cited_by_count":0,"area":null},{"id":"2311.11753","title":"AdvGen: Physical Adversarial Attack on Face Presentation Attack Detection Systems","created":"2023-11-20","cited_by_count":0,"area":null},{"id":"2403.03674","title":"Adversarial Infrared Geometry: Using Geometry to Perform Adversarial Attack against Infrared Pedestrian Detectors","created":"2024-03-06","cited_by_count":0,"area":null},{"id":"2412.13376","title":"Targeted View-Invariant Adversarial Perturbations for 3D Object Recognition","created":"2024-12-17","cited_by_count":0,"area":null},{"id":"2509.12939","title":"Sy-FAR: Symmetry-based Fair Adversarial Robustness","created":"2025-09-16","cited_by_count":0,"area":null},{"id":"2601.09806","title":"Diffusion-Driven Deceptive Patches: Adversarial Manipulation and Forensic Detection in Facial Identity Verification","created":"2026-01-14","cited_by_count":0,"area":null},{"id":"2603.21867","title":"Adversarial Camouflage","created":"2026-03-23","cited_by_count":0,"area":null},{"id":"2604.19365","title":"Detection of T-shirt Presentation Attacks in Face Recognition Systems","created":"2026-04-21","cited_by_count":0,"area":null},{"id":"2607.25926","title":"Face De-Identification: A Domain-Centric Survey from Capture to Processing","created":"2026-07-28","cited_by_count":0,"area":null},{"id":"2608.04559","title":"ColorFD: A Finite-Difference Guided Black-Box Physical Adversarial Attack for Remote Sensing Object Detection","created":"2026-08-05","cited_by_count":0,"area":null},{"id":"2610.17323","title":"SSM-Attack: Learning Where to Perturb for Black-Box Face Privacy","created":"2026-10-12","cited_by_count":0,"area":null}],"next_cursor":null}