{"total":245,"rows":[{"id":"2203.03373","title":"Adversarial Texture for Fooling Person Detectors in the Physical World","created":"2022-03-07","cited_by_count":96,"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":"2303.09105","title":"Rethinking Model Ensemble in Transfer-based Adversarial Attacks","created":"2023-03-16","cited_by_count":89,"area":null},{"id":"2112.12376","title":"Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization","created":"2021-12-23","cited_by_count":76,"area":null},{"id":"2109.07193","title":"FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack","created":"2021-09-15","cited_by_count":74,"area":null},{"id":"2112.04532","title":"Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detection","created":"2021-12-08","cited_by_count":67,"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":"2211.09773","title":"T-SEA: Transfer-based Self-Ensemble Attack on Object Detection","created":"2022-11-16","cited_by_count":59,"area":null},{"id":"2207.04718","title":"Physical Attack on Monocular Depth Estimation with Optimal Adversarial Patches","created":"2022-07-11","cited_by_count":57,"area":null},{"id":"2203.01730","title":"Beyond 3D Siamese Tracking: A Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds","created":"2022-03-03","cited_by_count":55,"area":null},{"id":"2101.08154","title":"Fooling thermal infrared pedestrian detectors in real world using small bulbs","created":"2021-01-20","cited_by_count":51,"area":null},{"id":"2203.09831","title":"DTA: Physical Camouflage Attacks using Differentiable Transformation Network","created":"2022-03-18","cited_by_count":51,"area":null},{"id":"2110.07719","title":"Certified Patch Robustness via Smoothed Vision Transformers","created":"2021-10-11","cited_by_count":45,"area":null},{"id":"2205.05909","title":"Infrared Invisible Clothing:Hiding from Infrared Detectors at Multiple Angles in Real World","created":"2022-05-12","cited_by_count":42,"area":null},{"id":"2101.02559","title":"Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead","created":"2021-01-04","cited_by_count":41,"area":null},{"id":"2307.01778","title":"Physically Realizable Natural-Looking Clothing Textures Evade Person Detectors via 3D Modeling","created":"2023-07-04","cited_by_count":41,"area":null},{"id":"2305.11618","title":"DAP: A Dynamic Adversarial Patch for Evading Person Detectors","created":"2023-05-19","cited_by_count":40,"area":null},{"id":"2109.07986","title":"Harnessing Perceptual Adversarial Patches for Crowd Counting","created":"2021-09-16","cited_by_count":39,"area":null},{"id":"2303.17297","title":"Understanding the Robustness of 3D Object Detection with Bird's-Eye-View Representations in Autonomous Driving","created":"2023-03-30","cited_by_count":37,"area":null},{"id":"2104.14235","title":"Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety","created":"2021-04-29","cited_by_count":35,"area":null},{"id":"2108.11765","title":"Physical Adversarial Attacks on an Aerial Imagery Object Detector","created":"2021-08-26","cited_by_count":35,"area":null},{"id":"2304.10029","title":"Jedi: Entropy-based Localization and Removal of Adversarial Patches","created":"2023-04-20","cited_by_count":35,"area":null},{"id":"2403.17301","title":"Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous Driving","created":"2024-03-26","cited_by_count":32,"area":null},{"id":"2404.16452","title":"PAD: Patch-Agnostic Defense against Adversarial Patch Attacks","created":"2024-04-25","cited_by_count":32,"area":null},{"id":"2308.07009","title":"ACTIVE: Towards Highly Transferable 3D Physical Camouflage for Universal and Robust Vehicle Evasion","created":"2023-08-14","cited_by_count":31,"area":null},{"id":"2102.02956","title":"DetectorGuard: Provably Securing Object Detectors against Localized Patch Hiding Attacks","created":"2021-02-05","cited_by_count":29,"area":null},{"id":"2205.13618","title":"Phantom Sponges: Exploiting Non-Maximum Suppression to Attack Deep Object Detectors","created":"2022-05-26","cited_by_count":28,"area":null},{"id":"2110.03605","title":"Robust Feature-Level Adversaries are Interpretability Tools","created":"2021-10-07","cited_by_count":27,"area":null},{"id":"2212.05709","title":"HOTCOLD Block: Fooling Thermal Infrared Detectors with a Novel Wearable Design","created":"2022-12-12","cited_by_count":27,"area":null},{"id":"2307.07859","title":"Unified Adversarial Patch for Cross-modal Attacks in the Physical World","created":"2023-07-15","cited_by_count":27,"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":"2312.09558","title":"Towards Transferable Targeted 3D Adversarial Attack in the Physical World","created":"2023-12-15","cited_by_count":25,"area":null},{"id":"2102.04154","title":"Efficient Certified Defenses Against Patch Attacks on Image Classifiers","created":"2021-02-08","cited_by_count":24,"area":null},{"id":"2303.05071","title":"MBPTrack: Improving 3D Point Cloud Tracking with Memory Networks and Box Priors","created":"2023-03-09","cited_by_count":24,"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":"2201.08619","title":"Dangerous Cloaking: Natural Trigger based Backdoor Attacks on Object Detectors in the Physical World","created":"2022-01-21","cited_by_count":22,"area":null},{"id":"2202.01811","title":"ObjectSeeker: Certifiably Robust Object Detection against Patch Hiding Attacks via Patch-agnostic Masking","created":"2022-02-03","cited_by_count":22,"area":null},{"id":"2210.16765","title":"Benchmarking Adversarial Patch Against Aerial Detection","created":"2022-10-30","cited_by_count":21,"area":null},{"id":"2307.14682","title":"Unified Adversarial Patch for Visible-Infrared Cross-modal Attacks in the Physical World","created":"2023-07-27","cited_by_count":21,"area":null},{"id":"2106.02734","title":"Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness","created":"2021-06-04","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":"2106.15202","title":"Inconspicuous Adversarial Patches for Fooling Image Recognition Systems on Mobile Devices","created":"2021-06-29","cited_by_count":18,"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":"2103.08860","title":"Adversarial YOLO: Defense Human Detection Patch Attacks via Detecting Adversarial Patches","created":"2021-03-16","cited_by_count":17,"area":null},{"id":"2109.00124","title":"Learning Coated Adversarial Camouflages for Object Detectors","created":"2021-09-01","cited_by_count":17,"area":null},{"id":"2109.06467","title":"Dodging Attack Using Carefully Crafted Natural Makeup","created":"2021-09-14","cited_by_count":17,"area":null},{"id":"2206.08304","title":"Adversarial Patch Attacks and Defences in Vision-Based Tasks: A Survey","created":"2022-06-16","cited_by_count":17,"area":null},{"id":"2103.09448","title":"Adversarial Attacks on Camera-LiDAR Models for 3D Car Detection","created":"2021-03-17","cited_by_count":16,"area":null},{"id":"2304.02782","title":"FACE-AUDITOR: Data Auditing in Facial Recognition Systems","created":"2023-04-05","cited_by_count":16,"area":null},{"id":"2305.01074","title":"Physical Adversarial Attacks for Surveillance: A Survey","created":"2023-05-01","cited_by_count":15,"area":null},{"id":"2101.10747","title":"Towards Universal Physical Attacks On Cascaded Camera-Lidar 3D Object Detection Models","created":"2021-01-26","cited_by_count":14,"area":null},{"id":"2107.07449","title":"Adversarial Attacks on Multi-task Visual Perception for Autonomous Driving","created":"2021-07-15","cited_by_count":14,"area":null},{"id":"2303.12535","title":"An Effective Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds","created":"2023-03-21","cited_by_count":14,"area":null},{"id":"2103.05472","title":"Differentially Private Imaging via Latent Space Manipulation","created":"2021-03-08","cited_by_count":13,"area":null},{"id":"2104.02655","title":"DeepBlur: A Simple and Effective Method for Natural Image Obfuscation","created":"2021-03-31","cited_by_count":13,"area":null},{"id":"2207.07347","title":"Feasibility of Inconspicuous GAN-generated Adversarial Patches against Object Detection","created":"2022-07-15","cited_by_count":13,"area":null},{"id":"2111.10481","title":"PatchCensor: Patch Robustness Certification for Transformers via Exhaustive Testing","created":"2021-11-19","cited_by_count":12,"area":null},{"id":"2210.04311","title":"Pruning Adversarially Robust Neural Networks without Adversarial Examples","created":"2022-10-09","cited_by_count":12,"area":null},{"id":"2303.01734","title":"AdvART: Adversarial Art for Camouflaged Object Detection Attacks","created":"2023-03-03","cited_by_count":12,"area":null},{"id":"2110.04337","title":"Adversarial Token Attacks on Vision Transformers","created":"2021-10-08","cited_by_count":11,"area":null},{"id":"2112.01723","title":"Adversarial Attacks against a Satellite-borne Multispectral Cloud Detector","created":"2021-12-03","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":"2304.10712","title":"Adversarial Infrared Blocks: A Multi-view Black-box Attack to Thermal Infrared Detectors in Physical World","created":"2023-04-21","cited_by_count":11,"area":null},{"id":"2312.06701","title":"Dynamic Adversarial Attacks on Autonomous Driving Systems","created":"2023-12-10","cited_by_count":11,"area":null},{"id":"2405.07595","title":"Environmental Matching Attack Against Unmanned Aerial Vehicles Object Detection","created":"2024-05-13","cited_by_count":11,"area":null},{"id":"2106.06410","title":"What Can Knowledge Bring to Machine Learning? -- A Survey of Low-shot Learning for Structured Data","created":"2021-06-11","cited_by_count":10,"area":null},{"id":"2107.01943","title":"When and How to Fool Explainable Models (and Humans) with Adversarial Examples","created":"2021-07-05","cited_by_count":10,"area":null},{"id":"2203.09845","title":"Location-Free Camouflage Generation Network","created":"2022-03-18","cited_by_count":10,"area":null},{"id":"2303.01351","title":"APARATE: Adaptive Adversarial Patch for CNN-based Monocular Depth Estimation for Autonomous Navigation","created":"2023-03-02","cited_by_count":10,"area":null},{"id":"2310.03578","title":"Targeted Adversarial Attacks on Generalizable Neural Radiance Fields","created":"2023-10-05","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":"2204.13004","title":"Defending Person Detection Against Adversarial Patch Attack by using Universal Defensive Frame","created":"2022-04-27","cited_by_count":9,"area":null},{"id":"2208.09500","title":"Causality-Inspired Taxonomy for Explainable Artificial Intelligence","created":"2022-08-19","cited_by_count":9,"area":null},{"id":"2311.10366","title":"Breaking Temporal Consistency: Generating Video Universal Adversarial Perturbations Using Image Models","created":"2023-11-17","cited_by_count":9,"area":null},{"id":"2501.05783","title":"UV-Attack: Physical-World Adversarial Attacks for Person Detection via Dynamic-NeRF-based UV Mapping","created":"2025-01-10","cited_by_count":9,"area":null},{"id":"2104.11101","title":"Learning Transferable 3D Adversarial Cloaks for Deep Trained Detectors","created":"2021-04-22","cited_by_count":8,"area":null},{"id":"2109.15177","title":"You Cannot Easily Catch Me: A Low-Detectable Adversarial Patch for Object Detectors","created":"2021-09-30","cited_by_count":8,"area":null},{"id":"2203.04623","title":"Controllable Evaluation and Generation of Physical Adversarial Patch on Face Recognition","created":"2022-03-09","cited_by_count":8,"area":null},{"id":"2209.02339","title":"TransCAB: Transferable Clean-Annotation Backdoor to Object Detection with Natural Trigger in Real-World","created":"2022-09-06","cited_by_count":8,"area":null},{"id":"2302.06060","title":"Threatening Patch Attacks on Object Detection in Optical Remote Sensing Images","created":"2023-02-13","cited_by_count":8,"area":null},{"id":"2405.09924","title":"Infrared Adversarial Car Stickers","created":"2024-05-16","cited_by_count":8,"area":null},{"id":"2105.00113","title":"IPatch: A Remote Adversarial Patch","created":"2021-04-30","cited_by_count":7,"area":null},{"id":"2105.09090","title":"Local Aggressive Adversarial Attacks on 3D Point Cloud","created":"2021-05-19","cited_by_count":7,"area":null},{"id":"2108.07229","title":"Patch Attack Invariance: How Sensitive are Patch Attacks to 3D Pose?","created":"2021-08-16","cited_by_count":7,"area":null},{"id":"2202.12154","title":"Towards Effective and Robust Neural Trojan Defenses via Input Filtering","created":"2022-02-24","cited_by_count":7,"area":null},{"id":"2302.13519","title":"CBA: Contextual Background Attack against Optical Aerial Detection in the Physical World","created":"2023-02-27","cited_by_count":7,"area":null},{"id":"2402.13575","title":"Flexible Physical Camouflage Generation Based on a Differential Approach","created":"2024-02-21","cited_by_count":7,"area":null},{"id":"2403.11397","title":"Defense Against Adversarial Attacks on No-Reference Image Quality Models with Gradient Norm Regularization","created":"2024-03-18","cited_by_count":7,"area":null},{"id":"2408.01934","title":"A Survey and Evaluation of Adversarial Attacks for Object Detection","created":"2024-08-04","cited_by_count":7,"area":null},{"id":"2507.01367","title":"3D Gaussian Splatting Driven Multi-View Robust Physical Adversarial Camouflage Generation","created":"2025-07-02","cited_by_count":7,"area":null},{"id":"2105.07334","title":"Real-time Detection of Practical Universal Adversarial Perturbations","created":"2021-05-16","cited_by_count":6,"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":"2109.15009","title":"Adversarial Semantic Contour for Object Detection","created":"2021-09-30","cited_by_count":6,"area":null},{"id":"2111.04303","title":"Defense Against Explanation Manipulation","created":"2021-11-08","cited_by_count":6,"area":null},{"id":"2112.09422","title":"A Review on Visual Privacy Preservation Techniques for Active and Assisted Living","created":"2021-12-17","cited_by_count":6,"area":null},{"id":"2205.09592","title":"Transferable Physical Attack against Object Detection with Separable Attention","created":"2022-05-19","cited_by_count":6,"area":null},{"id":"2209.13353","title":"Suppress with a Patch: Revisiting Universal Adversarial Patch Attacks against Object Detection","created":"2022-09-27","cited_by_count":6,"area":null},{"id":"2210.08870","title":"Differential Evolution based Dual Adversarial Camouflage: Fooling Human Eyes and Object Detectors","created":"2022-10-17","cited_by_count":6,"area":null},{"id":"2211.08859","title":"Attacking Object Detector Using A Universal Targeted Label-Switch Patch","created":"2022-11-16","cited_by_count":6,"area":null}],"next_cursor":"100"}