{"total":45,"rows":[{"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":"2201.12296","title":"Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions","created":"2022-01-28","cited_by_count":80,"area":null},{"id":"2101.01461","title":"PointCutMix: Regularization Strategy for Point Cloud Classification","created":"2021-01-05","cited_by_count":69,"area":null},{"id":"2103.03046","title":"PointGuard: Provably Robust 3D Point Cloud Classification","created":"2021-03-04","cited_by_count":49,"area":null},{"id":"2111.10990","title":"Imperceptible Transfer Attack and Defense on 3D Point Cloud Classification","created":"2021-11-22","cited_by_count":36,"area":null},{"id":"2103.16074","title":"PointBA: Towards Backdoor Attacks in 3D Point Cloud","created":"2021-03-30","cited_by_count":35,"area":null},{"id":"2210.15291","title":"Isometric 3D Adversarial Examples in the Physical World","created":"2022-10-27","cited_by_count":25,"area":null},{"id":"2308.12113","title":"Advancements in Point Cloud Data Augmentation for Deep Learning: A Survey","created":"2023-08-23","cited_by_count":24,"area":null},{"id":"2408.05500","title":"PointNCBW: Towards Dataset Ownership Verification for Point Clouds via Negative Clean-label Backdoor Watermark","created":"2024-08-10","cited_by_count":20,"area":null},{"id":"2202.07261","title":"Exploring the Devil in Graph Spectral Domain for 3D Point Cloud Attacks","created":"2022-02-15","cited_by_count":19,"area":null},{"id":"2307.10235","title":"Towards Viewpoint-Invariant Visual Recognition via Adversarial Training","created":"2023-07-16","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":"2203.15245","title":"Robust Structured Declarative Classifiers for 3D Point Clouds: Defending Adversarial Attacks with Implicit Gradients","created":"2022-03-29","cited_by_count":17,"area":null},{"id":"2103.16652","title":"Robustness Certification for Point Cloud Models","created":"2021-03-30","cited_by_count":16,"area":null},{"id":"2207.13326","title":"Point Cloud Attacks in Graph Spectral Domain: When 3D Geometry Meets Graph Signal Processing","created":"2022-07-27","cited_by_count":16,"area":null},{"id":"2104.03356","title":"Universal Spectral Adversarial Attacks for Deformable Shapes","created":"2021-04-07","cited_by_count":14,"area":null},{"id":"2111.03549","title":"Interpreting Representation Quality of DNNs for 3D Point Cloud Processing","created":"2021-11-05","cited_by_count":12,"area":null},{"id":"2203.03888","title":"ART-Point: Improving Rotation Robustness of Point Cloud Classifiers via Adversarial Rotation","created":"2022-03-08","cited_by_count":12,"area":null},{"id":"2308.07546","title":"3DHacker: Spectrum-based Decision Boundary Generation for Hard-label 3D Point Cloud Attack","created":"2023-08-15","cited_by_count":9,"area":null},{"id":"2110.04158","title":"Explainability-Aware One Point Attack for Point Cloud Neural Networks","created":"2021-10-08","cited_by_count":7,"area":null},{"id":"2211.14207","title":"Invariance-Aware Randomized Smoothing Certificates","created":"2022-11-25","cited_by_count":7,"area":null},{"id":"2104.02963","title":"The art of defense: letting networks fool the attacker","created":"2021-04-07","cited_by_count":6,"area":null},{"id":"2110.03745","title":"Adversarial Attack by Limited Point Cloud Surface Modifications","created":"2021-10-07","cited_by_count":6,"area":null},{"id":"2303.01959","title":"PointCert: Point Cloud Classification with Deterministic Certified Robustness Guarantees","created":"2023-03-03","cited_by_count":6,"area":null},{"id":"2307.10875","title":"Risk-optimized Outlier Removal for Robust 3D Point Cloud Classification","created":"2023-07-20","cited_by_count":6,"area":null},{"id":"2207.07539","title":"3DVerifier: Efficient Robustness Verification for 3D Point Cloud Models","created":"2022-07-15","cited_by_count":5,"area":null},{"id":"2307.00309","title":"Adversarial Attacks and Defenses on 3D Point Cloud Classification: A Survey","created":"2023-07-01","cited_by_count":5,"area":null},{"id":"2107.03552","title":"Staying in Shape: Learning Invariant Shape Representations using Contrastive Learning","created":"2021-07-08","cited_by_count":4,"area":null},{"id":"2202.07453","title":"Random Walks for Adversarial Meshes","created":"2022-02-15","cited_by_count":3,"area":null},{"id":"2303.09731","title":"Exorcising ''Wraith'': Protecting LiDAR-based Object Detector in Automated Driving System from Appearing Attacks","created":"2023-03-17","cited_by_count":3,"area":null},{"id":"2111.08973","title":"Generating Unrestricted 3D Adversarial Point Clouds","created":"2021-11-17","cited_by_count":2,"area":null},{"id":"2209.11916","title":"A Simple Strategy to Provable Invariance via Orbit Mapping","created":"2022-09-24","cited_by_count":2,"area":null},{"id":"2308.05525","title":"Robustifying Point Cloud Networks by Refocusing","created":"2023-08-10","cited_by_count":2,"area":null},{"id":"2410.09691","title":"Robust 3D Point Clouds Classification based on Declarative Defenders","created":"2024-10-13","cited_by_count":2,"area":null},{"id":"2401.11406","title":"Adversarial Augmentation Training Makes Action Recognition Models More Robust to Realistic Video Distribution Shifts","created":"2024-01-21","cited_by_count":1,"area":null},{"id":"2505.13289","title":"RECON: Robust symmetry discovery via Explicit Canonical Orientation Normalization","created":"2025-05-19","cited_by_count":1,"area":null},{"id":"2507.18870","title":"Transferable and Undefendable Point Cloud Attacks via Medial Axis Transform","created":"2025-07-25","cited_by_count":1,"area":null},{"id":"2112.09428","title":"Dynamics-aware Adversarial Attack of 3D Sparse Convolution Network","created":"2021-12-17","cited_by_count":0,"area":null},{"id":"2303.06641","title":"Adaptive Local Adversarial Attacks on 3D Point Clouds for Augmented Reality","created":"2023-03-12","cited_by_count":0,"area":null},{"id":"2412.00404","title":"Hard-Label Black-Box Attacks on 3D Point Clouds","created":"2024-11-30","cited_by_count":0,"area":null},{"id":"2412.19015","title":"Imperceptible Adversarial Attacks on Point Clouds Guided by Point-to-Surface Field","created":"2024-12-26","cited_by_count":0,"area":null},{"id":"2507.00690","title":"Cage-Based Deformation for Transferable and Undefendable Point Cloud Attack","created":"2025-07-01","cited_by_count":0,"area":null},{"id":"2510.19371","title":"AegisRF: Adversarial Perturbations Guided with Sensitivity for Protecting Intellectual Property of Neural Radiance Fields","created":"2025-10-22","cited_by_count":0,"area":null},{"id":"2511.21574","title":"Multimodal Robust Prompt Distillation for 3D Point Cloud Models","created":"2025-11-26","cited_by_count":0,"area":null},{"id":"2601.23102","title":"Rethinking Transferable Adversarial Attacks on Point Clouds from a Compact Subspace Perspective","created":"2026-01-30","cited_by_count":0,"area":null}],"next_cursor":null}