{"total":20,"rows":[{"id":"2303.11296","title":"Attribute-preserving Face Dataset Anonymization via Latent Code Optimization","created":"2023-03-20","cited_by_count":43,"area":null},{"id":"2403.12457","title":"Privacy-Preserving Face Recognition Using Trainable Feature Subtraction","created":"2024-03-19","cited_by_count":24,"area":null},{"id":"2112.04558","title":"SoK: Anti-Facial Recognition Technology","created":"2021-12-08","cited_by_count":16,"area":null},{"id":"2211.01361","title":"My Face My Choice: Privacy Enhancing Deepfakes for Social Media Anonymization","created":"2022-11-02","cited_by_count":14,"area":null},{"id":"2309.16398","title":"Recent Advances of Differential Privacy in Centralized Deep Learning: A Systematic Survey","created":"2023-09-28","cited_by_count":12,"area":null},{"id":"2305.02143","title":"GANonymization: A GAN-based Face Anonymization Framework for Preserving Emotional Expressions","created":"2023-05-03","cited_by_count":9,"area":null},{"id":"2310.08565","title":"Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities","created":"2023-10-12","cited_by_count":9,"area":null},{"id":"2411.09863","title":"Face De-identification: State-of-the-art Methods and Comparative Studies","created":"2024-11-15","cited_by_count":9,"area":null},{"id":"2303.13269","title":"Disguise without Disruption: Utility-Preserving Face De-Identification","created":"2023-03-23","cited_by_count":8,"area":null},{"id":"2209.11531","title":"Deep Learning-based Anonymization of Chest Radiographs: A Utility-preserving Measure for Patient Privacy","created":"2022-09-23","cited_by_count":5,"area":null},{"id":"2311.04833","title":"Anonymizing medical case-based explanations through disentanglement","created":"2023-11-08","cited_by_count":5,"area":null},{"id":"2408.00950","title":"PrivateGaze: Preserving User Privacy in Black-box Mobile Gaze Tracking Services","created":"2024-08-01","cited_by_count":4,"area":null},{"id":"2212.02042","title":"Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning","created":"2022-12-05","cited_by_count":2,"area":null},{"id":"2502.00451","title":"Towards Privacy-aware Mental Health AI Models: Advances, Challenges, and Opportunities","created":"2025-02-01","cited_by_count":2,"area":null},{"id":"2409.03434","title":"A Key-Driven Framework for Identity-Preserving Face Anonymization","created":"2024-09-05","cited_by_count":1,"area":null},{"id":"2412.15590","title":"SemDP: Semantic-level Differential Privacy Protection for Face Datasets","created":"2024-12-20","cited_by_count":1,"area":null},{"id":"2312.02124","title":"VerA: Versatile Anonymization Applicable to Clinical Facial Photographs","created":"2023-12-04","cited_by_count":0,"area":null},{"id":"2511.17747","title":"AEGIS: Preserving privacy of 3D Facial Avatars with Adversarial Perturbations","created":"2025-11-21","cited_by_count":0,"area":null},{"id":"2603.17567","title":"Face anonymization preserving facial expressions and photometric realism","created":"2026-03-18","cited_by_count":0,"area":null},{"id":"2608.17147","title":"Picture the Epsilon: Pursuing Identity-Level Privacy Guarantees for Images","created":"2026-08-17","cited_by_count":0,"area":null}],"next_cursor":null}