{"total":20,"rows":[{"id":"2103.04098","title":"WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition","created":"2021-03-06","cited_by_count":223,"area":null},{"id":"2210.02579","title":"DigiFace-1M: 1 Million Digital Face Images for Face Recognition","created":"2022-10-05","cited_by_count":92,"area":null},{"id":"2203.02194","title":"Rethinking Reconstruction Autoencoder-Based Out-of-Distribution Detection","created":"2022-03-04","cited_by_count":59,"area":null},{"id":"2204.10149","title":"WebFace260M: A Benchmark for Million-Scale Deep Face Recognition","created":"2022-04-21","cited_by_count":42,"area":null},{"id":"2305.01021","title":"Synthetic Data for Face Recognition: Current State and Future Prospects","created":"2023-05-01","cited_by_count":38,"area":null},{"id":"2108.07189","title":"Masked Face Recognition Challenge: The WebFace260M Track Report","created":"2021-08-16","cited_by_count":12,"area":null},{"id":"2404.11236","title":"ONOT: a High-Quality ICAO-compliant Synthetic Mugshot Dataset","created":"2024-04-17","cited_by_count":10,"area":null},{"id":"2510.17372","title":"Beyond Real Faces: Synthetic Datasets Can Achieve Reliable Recognition Performance without Privacy Compromise","created":"2025-10-20","cited_by_count":8,"area":null},{"id":"2205.11090","title":"FaceMAE: Privacy-Preserving Face Recognition via Masked Autoencoders","created":"2022-05-23","cited_by_count":7,"area":null},{"id":"2102.12308","title":"\"Train one, Classify one, Teach one\" -- Cross-surgery transfer learning for surgical step recognition","created":"2021-02-24","cited_by_count":4,"area":null},{"id":"2308.07590","title":"ADD: An Automatic Desensitization Fisheye Dataset for Autonomous Driving","created":"2023-08-15","cited_by_count":4,"area":null},{"id":"2104.09145","title":"Face-GCN: A Graph Convolutional Network for 3D Dynamic Face Identification/Recognition","created":"2021-04-19","cited_by_count":2,"area":null},{"id":"2105.06967","title":"Open-set Face Recognition for Small Galleries Using Siamese Networks","created":"2021-05-14","cited_by_count":2,"area":null},{"id":"2312.14301","title":"Autoencoder Based Face Verification System","created":"2023-12-21","cited_by_count":2,"area":null},{"id":"2108.11082","title":"3D Face Recognition: A Survey","created":"2021-08-25","cited_by_count":1,"area":null},{"id":"2312.13240","title":"Efficient Verification-Based Face Identification","created":"2023-12-20","cited_by_count":1,"area":null},{"id":"2405.01662","title":"Out-of-distribution detection based on subspace projection of high-dimensional features output by the last convolutional layer","created":"2024-05-02","cited_by_count":1,"area":null},{"id":"2407.03486","title":"Celeb-FBI: A Benchmark Dataset on Human Full Body Images and Age, Gender, Height and Weight Estimation using Deep Learning Approach","created":"2024-07-03","cited_by_count":1,"area":null},{"id":"2109.05635","title":"Mixing between the Cross Entropy and the Expectation Loss Terms","created":"2021-09-12","cited_by_count":0,"area":null},{"id":"2505.15272","title":"DiffProb: Data Pruning for Face Recognition","created":"2025-05-21","cited_by_count":0,"area":null}],"next_cursor":null}