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cs.CV2025

A Comparative Study on Synthetic Facial Data Generation Techniques for Face Recognition

Pedro Vidal, Bernardo Biesseck, Luiz E. L. Coelho +2

Facial recognition has become a widely used method for authentication and identification, with applications for secure access and locating missing persons. Its success is largely a…

cs.CV2025

Second FRCSyn-onGoing: Winning Solutions and Post-Challenge Analysis to Improve Face Recognition with Synthetic Data

Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi +56

Synthetic data is gaining increasing popularity for face recognition technologies, mainly due to the privacy concerns and challenges associated with obtaining real data, including…

cs.CV2024

Watchlist Challenge: 3rd Open-set Face Detection and Identification

Furkan Kasım, Terrance E. Boult, Rensso Mora +8

In the current landscape of biometrics and surveillance, the ability to accurately recognize faces in uncontrolled settings is paramount. The Watchlist Challenge addresses this cri…

cs.CV2024

TCDiff: Triple Condition Diffusion Model with 3D Constraints for Stylizing Synthetic Faces

Bernardo Biesseck, Pedro Vidal, Luiz Coelho +2

A robust face recognition model must be trained using datasets that include a large number of subjects and numerous samples per subject under varying conditions (such as pose, expr…

cs.CV2024

Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data

Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi +55

Synthetic data is gaining increasing relevance for training machine learning models. This is mainly motivated due to several factors such as the lack of real data and intra-class v…

cs.CV2024

SDFR: Synthetic Data for Face Recognition Competition

Hatef Otroshi Shahreza, Christophe Ecabert, Anjith George +25

Large-scale face recognition datasets are collected by crawling the Internet and without individuals' consent, raising legal, ethical, and privacy concerns. With the recent advance…