17 citations · 43 across the 9 of their papers we have counts for
9 papers
Identity-Conditioned Latent Consistency Distillation for Face Synthesis
Tiago Kienen Chaves, Bernardo Biesseck, David Menotti
Diffusion models have achieved strong results in high-fidelity image synthesis, but their iterative sampling process makes large-scale generation computationally expensive. This li…
UFPR-PEs: A Brazilian Face Recognition Benchmark with Self-Declared Race/Color Labels
Alexandre Diano, Bernardo Biesseck, Gabriel Polo +4
While face recognition systems are widely deployed, ensuring their demographic reliability and robustness under uncontrolled visual conditions remains a critical challenge. To brid…
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…
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…
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…
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…
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…
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…
FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data
Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez +44
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must…