most citedSDFR: Synthetic Data for Face Recognition Competition

7 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20247 cited

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…

cs.CV20241 cited

Synthetic Data for the Mitigation of Demographic Biases in Face Recognition

Pietro Melzi, Christian Rathgeb, Ruben Tolosana +5

This study investigates the possibility of mitigating the demographic biases that affect face recognition technologies through the use of synthetic data. Demographic biases have th…

cs.CV20232 cited

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…

cs.CV2023

GANDiffFace: Controllable Generation of Synthetic Datasets for Face Recognition with Realistic Variations

Pietro Melzi, Christian Rathgeb, Ruben Tolosana +4

Face recognition systems have significantly advanced in recent years, driven by the availability of large-scale datasets. However, several issues have recently came up, including p…

cs.CV20231 cited

Benchmarking of Cancelable Biometrics for Deep Templates

Hatef Otroshi Shahreza, Pietro Melzi, Dailé Osorio-Roig +5

In this paper, we benchmark several cancelable biometrics (CB) schemes on different biometric characteristics. We consider BioHashing, Multi-Layer Perceptron (MLP) Hashing, Bloom F…