17 citations · 36 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
Synthetic to Authentic: Transferring Realism to 3D Face Renderings for Boosting Face Recognition
Parsa Rahimi, Behrooz Razeghi, Sebastien Marcel
In this paper, we investigate the potential of image-to-image translation (I2I) techniques for transferring realism to 3D-rendered facial images in the context of Face Recognition…
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…
Deep Privacy Funnel Model: From a Discriminative to a Generative Approach with an Application to Face Recognition
Behrooz Razeghi, Parsa Rahimi, Sébastien Marcel
In this study, we apply the information-theoretic Privacy Funnel (PF) model to face recognition and develop a method for privacy-preserving representation learning within an end-to…
Deep Variational Privacy Funnel: General Modeling with Applications in Face Recognition
Behrooz Razeghi, Parsa Rahimi, Sébastien Marcel
In this study, we harness the information-theoretic Privacy Funnel (PF) model to develop a method for privacy-preserving representation learning using an end-to-end training framew…