7 citations · 10 across the 7 of their papers we have counts for
7 papers
Face Reconstruction from Face Embeddings using Adapter to a Face Foundation Model
Hatef Otroshi Shahreza, Anjith George, Sébastien Marcel
Face recognition systems extract embedding vectors from face images and use these embeddings to verify or identify individuals. Face reconstruction attack (also known as template i…
Unveiling Synthetic Faces: How Synthetic Datasets Can Expose Real Identities
Hatef Otroshi Shahreza, Sébastien Marcel
Synthetic data generation is gaining increasing popularity in different computer vision applications. Existing state-of-the-art face recognition models are trained using large-scal…
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…
SynthDistill: Face Recognition with Knowledge Distillation from Synthetic Data
Hatef Otroshi Shahreza, Anjith George, Sébastien Marcel
State-of-the-art face recognition networks are often computationally expensive and cannot be used for mobile applications. Training lightweight face recognition models also require…
EFaR 2023: Efficient Face Recognition Competition
Jan Niklas Kolf, Fadi Boutros, Jurek Elliesen +24
This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition rece…