24 citations · 80 across the 28 of their papers we have counts for
14 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…
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…
HyperFace: Generating Synthetic Face Recognition Datasets by Exploring Face Embedding Hypersphere
Hatef Otroshi Shahreza, Sébastien Marcel
Face recognition datasets are often collected by crawling Internet and without individuals' consents, raising ethical and privacy concerns. Generating synthetic datasets for traini…
Digi2Real: Bridging the Realism Gap in Synthetic Data Face Recognition via Foundation Models
Anjith George, Sebastien Marcel
The accuracy of face recognition systems has improved significantly in the past few years, thanks to the large amount of data collected and advancements in neural network architect…
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…
Modality Agnostic Heterogeneous Face Recognition with Switch Style Modulators
Anjith George, Sebastien Marcel
Heterogeneous Face Recognition (HFR) systems aim to enhance the capability of face recognition in challenging cross-modal authentication scenarios. However, the significant domain…
Synthetic Face Datasets Generation via Latent Space Exploration from Brownian Identity Diffusion
David Geissbühler, Hatef Otroshi Shahreza, Sébastien Marcel
Face recognition models are trained on large-scale datasets, which have privacy and ethical concerns. Lately, the use of synthetic data to complement or replace genuine data for th…
Heterogeneous Face Recognition Using Domain Invariant Units
Anjith George, Sebastien Marcel
Heterogeneous Face Recognition (HFR) aims to expand the applicability of Face Recognition (FR) systems to challenging scenarios, enabling the matching of face images across differe…
From Modalities to Styles: Rethinking the Domain Gap in Heterogeneous Face Recognition
Anjith George, Sebastien Marcel
Heterogeneous Face Recognition (HFR) focuses on matching faces from different domains, for instance, thermal to visible images, making Face Recognition (FR) systems more versatile…
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…
ChatGPT and biometrics: an assessment of face recognition, gender detection, and age estimation capabilities
Ahmad Hassanpour, Yasamin Kowsari, Hatef Otroshi Shahreza +2
This paper explores the application of large language models (LLMs), like ChatGPT, for biometric tasks. We specifically examine the capabilities of ChatGPT in performing biometric-…
Model Pairing Using Embedding Translation for Backdoor Attack Detection on Open-Set Classification Tasks
Alexander Unnervik, Hatef Otroshi Shahreza, Anjith George +1
Backdoor attacks allow an attacker to embed a specific vulnerability in a machine learning algorithm, activated when an attacker-chosen pattern is presented, causing a specific mis…
Approximating Optimal Morphing Attacks using Template Inversion
Laurent Colbois, Hatef Otroshi Shahreza, Sébastien Marcel
Recent works have demonstrated the feasibility of inverting face recognition systems, enabling to recover convincing face images using only their embeddings. We leverage such templ…