17 citations · 42 across the 14 of their papers we have counts for
15 papers
Augmenting Large Audio Language Models with Low-Level Acoustic Features for Dysarthric Speech Detection
Mahdi Amiri, Hatef Otroshi Shahreza, Pascal Frossard +1
Automatic dysarthric speech detection approaches can support traditional clinical diagnosis, which relies on costly and time-consuming evaluation by a speech and language pathologi…
Foundation and Multimodal Large Language Models for Face Presentation and Morph Attack Detection
Hatef Otroshi Shahreza, Asif Hussain Khan, Peter Lorenz +2
Face recognition systems are increasingly deployed in security-critical applications, yet they remain vulnerable to presentation and morph attacks. Presentation attack detection (P…
Improving Low-Resolution Face Recognition under Limited Data: How Synthetic Data Generation Can Close the Domain Gap
Luis S. Luevano, Ünsal Öztürk, Hatef Otroshi Shahreza +2
Face Recognition (FR) systems in surveillance settings often encounter Low Resolution (LR) faces, those whose face region falls below the standard 112 112 input size. Whil…
IJCB-AFMFR 2026: Competition on Adapting Foundation Models for Face Recognition Using Synthetic Training Data
Tahar Chettaoui, Guray Ozgur, Eduarda Caldeira +13
This paper presents a summary of the Competition on Adapting Foundation Models for Face Recognition Using Synthetic Training Data (AFMFR), held at the 2026 International Joint Conf…
Evaluating Multimodal Large Language Models for Heterogeneous Face Recognition
Hatef Otroshi Shahreza, Anjith George, Sébastien Marcel
Multimodal Large Language Models (MLLMs) have recently demonstrated strong performance on a wide range of vision-language tasks, raising interest in their potential use for biometr…
Exploring ChatGPT for Face Presentation Attack Detection in Zero and Few-Shot in-Context Learning
Alain Komaty, Hatef Otroshi Shahreza, Anjith George +1
This study highlights the potential of ChatGPT (specifically GPT-4o) as a competitive alternative for Face Presentation Attack Detection (PAD), outperforming several PAD models, in…
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…
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…
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…
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…
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…
EdgeFace: Efficient Face Recognition Model for Edge Devices
Anjith George, Christophe Ecabert, Hatef Otroshi Shahreza +2
In this paper, we present EdgeFace, a lightweight and efficient face recognition network inspired by the hybrid architecture of EdgeNeXt. By effectively combining the strengths of…
MLP-Hash: Protecting Face Templates via Hashing of Randomized Multi-Layer Perceptron
Hatef Otroshi Shahreza, Vedrana Krivokuća Hahn, Sébastien Marcel
Applications of face recognition systems for authentication purposes are growing rapidly. Although state-of-the-art (SOTA) face recognition systems have high recognition accuracy,…