Hatef Otroshi Shahreza

Cette personne a quitté l’EPFL

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Publications associées (30)

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FRCSyn Challenge atWACV 2024: Face Recognition Challenge in the Era of Synthetic Data

Hatef Otroshi Shahreza, Alexander Carl Unnervik, Parsa Rahimi Noshanagh

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 be covered in more detail. This paper offers an overview of the Face Recogni ...

IEEE2024

Template Inversion Attack against Face Recognition Systems using 3D Face Reconstruction

Hatef Otroshi Shahreza

Face recognition systems are increasingly being used in different applications. In such systems, some features (also known as embeddings or templates) are extracted from each face image. Then, the extracted templates are stored in the system's database dur ...

Ieee Computer Soc2023

Hybrid Protection of Biometric Templates by Combining Homomorphic Encryption and Cancelable Biometrics

Sébastien Marcel, Hatef Otroshi Shahreza

Homomorphic Encryption (HE) has become a wellknown tool for privacy-preserving recognition in biometric systems. Despite some important advantages of HE (such as preservation of recognition accuracy), there are two main drawbacks in the application of HE t ...

IEEE2022

Face Recognition Using Lensless Camera

Hatef Otroshi Shahreza

Coded aperture imaging is an emerging technique allowing thin form factor cameras that can be cheaply constructed. Many applications benefit from using such lensless cameras, such as face recognition. We propose a method for face recognition using coded ap ...

IEEE2024

Second Frcsyn-ongoing: Winning Solutions and Post-challenge Analysis to Improve Face Recognition with Synthetic Data

Hatef Otroshi Shahreza, Alexander Carl Unnervik, Parsa Rahimi Noshanagh

Synthetic data is gaining increasing popularity for face recognition technologies, mainly due to the privacy concerns and challenges associated with obtaining real data, including diverse scenarios, quality, and demographic groups, among others. It also of ...

ELSEVIER2025

Breaking Template Protection: Reconstruction of Face Images from Protected Facial Templates

Hatef Otroshi Shahreza

Face recognition systems tend toward ubiquity and are commonly utilized for security purposes. These systems operate based on facial representations, called templates, extracted by a deep neural network from each face image. However, it has been shown that ...

IEEE2024

Blackbox Face Reconstruction from Deep Facial Embeddings Using A Different Face Recognition Model

Hatef Otroshi Shahreza

Face recognition systems generally store features (called embeddings) extracted from each face image during the enrollment stage, and then compare the extracted embeddings with the stored embeddings during the recognition stage. In this paper, we focus on ...

New York2023

SDFR: Synthetic Data for Face Recognition Competition

Hatef Otroshi Shahreza, Alexander Carl Unnervik

Large-scale face recognition datasets are collected by crawling the Internet and without individuals' consent, raising legal, ethical, and privacy concerns. With the recent advances in generative models, recently several works proposed generating synthetic ...

IEEE2024

Approximating Optimal Morphing Attacks using Template Inversion

Hatef Otroshi Shahreza

Recent works have demonstrated the feasibility of inverting face recognition systems, enabling to recover convincing face images using only their embeddings. We leverage such template inversion models to develop a novel type of deep morphing attack based o ...

IEEE2023

SynthDistill: Face Recognition with Knowledge Distillation from Synthetic Data

Hatef Otroshi Shahreza

State-of-the-art face recognition networks are often computationally expensive and cannot be used for mobile applications. Training lightweight face recognition models also requires large identity-labeled datasets. Meanwhile, there are privacy and ethical ...

IEEE2023