SDFR: Synthetic Data for Face Recognition Competition

no code implementations • 6 Apr 2024 • Hatef Otroshi Shahreza, Christophe Ecabert, Anjith George, Alexander Unnervik, Sébastien Marcel, Nicolò Di Domenico, Guido Borghi, Davide Maltoni, Fadi Boutros, Julia Vogel, Naser Damer, Ángela Sánchez-Pérez, EnriqueMas-Candela, Jorge Calvo-Zaragoza, Bernardo Biesseck, Pedro Vidal, Roger Granada, David Menotti, Ivan DeAndres-Tame, Simone Maurizio La Cava, Sara Concas, Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez, Gianpaolo Perelli, Giulia Orrù, Gian Luca Marcialis, Julian Fierrez

The submitted models were trained on existing and also new synthetic datasets and used clever methods to improve training with synthetic data.

Benchmarking Gesture Recognition +1

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

1 code implementation • 17 Nov 2023 • Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez, Minchul Kim, Christian Rathgeb, Xiaoming Liu, Ivan DeAndres-Tame, Aythami Morales, Julian Fierrez, Javier Ortega-Garcia, Weisong Zhao, Xiangyu Zhu, Zheyu Yan, Xiao-Yu Zhang, Jinlin Wu, Zhen Lei, Suvidha Tripathi, Mahak Kothari, Md Haider Zama, Debayan Deb, Bernardo Biesseck, Pedro Vidal, Roger Granada, Guilherme Fickel, Gustavo Führ, David Menotti, Alexander Unnervik, Anjith George, Christophe Ecabert, Hatef Otroshi Shahreza, Parsa Rahimi, Sébastien Marcel, Ioannis Sarridis, Christos Koutlis, Georgia Baltsou, Symeon Papadopoulos, Christos Diou, Nicolò Di Domenico, Guido Borghi, Lorenzo Pellegrini, Enrique Mas-Candela, Ángela Sánchez-Pérez, Andrea Atzori, Fadi Boutros, Naser Damer, Gianni Fenu, Mirko Marras

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.

Face Recognition

Toward responsible face datasets: modeling the distribution of a disentangled latent space for sampling face images from demographic groups

no code implementations • 15 Sep 2023 • Parsa Rahimi, Christophe Ecabert, Sebastien Marcel

Recently, it has been exposed that some modern facial recognition systems could discriminate specific demographic groups and may lead to unfair attention with respect to various facial attributes such as gender and origin.

EFaR 2023: Efficient Face Recognition Competition

1 code implementation • 8 Aug 2023 • Jan Niklas Kolf, Fadi Boutros, Jurek Elliesen, Markus Theuerkauf, Naser Damer, Mohamad Alansari, Oussama Abdul Hay, Sara Alansari, Sajid Javed, Naoufel Werghi, Klemen Grm, Vitomir Štruc, Fernando Alonso-Fernandez, Kevin Hernandez Diaz, Josef Bigun, Anjith George, Christophe Ecabert, Hatef Otroshi Shahreza, Ketan Kotwal, Sébastien Marcel, Iurii Medvedev, Bo Jin, Diogo Nunes, Ahmad Hassanpour, Pankaj Khatiwada, Aafan Ahmad Toor, Bian Yang

To drive further development of efficient face recognition models, the submitted solutions are ranked based on a weighted score of the achieved verification accuracies on a diverse set of benchmarks, as well as the deployability given by the number of floating-point operations and model size.

Lightweight Face Recognition Quantization

EdgeFace: Efficient Face Recognition Model for Edge Devices

3 code implementations • 4 Jul 2023 • Anjith George, Christophe Ecabert, Hatef Otroshi Shahreza, Ketan Kotwal, Sebastien Marcel

In this paper, we present EdgeFace, a lightweight and efficient face recognition network inspired by the hybrid architecture of EdgeNeXt.

Lightweight Face Recognition