Zobrazeno 1 - 10
of 188
pro vyhledávání: '"Marcel, Sebastien"'
Autor:
Linghu, Yu, Pereira, Tiago de Freitas, Ecabert, Christophe, Marcel, Sébastien, Günther, Manuel
Fair biometric algorithms have similar verification performance across different demographic groups given a single decision threshold. Unfortunately, for state-of-the-art face recognition networks, score distributions differ between demographics. Con
Externí odkaz:
http://arxiv.org/abs/2407.14087
Autor:
George, Anjith, Marcel, Sebastien
Heterogeneous Face Recognition (HFR) systems aim to enhance the capability of face recognition in challenging cross-modal authentication scenarios. However, the significant domain gap between the source and target modalities poses a considerable chal
Externí odkaz:
http://arxiv.org/abs/2407.08640
In this paper, we investigate the potential of image-to-image translation (I2I) techniques for transferring realism to 3D-rendered facial images in the context of Face Recognition (FR) systems. The primary motivation for using 3D-rendered facial imag
Externí odkaz:
http://arxiv.org/abs/2407.07627
With advancements in hardware, high-quality HMD devices are being developed by numerous companies, driving increased consumer interest in AR, VR, and MR applications. In this work, we present a new dataset, called VRBiom, of periocular videos acquire
Externí odkaz:
http://arxiv.org/abs/2407.02150
Face Recognition (FR) 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 the training of FR models has been proposed. While promising result
Externí odkaz:
http://arxiv.org/abs/2405.00228
Autor:
George, Anjith, Marcel, Sebastien
Heterogeneous Face Recognition (HFR) aims to expand the applicability of Face Recognition (FR) systems to challenging scenarios, enabling the matching of face images across different domains, such as matching thermal images to visible spectra. Howeve
Externí odkaz:
http://arxiv.org/abs/2404.14343
Autor:
George, Anjith, Marcel, Sebastien
Heterogeneous Face Recognition (HFR) focuses on matching faces from different domains, for instance, thermal to visible images, making Face Recognition (FR) systems more versatile for challenging scenarios. However, the domain gap between these domai
Externí odkaz:
http://arxiv.org/abs/2404.14247
Autor:
DeAndres-Tame, Ivan, Tolosana, Ruben, Melzi, Pietro, Vera-Rodriguez, Ruben, Kim, Minchul, Rathgeb, Christian, Liu, Xiaoming, Morales, Aythami, Fierrez, Julian, Ortega-Garcia, Javier, Zhong, Zhizhou, Huang, Yuge, Mi, Yuxi, Ding, Shouhong, Zhou, Shuigeng, He, Shuai, Fu, Lingzhi, Cong, Heng, Zhang, Rongyu, Xiao, Zhihong, Smirnov, Evgeny, Pimenov, Anton, Grigorev, Aleksei, Timoshenko, Denis, Asfaw, Kaleb Mesfin, Low, Cheng Yaw, Liu, Hao, Wang, Chuyi, Zuo, Qing, He, Zhixiang, Shahreza, Hatef Otroshi, George, Anjith, Unnervik, Alexander, Rahimi, Parsa, Marcel, Sébastien, Neto, Pedro C., Huber, Marco, Kolf, Jan Niklas, Damer, Naser, Boutros, Fadi, Cardoso, Jaime S., Sequeira, Ana F., Atzori, Andrea, Fenu, Gianni, Marras, Mirko, Štruc, Vitomir, Yu, Jiang, Li, Zhangjie, Li, Jichun, Zhao, Weisong, Lei, Zhen, Zhu, Xiangyu, Zhang, Xiao-Yu, Biesseck, Bernardo, Vidal, Pedro, Coelho, Luiz, Granada, Roger, Menotti, David
Publikováno v:
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRw 2024)
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 variability, time and errors produced in manual labeling, and in some c
Externí odkaz:
http://arxiv.org/abs/2404.10378
Autor:
Geissbühler, David, Bhattacharjee, Sushil, Kotwal, Ketan, Clivaz, Guillaume, Marcel, Sébastien
Current finger-vein or palm-vein recognition systems usually require direct contact of the subject with the apparatus. This can be problematic in environments where hygiene is of primary importance. In this work we present a contactless vascular biom
Externí odkaz:
http://arxiv.org/abs/2404.09376
Autor:
Shahreza, Hatef Otroshi, Ecabert, Christophe, George, Anjith, Unnervik, Alexander, Marcel, Sébastien, Di Domenico, Nicolò, Borghi, Guido, Maltoni, Davide, Boutros, Fadi, Vogel, Julia, Damer, Naser, Sánchez-Pérez, Ángela, EnriqueMas-Candela, Calvo-Zaragoza, Jorge, Biesseck, Bernardo, Vidal, Pedro, Granada, Roger, Menotti, David, DeAndres-Tame, Ivan, La Cava, Simone Maurizio, Concas, Sara, Melzi, Pietro, Tolosana, Ruben, Vera-Rodriguez, Ruben, Perelli, Gianpaolo, Orrù, Giulia, Marcialis, Gian Luca, Fierrez, Julian
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 syn
Externí odkaz:
http://arxiv.org/abs/2404.04580