Melzi, Pietro ; Tolosana, Ruben ; Vera-Rodriguez, Ruben ; Kim, Minchul ; Rathgeb, Christian ; Liu, Xiaoming ; DeAndres-Tame, Ivan ; Morales, Aythami ; Fierrez, Julian ; Ortega-Garcia, Javier ; Zhao, Weisong ; Zhu, Xiangyu ; Yan, Zheyu ; Zhang, Xiao-Yu ; Wu, Jinlin ; Lei, Zhen ; Tripathi, Suvidha ; Kothari, Mahak ; Zama, Md Haider ; Deb, Debayan ; Biesseck, Bernardo ; Vidal, Pedro ; Granada, Roger ; Fickel, Guilherme ; Führ, Gustavo ; Menotti, David ; Unnervik, Alexander ; George, Anjith ; Ecabert, Christophe ; Shahreza, Hatef Otroshi ; Rahimi, Parsa ; Marcel, Sébastien ; Sarridis, Ioannis ; Koutlis, Christos ; Baltsou, Georgia ; Papadopoulos, Symeon ; Diou, Christos ; Di Domenico, Nicolò ; Borghi, Guido ; Pellegrini, Lorenzo ; Mas-Candela, Enrique ; Sánchez-Pérez, Ángela ; Atzori, Andrea ; Fenu, Gianni ; Boutros, Fadi ; Marras, Mirko ; Damer, Naser
Hrsg.: Institute of Electrical and Electronics Engineers (2024)
FRCSyn Challenge at WACV 2024: Face Recognition Challenge in the Era of Synthetic Data.
Winter Conference on Applications of Computer Vision 2024. Waikoloa, Hawaii, USA (01.01. - 06.01.2024)
doi: 10.1109/WACVW60836.2024.00100
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
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 Recognition Challenge in the Era of Synthetic Data (FRCSyn) organized at WACV 2024. This is the first international challenge aiming to explore the use of synthetic data in face recognition to address existing limitations in the technology. Specifically, the FRCSyn Challenge targets concerns related to data privacy issues, demographic biases, generalization to unseen scenarios, and performance limitations in challenging scenarios, including significant age disparities between enrollment and testing, pose variations, and occlusions. The results achieved in the FRCSyn Challenge, together with the proposed benchmark, contribute significantly to the application of synthetic data to improve face recognition technology.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Melzi, Pietro ; Tolosana, Ruben ; Vera-Rodriguez, Ruben ; Kim, Minchul ; Rathgeb, Christian ; Liu, Xiaoming ; DeAndres-Tame, Ivan ; Morales, Aythami ; Fierrez, Julian ; Ortega-Garcia, Javier ; Zhao, Weisong ; Zhu, Xiangyu ; Yan, Zheyu ; Zhang, Xiao-Yu ; Wu, Jinlin ; Lei, Zhen ; Tripathi, Suvidha ; Kothari, Mahak ; Zama, Md Haider ; Deb, Debayan ; Biesseck, Bernardo ; Vidal, Pedro ; Granada, Roger ; Fickel, Guilherme ; Führ, Gustavo ; Menotti, David ; Unnervik, Alexander ; George, Anjith ; Ecabert, Christophe ; Shahreza, Hatef Otroshi ; Rahimi, Parsa ; Marcel, Sébastien ; Sarridis, Ioannis ; Koutlis, Christos ; Baltsou, Georgia ; Papadopoulos, Symeon ; Diou, Christos ; Di Domenico, Nicolò ; Borghi, Guido ; Pellegrini, Lorenzo ; Mas-Candela, Enrique ; Sánchez-Pérez, Ángela ; Atzori, Andrea ; Fenu, Gianni ; Boutros, Fadi ; Marras, Mirko ; Damer, Naser |
| Art des Eintrags: | Bibliographie |
| Titel: | FRCSyn Challenge at WACV 2024: Face Recognition Challenge in the Era of Synthetic Data |
| Sprache: | Englisch |
| Publikationsjahr: | 2024 |
| Ort: | Piscataway, NJ |
| Verlag: | IEEE |
| Buchtitel: | 2024 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW) |
| Veranstaltungstitel: | Winter Conference on Applications of Computer Vision 2024 |
| Veranstaltungsort: | Waikoloa, Hawaii, USA |
| Veranstaltungsdatum: | 01.01. - 06.01.2024 |
| DOI: | 10.1109/WACVW60836.2024.00100 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | 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 Recognition Challenge in the Era of Synthetic Data (FRCSyn) organized at WACV 2024. This is the first international challenge aiming to explore the use of synthetic data in face recognition to address existing limitations in the technology. Specifically, the FRCSyn Challenge targets concerns related to data privacy issues, demographic biases, generalization to unseen scenarios, and performance limitations in challenging scenarios, including significant age disparities between enrollment and testing, pose variations, and occlusions. The results achieved in the FRCSyn Challenge, together with the proposed benchmark, contribute significantly to the application of synthetic data to improve face recognition technology. |
| Freie Schlagworte: | Biometrics, Face recognition, Image generation, Machine learning, Deep learning |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 17 Mai 2024 08:30 |
| Letzte Änderung: | 03 Jun 2024 06:33 |
| PPN: | 518772853 |
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