Fang, Meiling ; Huber, Marco ; Fierrez, Julian ; Ramachandra, Raghavendra ; Damer, Naser ; Alkhaddour, Alhasan ; Kasantcev, Maksim ; Pryadchenko, Vasiliy ; Yang, Ziyuan ; Huangfu, Huijie ; Chen, Yingyu ; Zhang, Yi ; Pan, Yuchen ; Jiang, Junjun ; Liu, Xianming ; Sun, Xianyun ; Wang, Caiyong ; Liu, Xingyu ; Chang, Zhaohua ; Zhao, Guangzhe ; Tapia, Juan ; Gonzalez-Soler, Lazaro ; Aravena, Carlos ; Schulz, Daniel (2023)
SynFacePAD 2023: Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data.
International Joint Conference on Biometrics 2023. Ljubljana, Slovenia (25.-28.9.2023)
doi: 10.1109/IJCB57857.2023.10449130
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
This paper presents a summary of the Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data (SynFacePAD 2023) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition attracted a total of 8 participating teams with valid submissions from academia and industry. The competition aimed to motivate and attract solutions that target detecting face presentation attacks while considering synthetic-based training data motivated by privacy, legal and ethical concerns associated with personal data. To achieve that, the training data used by the participants was limited to synthetic data provided by the organizers. The submitted solutions presented innovations and novel approaches that led to outperforming the considered baseline in the investigated benchmarks.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Fang, Meiling ; Huber, Marco ; Fierrez, Julian ; Ramachandra, Raghavendra ; Damer, Naser ; Alkhaddour, Alhasan ; Kasantcev, Maksim ; Pryadchenko, Vasiliy ; Yang, Ziyuan ; Huangfu, Huijie ; Chen, Yingyu ; Zhang, Yi ; Pan, Yuchen ; Jiang, Junjun ; Liu, Xianming ; Sun, Xianyun ; Wang, Caiyong ; Liu, Xingyu ; Chang, Zhaohua ; Zhao, Guangzhe ; Tapia, Juan ; Gonzalez-Soler, Lazaro ; Aravena, Carlos ; Schulz, Daniel |
| Art des Eintrags: | Bibliographie |
| Titel: | SynFacePAD 2023: Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data |
| Sprache: | Englisch |
| Publikationsjahr: | 29 September 2023 |
| Verlag: | IEEE |
| Buchtitel: | 2023 IEEE International Joint Conference on Biometrics (IJCB) |
| Veranstaltungstitel: | International Joint Conference on Biometrics 2023 |
| Veranstaltungsort: | Ljubljana, Slovenia |
| Veranstaltungsdatum: | 25.-28.9.2023 |
| DOI: | 10.1109/IJCB57857.2023.10449130 |
| Kurzbeschreibung (Abstract): | This paper presents a summary of the Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data (SynFacePAD 2023) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition attracted a total of 8 participating teams with valid submissions from academia and industry. The competition aimed to motivate and attract solutions that target detecting face presentation attacks while considering synthetic-based training data motivated by privacy, legal and ethical concerns associated with personal data. To achieve that, the training data used by the participants was limited to synthetic data provided by the organizers. The submitted solutions presented innovations and novel approaches that led to outperforming the considered baseline in the investigated benchmarks. |
| Freie Schlagworte: | Biometrics, Machine learning, Spoofing attacks, Face recognition, Generative Adversarial Networks (GAN) |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 12 Apr 2024 10:36 |
| Letzte Änderung: | 12 Apr 2024 10:36 |
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