Purnapatra, Sandip ; Smalt, Nic ; Bahmani, Keivan ; Das, Priyanka ; Yambay, David ; Mohammadi, Amir ; George, Anjith ; Bourlai, Thirimachos ; Marcel, Sebastien ; Schuckers, Stephanie ; Fang, Meiling ; Damer, Naser ; Boutros, Fadi ; Kuijper, Arjan ; Kantarci, Alperen ; Demir, Basar ; Yildiz, Zafer ; Ghafoory, Zabi ; Dertli, Hasan ; Ekenel, Hazim Kemal ; Vu, Son ; Christophides, Vassilis ; Dashuang, Liang ; Guanghao, Zhang ; Zhanlong, Hao ; Junfu, Liu ; Yufeng, Jin ; Liu, Samo ; Huang, Samuel ; Kuei, Salieri ; Singh, Jag Mohan ; Ramachandra, Raghavendra (2021)
Face Liveness Detection Competition (LivDet-Face) - 2021.
2021 IEEE International Joint Conference on Biometrics (IJCB). virtual Conference (04.08.2021-07.08.2021)
doi: 10.1109/IJCB52358.2021.9484359
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Liveness Detection (LivDet)-Face is an international competition series open to academia and industry. The competition’s objective is to assess and report state-of-the-art in liveness / Presentation Attack Detection (PAD) for face recognition. Impersonation and presentation of false samples to the sensors can be classified as presentation attacks and the ability for the sensors to detect such attempts is known as PAD. LivDet-Face 2021 * will be the first edition of the face liveness competition. This competition serves as an important benchmark in face presentation attack detection, offering (a) an independent assessment of the current state of the art in face PAD, and (b) a common evaluation protocol, availability of Presentation Attack Instruments (PAI) and live face image dataset through the Biometric Evaluation and Testing (BEAT) platform. The competition can be easily followed by researchers after it is closed, in a platform in which participants can compare their solutions against the LivDet-Face winners.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2021 |
| Autor(en): | Purnapatra, Sandip ; Smalt, Nic ; Bahmani, Keivan ; Das, Priyanka ; Yambay, David ; Mohammadi, Amir ; George, Anjith ; Bourlai, Thirimachos ; Marcel, Sebastien ; Schuckers, Stephanie ; Fang, Meiling ; Damer, Naser ; Boutros, Fadi ; Kuijper, Arjan ; Kantarci, Alperen ; Demir, Basar ; Yildiz, Zafer ; Ghafoory, Zabi ; Dertli, Hasan ; Ekenel, Hazim Kemal ; Vu, Son ; Christophides, Vassilis ; Dashuang, Liang ; Guanghao, Zhang ; Zhanlong, Hao ; Junfu, Liu ; Yufeng, Jin ; Liu, Samo ; Huang, Samuel ; Kuei, Salieri ; Singh, Jag Mohan ; Ramachandra, Raghavendra |
| Art des Eintrags: | Bibliographie |
| Titel: | Face Liveness Detection Competition (LivDet-Face) - 2021 |
| Sprache: | Englisch |
| Publikationsjahr: | 20 Juli 2021 |
| Verlag: | IEEE |
| Veranstaltungstitel: | 2021 IEEE International Joint Conference on Biometrics (IJCB) |
| Veranstaltungsort: | virtual Conference |
| Veranstaltungsdatum: | 04.08.2021-07.08.2021 |
| DOI: | 10.1109/IJCB52358.2021.9484359 |
| Kurzbeschreibung (Abstract): | Liveness Detection (LivDet)-Face is an international competition series open to academia and industry. The competition’s objective is to assess and report state-of-the-art in liveness / Presentation Attack Detection (PAD) for face recognition. Impersonation and presentation of false samples to the sensors can be classified as presentation attacks and the ability for the sensors to detect such attempts is known as PAD. LivDet-Face 2021 * will be the first edition of the face liveness competition. This competition serves as an important benchmark in face presentation attack detection, offering (a) an independent assessment of the current state of the art in face PAD, and (b) a common evaluation protocol, availability of Presentation Attack Instruments (PAI) and live face image dataset through the Biometric Evaluation and Testing (BEAT) platform. The competition can be easily followed by researchers after it is closed, in a platform in which participants can compare their solutions against the LivDet-Face winners. |
| Freie Schlagworte: | Biometrics, Deep learning, Machine learning, Face recognition, Spoofing attacks |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
| Hinterlegungsdatum: | 03 Aug 2021 07:17 |
| Letzte Änderung: | 03 Aug 2021 07:17 |
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