Sandip Purnapatra, Nic Smalt, Keivan Bahmani, Priyanka Das, David Yambay, A. Mohammadi, Anjith George, T. Bourlai, S. Marcel, S. Schuckers, Meiling Fang, N. Damer, F. Boutros, Arjan Kuijper, Alperen Kantarci, Basar Demir, Zafer Yildiz, Zabi Ghafoory, Hasan Dertli, H. K. Ekenel, Son Vu, V. Christophides, Liang Dashuang, Zhang Guanghao, Hao Zhanlong, Liu Junfu, Jin Yufeng, Samo Liu, Samuel Huang, Salieri Kuei, Jag Mohan Singh, Raghavendra Ramachandra
{"title":"Face Liveness Detection Competition (LivDet-Face) - 2021","authors":"Sandip Purnapatra, Nic Smalt, Keivan Bahmani, Priyanka Das, David Yambay, A. Mohammadi, Anjith George, T. Bourlai, S. Marcel, S. Schuckers, Meiling Fang, N. Damer, F. Boutros, Arjan Kuijper, Alperen Kantarci, Basar Demir, Zafer Yildiz, Zabi Ghafoory, Hasan Dertli, H. K. Ekenel, Son Vu, V. Christophides, Liang Dashuang, Zhang Guanghao, Hao Zhanlong, Liu Junfu, Jin Yufeng, Samo Liu, Samuel Huang, Salieri Kuei, Jag Mohan Singh, Raghavendra Ramachandra","doi":"10.1109/IJCB52358.2021.9484359","DOIUrl":null,"url":null,"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.","PeriodicalId":175984,"journal":{"name":"2021 IEEE International Joint Conference on Biometrics (IJCB)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Joint Conference on Biometrics (IJCB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCB52358.2021.9484359","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
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.
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