Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Xunqiang Tao"'
Publikováno v:
PLoS ONE, Vol 7, Iss 4, p e35704 (2012)
Fingerprint recognition with identical twins is a challenging task due to the closest genetics-based relationship existing in the identical twins. Several pioneers have analyzed the similarity between twins' fingerprints. In this work we continue to
Externí odkaz:
https://doaj.org/article/37ef254b44a44b3580c7a2e736e53406
Autor:
Wei Chen, Han Huang, Xin Tong, Zhen Xu, Huaibo Liu, Shenqi Lai, Xuefeng Su, Peipei Li, Xunqiang Tao, Ziye Tong, Yinglu Liu, Yandong Guo, Xiangyu Zhu, Zhenan Sun, Duomin Wang, Hailin Shi, Zhenhua Chai
Publikováno v:
Pattern Recognition. ICPR International Workshops and Challenges ISBN: 9783030687922
ICPR Workshops (8)
ICPR Workshops (8)
Facial landmark localization has been applied to numerous face related applications, such as face recognition and face image synthesis. It is a very crucial step for achieving high performance in these applications. We host the \(2^\mathrm{nd}\) 106-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7842c2674b1b77e06ac7290e88e4291b
https://doi.org/10.1007/978-3-030-68793-9_25
https://doi.org/10.1007/978-3-030-68793-9_25
Publikováno v:
ICCV
Recently, large-margin softmax loss methods, such as angular softmax loss (SphereFace), large margin cosine loss (CosFace), and additive angular margin loss (ArcFace), have demonstrated impressive performance on deep face recognition. These methods i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::80f68578c6bcd57274e7d084bd253037
https://doi.org/10.1109/iccv.2019.01015
https://doi.org/10.1109/iccv.2019.01015
Publikováno v:
ICCV
Racial bias is an important issue in biometric, but has not been thoroughly studied in deep face recognition. In this paper, we first contribute a dedicated dataset called Racial Faces in-the-Wild (RFW) database, on which we firmly validated the raci
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::859668bd408a954dfd7c58ff8c3465b0
https://doi.org/10.1109/iccv.2019.00078
https://doi.org/10.1109/iccv.2019.00078
Publikováno v:
CVPR Workshops
In this paper, we propose a new face alignment method, called adaptive pose alignment (APA) which can greatly reduce the intra-class difference and correct the noise caused by the traditional method in the alignment process, especially in unconstrain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cce3f2613887b72592aec4b0dd722cb1
https://doi.org/10.1109/cvprw.2019.00032
https://doi.org/10.1109/cvprw.2019.00032
Publikováno v:
CVPR
Large-scale face datasets usually exhibit a massive number of classes, a long-tailed distribution, and severe label noise, which undoubtedly aggravate the difficulty of training. In this paper, we propose a training strategy that treats the head data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2dbe132094856ebe18790cae725055a0
https://doi.org/10.1109/cvpr.2019.00800
https://doi.org/10.1109/cvpr.2019.00800
Publikováno v:
Pattern Recognition Letters. 33:1411-1421
Traditional minutiae-based matching algorithms are challenged by the probability that minutiae from different regions of different fingers may not be well matched, and hence lead to erroneous matching results. In this paper we introduce a novel featu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42f8312ff9ac2bd327bdca0a125dea13
https://doi.org/10.1016/j.patrec.2012.03.007
https://doi.org/10.1016/j.patrec.2012.03.007
Publikováno v:
Journal of Network and Computer Applications. 33:207-220
Fuzzy vault is a practical and promising scheme, which can protect biometric templates and perform secure key management simultaneously. Alignment of the template biometric sample and the query one in the encrypted domain remains a challenging task.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::649746c88c91e0a723cd7316ac6cd19b
https://doi.org/10.1016/j.jnca.2009.12.003
https://doi.org/10.1016/j.jnca.2009.12.003
Publikováno v:
Journal of Network and Computer Applications. 33:258-267
Extracting and fusing discriminative features in fingerprint matching, especially in distorted fingerprint matching, is a challenging task. In this paper, we introduce two novel features to deal with nonlinear distortion in fingerprints. One is finge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d3b5d83f8c77131b714c7b9cea6b987
https://doi.org/10.1016/j.jnca.2009.12.007
https://doi.org/10.1016/j.jnca.2009.12.007