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Unconstrained face detection: State of the art baseline and challenges
2015
2015 International Conference on Biometrics (ICB)
A large scale study of the accuracy and efficiency of face detection algorithms on unconstrained face imagery is presented. Nine different face detection algorithms are studied, which are acquired through either government rights, open source, or commercial licensing. The primary data set utilized for analysis is the IAPRA Janus Benchmark A (IJB-A), a recently released unconstrained face detection and recognition dataset which, at the time of this study, contained 67,183 manually localized
doi:10.1109/icb.2015.7139089
dblp:conf/icb/CheneyKJK15
fatcat:hc6iuv3ue5ewdh242suvr2koie