- Conference Paper
Rights / licenseIn Copyright - Non-Commercial Use Permitted
The face is an important part of the identity of a person. Numerous applications benefit from the recent advances in prediction of face attributes, including biometrics (like age, gender, ethnicity) and accessories (eyeglasses, hat). We study the attributes’ relations to other attributes and to face images and propose prediction models for them. We show that handcrafted features can be as good as deep features, that the attributes themselves are powerful enough to predict other attributes and that clustering the samples according to their attributes can mitigate the training complexity for deep learning. We set new state-of-the-art results on two of the largest datasets to date, CelebA and Facebook BIG5, by predicting attributes either from face images, from other attributes, or from both face and other attributes. Particularly, on Facebook dataset, we show that we can accurately predict personality traits (BIG5) from tens of ‘likes’ or from only a profile picture and a couple of ‘likes’ comparing positively to human reference. Show more
Book titleComputer Vision – ACCV 2016
Journal / seriesLecture Notes in Computer Science
Pages / Article No.
SubjectFACE (ANATOMY AND PHYSIOLOGY); COMPUTER VISION + SCENE UNDERSTANDING (ARTIFICIAL INTELLIGENCE); GESICHT (ANATOMIE UND PHYSIOLOGIE); COMPUTERVISION (KÜNSTLICHE INTELLIGENZ); PERSONENIDENTIFIZIERUNG (INFORMATIONSTHEORIE); PERSONAL IDENTITY VERIFICATION (INFORMATION THEORY)
Organisational unit02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.
03514 - Van Gool, Luc / Van Gool, Luc
MoreShow all metadata