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Asian Conference on Computer Vision

ACCV 2016: Computer Vision – ACCV 2016 pp 313–329Cite as

From Face Images and Attributes to Attributes

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10113))

Abstract

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.

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Notes

  1. 1.

    http://mypersonality.org.

  2. 2.

    Disattenuation always leads to equal or better results.

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Acknowledgement

This work was supported by the ETH General Fund (OK) and by a K40 GPU grant from NVidia. We thank Michal Kosinski and David Stillwell for providing the Facebook BIG5 dataset.

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Authors and Affiliations

  1. Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland

    Robert Torfason, Eirikur Agustsson, Rasmus Rothe & Radu Timofte

Authors
  1. Robert Torfason
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  2. Eirikur Agustsson
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  3. Rasmus Rothe
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  4. Radu Timofte
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Corresponding author

Correspondence to Radu Timofte .

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Editors and Affiliations

  1. National Tsing Hua University, Hsinchu, Taiwan

    Shang-Hong Lai

  2. Graz University of Technology, Graz, Austria

    Vincent Lepetit

  3. Drexel University, Philadelphia, Pennsylvania, USA

    Ko Nishino

  4. The University of Tokyo , Tokyo, Japan

    Yoichi Sato

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Torfason, R., Agustsson, E., Rothe, R., Timofte, R. (2017). From Face Images and Attributes to Attributes. In: Lai, SH., Lepetit, V., Nishino, K., Sato, Y. (eds) Computer Vision – ACCV 2016. ACCV 2016. Lecture Notes in Computer Science(), vol 10113. Springer, Cham. https://doi.org/10.1007/978-3-319-54187-7_21

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  • DOI: https://doi.org/10.1007/978-3-319-54187-7_21

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  • Online ISBN: 978-3-319-54187-7

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