Learning social relation traits from face images
Refereed conference paper presented and published in conference proceedings


Times Cited
Altmetrics Information
.

Other information
AbstractSocial relation defines the association, e.g., warm, friendliness, and dominance, between two or more people. Motivated by psychological studies, we investigate if such fine grained and high-level relation traits can be characterised and quantified from face images in the wild. To address this challenging problem we propose a deep model that learns a rich face representation to capture gender, expression, head pose, and age-related attributes, and then performs pairwise-face reasoning for relation prediction. To learn from heterogeneous attribute sources, we formulate a new network architecture with a bridging layer to leverage the inherent correspondences among these datasets. It can also cope with missing target attribute labels. Extensive experiments show that our approach is effective for fine-grained social relation learning in images and videos.
All Author(s) ListZhang Z., Luo P., Loy C.-C., Tang X.
Name of Conference15th IEEE International Conference on Computer Vision, ICCV 2015
Start Date of Conference11/12/2015
End Date of Conference18/12/2015
Place of ConferenceSantiago
Country/Region of ConferenceRepublic of Chile
Year2016
Month2
Day17
Volume Number11-18-December-2015
Pages3631 - 3639
ISBN9781467383912
ISSN1550-5499
LanguagesEnglish-United Kingdom

Last updated on 2020-27-06 at 00:54