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ABSTRACT
We present the 2016 ChaLearn Looking at People and Faces of the World Challenge and Workshop, which ran three competitions on the common theme of face analysis from still images. The first one, Looking at People, addressed age estimation, while the second and third competitions, Faces of the World, addressed accessory classification and smile and gender classification, respectively. We present two crowd-sourcing methodologies used to collect manual annotations. A custom-build application was used to collect and label data about the apparent age of people (as opposed to the real age). For the Faces of the World data, the citizen-science Zooniverse platform was used. This paper summarizes the three challenges and the data used, as well as the results achieved by the participants of the competitions. Details of the ChaLearn LAP FotW competitions can be found at http://gesture.chalearn.org.
INDEX TERMS
Estimation, Databases, Face detection, Conferences, Data models, Face recognition
CITATION
Sergio Escalera, Mercedes Torres Torres, Brais Martinez, Xavier Baro, Hugo Jair Escalante, Isabelle Guyon, Georgios Tzimiropoulos, Ciprian Corneanu, Marc Oliu, Mohammad Ali Bagheri, Michel Valstar, "ChaLearn Looking at People and Faces of the World: Face AnalysisWorkshop and Challenge 2016", 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), vol. 00, no. , pp. 706-713, 2016, doi:10.1109/CVPRW.2016.93
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