ChaLearn Looking at People and Faces of the World: Face AnalysisWorkshop and Challenge 2016

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.

Cite

Text

Escalera et al. "ChaLearn Looking at People and Faces of the World: Face AnalysisWorkshop and Challenge 2016." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2016. doi:10.1109/CVPRW.2016.93

Markdown

[Escalera et al. "ChaLearn Looking at People and Faces of the World: Face AnalysisWorkshop and Challenge 2016." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2016.](https://mlanthology.org/cvprw/2016/escalera2016cvprw-chalearn/) doi:10.1109/CVPRW.2016.93

BibTeX

@inproceedings{escalera2016cvprw-chalearn,
  title     = {{ChaLearn Looking at People and Faces of the World: Face AnalysisWorkshop and Challenge 2016}},
  author    = {Escalera, Sergio and Torres, Mercedes and Martínez, Brais and Baró, Xavier and Escalante, Hugo Jair and Guyon, Isabelle and Tzimiropoulos, Georgios and Corneanu, Ciprian A. and Oliu, Marc and Bagheri, Mohammad Ali and Valstar, Michel F.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2016},
  pages     = {706-713},
  doi       = {10.1109/CVPRW.2016.93},
  url       = {https://mlanthology.org/cvprw/2016/escalera2016cvprw-chalearn/}
}