Facial landmark localization is a very crucial step in numerous face related
applications, such as face recognition, facial pose estimation, face image
synthesis, etc. However, previous competitions on facial landmark localization
(i.e., the 300-W, 300-VW and Menpo challenges) aim to predict 68-point
landmarks, which are incompetent to depict the structure of facial components.
In order to overcome this problem, we construct a challenging dataset, named
JD-landmark. Each image is manually annotated with 106-point landmarks. This
dataset covers large variations on pose and expression, which brings a lot of
difficulties to predict accurate landmarks. We hold a 106-point facial landmark
localization competition1 on this dataset in conjunction with IEEE
International Conference on Multimedia and Expo (ICME) 2019. The purpose of
this competition is to discover effective and robust facial landmark
localization approaches.

本文介绍了一个面部标志定位数据集 JD-landmark，图像中的面部区域用 106 个标志进行了手动注释。通过基于该数据集的挑战赛验证了许多有效且鲁棒的面部标志定位方法。