  Multi-face alignment aims to identify geometry structures of multiple faces
in an image, and its performance is essential for the many practical tasks,
such as face recognition, face tracking, and face animation. In this work, we
present a fast bottom-up multi-face alignment approach, which can
simultaneously localize multi-person facial landmarks with high precision.In
more detail, our bottom-up architecture maps the landmarks to the
high-dimensional space with which landmarks of all faces are represented. By
clustering the features belonging to the same face, our approach can align the
multi-person facial landmarks synchronously.Extensive experiments show that our
method can achieve high performance in the multi-face landmark alignment task
while our model is extremely fast. Moreover, we propose a new multi-face
dataset to compare the speed and precision of bottom-up face alignment method
with top-down methods. Our dataset is publicly available at
https://github.com/AISAResearch/FoxNet
