  The topic of facial landmark detection has been widely covered for pictures
of human faces, but it is still a challenge for drawings. Indeed, the
proportions and symmetry of standard human faces are not always used for comics
or mangas. The personal style of the author, the limitation of colors, etc.
makes the landmark detection on faces in drawings a difficult task. Detecting
the landmarks on manga images will be useful to provide new services for easily
editing the character faces, estimating the character emotions, or generating
automatically some animations such as lip or eye movements.
  This paper contains two main contributions: 1) a new landmark annotation
model for manga faces, and 2) a deep learning approach to detect these
landmarks. We use the "Deep Alignment Network", a multi stage architecture
where the first stage makes an initial estimation which gets refined in further
stages. The first results show that the proposed method succeed to accurately
find the landmarks in more than 80% of the cases.
