  Font design is now still considered as an exclusive privilege of professional
designers, whose creativity is not possessed by existing software systems.
Nevertheless, we also notice that most commercial font products are in fact
manually designed by following specific requirements on some attributes of
glyphs, such as italic, serif, cursive, width, angularity, etc. Inspired by
this fact, we propose a novel model, Attribute2Font, to automatically create
fonts by synthesizing visually-pleasing glyph images according to
user-specified attributes and their corresponding values. To the best of our
knowledge, our model is the first one in the literature which is capable of
generating glyph images in new font styles, instead of retrieving existing
fonts, according to given values of specified font attributes. Specifically,
Attribute2Font is trained to perform font style transfer between any two fonts
conditioned on their attribute values. After training, our model can generate
glyph images in accordance with an arbitrary set of font attribute values.
Furthermore, a novel unit named Attribute Attention Module is designed to make
those generated glyph images better embody the prominent font attributes.
Considering that the annotations of font attribute values are extremely
expensive to obtain, a semi-supervised learning scheme is also introduced to
exploit a large number of unlabeled fonts. Experimental results demonstrate
that our model achieves impressive performance on many tasks, such as creating
glyph images in new font styles, editing existing fonts, interpolation among
different fonts, etc.
