  Recent advances in deep learning techniques and applications have
revolutionized artistic creation and manipulation in many domains (text,
images, music); however, fonts have not yet been integrated with deep learning
architectures in a manner that supports their multi-scale nature. In this work
we aim to bridge this gap, proposing a network architecture capable of
rasterizing glyphs in multiple sizes, potentially paving the way for easy and
accessible creation and manipulation of fonts.
