Neural Font Rendering

TL;DR

This paper introduces a neural network architecture designed to rasterize fonts at multiple sizes, facilitating easier and more accessible font creation and manipulation using deep learning techniques.

Contribution

The work presents a novel neural network architecture specifically tailored for multi-scale font rasterization, addressing a gap in deep learning applications for font design.

Findings

Effective multi-scale font rasterization demonstrated

Potential for improved font creation workflows

Supports artistic manipulation of fonts using deep learning

Abstract

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.