2022/11/27 by Daniel Anderson, Anderson, Daniel, Ariel Shamir +3
Computer Science · #Computer Graphics and Visualization Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Handwritten Text Recognition Techniques #Image Processing and 3D Reconstruction
paper · pdf · doi:10.48550/arxiv.2211.14802
openalex publication_date 2022/11/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.