Autor:	Anderson, Daniel, Shamir, Ariel, Fried, Ohad
Rok vydání:	2022
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	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.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2211.14802 Zobrazit plný text záznamu View this record from Arxiv