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Neural Font Rendering

2022-11-27 · Daniel Anderson, Ariel Shamir, Ohad Fried

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.

📄 PDF Abstract BibTeX arXiv:2211.14802

Code (1)

andersondaniel/neural-font-rendering 공식 구현 tf

Tasks

Deep Learning

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