Word-As-Image for Semantic Typography

Iluz, Shir; Vinker, Yael; Hertz, Amir; Berio, Daniel; Cohen-Or, Daniel and Shamir, Ariel. 2023. Word-As-Image for Semantic Typography. ACM Transactions on Graphics, 42(4), 151. ISSN 0730-0301 [Article]

2303.01818.pdf - Accepted Version

Download (6MB) | Preview

Abstract or Description

A word-as-image is a semantic typography technique where a word illustration presents a visualization of the meaning of the word, while also preserving its readability. We present a method to create word-as-image illustrations automatically. This task is highly challenging as it requires semantic understanding of the word and a creative idea of where and how to depict these semantics in a visually pleasing and legible manner. We rely on the remarkable ability of recent large pretrained language-vision models to distill textual concepts visually. We target simple, concise, black-and-white designs that convey the semantics clearly. We deliberately do not change the color or texture of the letters and do not use embellishments. Our method optimizes the outline of each letter to convey the desired concept, guided by a pretrained Stable Diffusion model. We incorporate additional loss terms to ensure the legibility of the text and the preservation of the style of the font. We show high quality and engaging results on numerous examples and compare to alternative techniques. Code and demo will be available at our project page.

Item Type:


Identification Number (DOI):


Additional Information:

"© 2023 Copyright held by the owner/author(s). This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record is available at, https://doi.org/10.1145/3592123."


semantic typography, SVG, fonts, stable diffusion

Departments, Centres and Research Units:

Computing > Goldsmiths Digital Studios


26 July 2023Published Online
August 2023Published

Item ID:


Date Deposited:

18 Sep 2023 08:29

Last Modified:

19 Sep 2023 08:57

Peer Reviewed:

Yes, this version has been peer-reviewed.



View statistics for this item...

Edit Record Edit Record (login required)