Word-As-Image for Semantic Typographyhttps://wordasimage.github.io/Word-As-Image-Page/
The article presents a method for creating word-as-image illustrations automatically, which involves creating a visualization of the meaning of a word while preserving its readability. The method relies on large pretrained language-vision models to distill textual concepts visually and optimize the outline of each letter to convey the desired concept, guided by a pretrained Stable Diffusion model. The approach uses a differentiable rasterizer and additional loss terms to ensure the legibility of the text and the preservation of the style of the font. The method can handle a large variety of semantic concepts and use any font while preserving the legibility of the text and the font's style. The article provides a detailed explanation of how the method works, including the optimization of parameters for each letter and the use of additional loss functions to preserve the original letter's shape and ensure legibility.