Poster Generation Using Stable Diffusion 3 and Autoencoders

Creating posters can feel like a hassle, especially if design isn't your strong suit. It often requires a lot of manual adjustments and artistic decisions, which can be overwhelming. That's where PosterGen steps in—a framework designed to simplify and streamline the process. Using a large-scale visual-textual model, PosterGen can automatically find background images that complement your text. It also employs auto encoders to arrange the text in a visually appealing and easy-to-read way. On top of that, it selects fonts and colors that fit the theme, ensuring everything flows seamlessly. What's even more impressive is that PosterGen learns with very little labeled data by using weakly- and self-supervised methods. In our experiments, we've seen that it not only makes poster creation easier but also outperforms some of the current tools and techniques available.

Publication Details

Journal
REST Journal on Data Analytics and Artificial Intelligence
Published
2025-05-05
DOI
https://doi.org/10.46632/jdaai/4/1/55
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
0.00
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article

Poster Generation Using Stable Diffusion 3 and Autoencoders

REST Journal on Data Analytics and Artificial Intelligence
Topic Modeling
article

Poster Generation Using Stable Diffusion 3 and Autoencoders

article en

Abstract

Creating posters can feel like a hassle, especially if design isn't your strong suit. It often requires a lot of manual adjustments and artistic decisions, which can be overwhelming. That's where PosterGen steps in—a framework designed to simplify and streamline the process. Using a large-scale visual-textual model, PosterGen can automatically find background images that complement your text. It also employs auto encoders to arrange the text in a visually appealing and easy-to-read way. On top of that, it selects fonts and colors that fit the theme, ensuring everything flows seamlessly. What's even more impressive is that PosterGen learns with very little labeled data by using weakly- and self-supervised methods. In our experiments, we've seen that it not only makes poster creation easier but also outperforms some of the current tools and techniques available.

REST Journal on Data Analytics and Artificial IntelligenceVol. 4(1 March 2025)
Openalex Percentile: Top 96%
Topic Modeling
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