Book Cover Synthesis from the Summary

TL;DR

This paper investigates using AI-driven text-to-image synthesis to generate book covers from summaries, aiming to automate and enhance the design process by capturing the book's theme visually.

Contribution

It introduces a dataset of book summaries and covers, and evaluates multiple text-to-image methods for automatic book cover generation from summaries.

Findings

Effective generation of book covers from summaries demonstrated

Different text-to-image techniques compared and analyzed

Potential for automating book cover design processes

Abstract

The cover is the face of a book and is a point of attraction for the readers. Designing book covers is an essential task in the publishing industry. One of the main challenges in creating a book cover is representing the theme of the book's content in a single image. In this research, we explore ways to produce a book cover using artificial intelligence based on the fact that there exists a relationship between the summary of the book and its cover. Our key motivation is the application of text-to-image synthesis methods to generate images from given text or captions. We explore several existing text-to-image conversion techniques for this purpose and propose an approach to exploit these frameworks for producing book covers from provided summaries. We construct a dataset of English books that contains a large number of samples of summaries of existing books and their cover images. In this paper, we describe our approach to collecting, organizing, and pre-processing the dataset to use it for training models. We apply different text-to-image synthesis techniques to generate book covers from the summary and exhibit the results in this paper.