Collaborative Comic Generation: Integrating Visual Narrative Theories with AI Models for Enhanced Creativity

Yi-Chun Chen; Arnav Jhala

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arXiv · 2409.17263

Collaborative Comic Generation: Integrating Visual Narrative Theories with AI Models for Enhanced Creativity

Yi-Chun Chen·Arnav Jhala

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Abstract

This study presents a theory-inspired visual narrative generative system that integrates conceptual principles-comic authoring idioms-with generative and language models to enhance the comic creation process. Our system combines human creativity with AI models to support parts of the generative process, providing a collaborative platform for creating comic content. These comic-authoring idioms, derived from prior human-created image sequences, serve as guidelines for crafting and refining storytelling. The system translates these principles into system layers that facilitate comic creation through sequential decision-making, addressing narrative elements such as panel composition, story tension changes, and panel transitions. Key contributions include integrating machine learning models into the human-AI cooperative comic generation process, deploying abstract narrative theories into AI-driven comic creation, and a customizable tool for narrative-driven image sequences. This approach improves narrative elements in generated image sequences and engages human creativity in an AI-generative process of comics. We open-source the code at https://github.com/RimiChen/Collaborative_Comic_Generation.

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Yi-Chun Chen, Arnav Jhala. 2024-09-25. Collaborative Comic Generation: Integrating Visual Narrative Theories with AI Models for Enhanced Creativity. https://arxiv.org/abs/2409.17263

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