Sustained context-aware image generation for the Dungeons & Dragons domain

Abstract

Dungeons & Dragons (D&D) is a fantasy tabletop role-playing game which has become a subculture phenomenon due to its immense popularity. In a D&D adventure images play a major role in guiding the players’ emotions and providing additional information regarding the setting. The proposed research attempts to use text extracted from premade adventure to generate cohesive and contextually accurate images according to the given setting. The core of the proposed methodology involves two strategic components. First, the project seeks to develop an Natural Language Processing (NLP) model capable of deep textual analysis to identify and understand the underlying context and key elements within the D&D text. This model will focus on extracting salient features and narrative cues from the text, which will then be used to generate precise prompts. These prompts are designed to encapsulate the essential elements needed to guide the image generation process, ensuring that the resulting visuals are not only relevant but also enrich the storytelling by aligning closely with the D&D lore. The second component is a comprehensive pipeline that generates consistent images in a zero-shot manner. Additionally, this study proposes the creation of an end-to-end pipeline that not only generates images but also automates the creation of complete D&D adventures. This pipeline will integrate multi-agent workflows, an image generation framework, and NLP techniques to produce a comprehensive suite of adventure materials—including story narratives, gameplay guidelines, gameplay-related tables, contextual images, and maps. This holistic approach is designed to streamline the preparation process for Dungeon Masters, enabling them to deliver richly detailed sessions with less preparation time.