Outline and Detail: A Semantic-Driven Framework for Layered 2D Character Generation

DOI

2D cartoon-style digital characters represent an important art form in games, animation, and virtual live streaming. However, traditional 2D character creation workflows involve tedious manual layering, complex skeleton rigging, and professional animation skills, posing challenges for independent studios and non-professional users. While existing AI generation technologies can quickly create visual content, they typically produce non-layered, difficult-to-edit composite images that cannot be integrated into current workflows. This paper presents Spiritus, a semantic-driven 2D character generation framework. Unlike existing text-based AI animation workflows, Spiritus integrates mixed text and sketch inputs, achieving character image generation and automatic component segmentation through an open mask library and semantic matching. We validated the system's effectiveness in character generation freedom, character animation quality, and technical barrier reduction through comparative evaluation of user experiment results. Finally, we explored the possibilities of applying generated characters to various workflows and scenarios, including game development, animation production, and interactive illustrations.