Generative AI for Cel-Animation: A Survey

TL;DR

This survey reviews how generative AI models are transforming traditional cel-animation workflows by automating key tasks, reducing manual effort, and increasing accessibility for creators, while also discussing current challenges and future prospects.

Contribution

It provides a comprehensive overview of AI tools and techniques applied to cel-animation, highlighting recent innovations, practical applications, and future research directions.

Findings

GenAI automates inbetweening, coloring, and storyboard creation.

Tools like AniDoc, ToonCrafter, and AniSora enhance accessibility.

Challenges include maintaining visual consistency and ethical issues.

Abstract

Traditional Celluloid (Cel) Animation production pipeline encompasses multiple essential steps, including storyboarding, layout design, keyframe animation, inbetweening, and colorization, which demand substantial manual effort, technical expertise, and significant time investment. These challenges have historically impeded the efficiency and scalability of Cel-Animation production. The rise of generative artificial intelligence (GenAI), encompassing large language models, multimodal models, and diffusion models, offers innovative solutions by automating tasks such as inbetween frame generation, colorization, and storyboard creation. This survey explores how GenAI integration is revolutionizing traditional animation workflows by lowering technical barriers, broadening accessibility for a wider range of creators through tools like AniDoc, ToonCrafter, and AniSora, and enabling artists to focus more on creative expression and artistic innovation. Despite its potential, challenges like visual consistency, stylistic coherence, and ethical considerations persist. Additionally, this paper explores future directions and advancements in AI-assisted animation. For further exploration and resources, please visit our GitHub repository: https://github.com/yunlong10/Awesome-AI4Animation