用生成式AI自动完成手绘动画关键流程，提升效率与创作自由度。
Generative AI for Cel-Animation: A Survey
- 利用大语言模型、多模态与扩散模型自动化补帧、上色与分镜设计
- 通过AniDoc、ToonCrafter等工具降低技术门槛，提升创作效率
- 适合动画初学者、独立创作者及需要快速原型设计的团队
传统手绘动画制作流程包含分镜、布局设计、关键帧绘制、补间动画和上色等多个环节，需大量人工投入、专业技术与时间成本。这些挑战长期制约了动画生产的效率与可扩展性。生成式人工智能（GenAI）——包括大语言模型、多模态模型和扩散模型——为自动化补间帧生成、上色与分镜创建提供了创新解决方案。本综述探讨了GenAI如何通过AniDoc、ToonCrafter、AniSora等工具，重构传统动画工作流，降低技术壁垒，扩大创作者群体，使艺术家能更专注于创意表达与艺术创新。尽管潜力巨大，视觉一致性、风格连贯性及伦理问题仍待解决。本文还展望了未来发展方向与技术演进路径。更多资源请访问我们的GitHub：https://github.com/yunlong10/Awesome-AI4Animation
原文摘要 · Abstract (English)
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
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