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
翻译:传统的赛璐珞动画制作流程包含多个关键步骤,如故事板绘制、布局设计、关键帧动画、中间帧生成与上色,这些步骤需要大量的人工投入、专业技术知识以及显著的时间成本。这些挑战历来制约着赛璐珞动画制作的效率与可扩展性。生成式人工智能的兴起,包括大语言模型、多模态模型和扩散模型,通过自动化中间帧生成、上色及故事板创建等任务,提供了创新的解决方案。本综述探讨了生成式人工智能的整合如何通过降低技术门槛、借助AniDoc、ToonCrafter和AniSora等工具扩大创作者的参与范围,并使艺术家能更专注于创意表达与艺术创新,从而革新传统动画工作流程。尽管潜力巨大,但视觉一致性、风格连贯性及伦理考量等挑战依然存在。此外,本文还探讨了人工智能辅助动画的未来发展方向与进展。如需进一步探索及相关资源,请访问我们的GitHub仓库:https://github.com/yunlong10/Awesome-AI4Animation