ToonComposer：通过生成式后关键帧技术简化卡通制作流程

ToonComposer: Streamlining Cartoon Production with Generative Post-Keyframing

August 14, 2025

作者: Lingen Li, Guangzhi Wang, Zhaoyang Zhang, Yaowei Li, Xiaoyu Li, Qi Dou, Jinwei Gu, Tianfan Xue, Ying Shan

cs.AI

摘要

传统动画与动漫制作包含关键帧绘制、中间帧补全及上色等环节，这些步骤往往需要大量人工投入。尽管人工智能领域近期取得了显著进展，现有方法通常将这些环节分开处理，导致误差累积和画面瑕疵。例如，中间帧补全技术难以应对大幅度的动作变化，而上色方法则需依赖密集的逐帧线稿。为解决这些问题，我们推出了ToonComposer，一种将中间帧补全与上色统一于关键帧后处理阶段的生成模型。ToonComposer采用稀疏线稿注入机制，通过关键帧线稿实现精确控制。此外，它结合了卡通适配方法，利用空间低秩适配器将现代视频基础模型定制化应用于卡通领域，同时保持其时间先验不变。仅需一幅线稿及一帧彩色参考画面，ToonComposer便能出色处理稀疏输入，同时支持在任意时间点插入多幅线稿以实现更精准的动作控制。这种双重能力不仅减轻了人工负担，还提升了创作灵活性，在实际场景中为艺术家赋能。为评估模型性能，我们进一步构建了PKBench基准测试集，其中包含模拟真实应用场景的手绘线稿。评估结果表明，ToonComposer在视觉质量、动作一致性及制作效率上均优于现有方法，为AI辅助动画制作提供了更优质、更灵活的解决方案。

English

Traditional cartoon and anime production involves keyframing, inbetweening, and colorization stages, which require intensive manual effort. Despite recent advances in AI, existing methods often handle these stages separately, leading to error accumulation and artifacts. For instance, inbetweening approaches struggle with large motions, while colorization methods require dense per-frame sketches. To address this, we introduce ToonComposer, a generative model that unifies inbetweening and colorization into a single post-keyframing stage. ToonComposer employs a sparse sketch injection mechanism to provide precise control using keyframe sketches. Additionally, it uses a cartoon adaptation method with the spatial low-rank adapter to tailor a modern video foundation model to the cartoon domain while keeping its temporal prior intact. Requiring as few as a single sketch and a colored reference frame, ToonComposer excels with sparse inputs, while also supporting multiple sketches at any temporal location for more precise motion control. This dual capability reduces manual workload and improves flexibility, empowering artists in real-world scenarios. To evaluate our model, we further created PKBench, a benchmark featuring human-drawn sketches that simulate real-world use cases. Our evaluation demonstrates that ToonComposer outperforms existing methods in visual quality, motion consistency, and production efficiency, offering a superior and more flexible solution for AI-assisted cartoon production.