CartoonAlive: Towards Expressive Live2D Modeling from Single Portraits
Chao He, Jianqiang Ren, Jianjing Xiang, Xiejie Shen

TL;DR
CartoonAlive introduces a fast, scalable method to generate expressive Live2D digital humans from a single portrait, leveraging shape basis and facial keypoints for real-time animation.
Contribution
It presents a novel approach that constructs Live2D models from a single image using shape basis and keypoint inference, enabling rapid and accurate digital human creation.
Findings
High-quality Live2D models generated in less than 30 seconds.
Models closely resemble input portraits with expressive facial movements.
Scalable solution for interactive 2D cartoon character creation.
Abstract
With the rapid advancement of large foundation models, AIGC, cloud rendering, and real-time motion capture technologies, digital humans are now capable of achieving synchronized facial expressions and body movements, engaging in intelligent dialogues driven by natural language, and enabling the fast creation of personalized avatars. While current mainstream approaches to digital humans primarily focus on 3D models and 2D video-based representations, interactive 2D cartoon-style digital humans have received relatively less attention. Compared to 3D digital humans that require complex modeling and high rendering costs, and 2D video-based solutions that lack flexibility and real-time interactivity, 2D cartoon-style Live2D models offer a more efficient and expressive alternative. By simulating 3D-like motion through layered segmentation without the need for traditional 3D modeling, Live2D…
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Taxonomy
TopicsHuman Motion and Animation · Computer Graphics and Visualization Techniques · 3D Shape Modeling and Analysis
