English

AniDoc: Animation Creation Made Easier

Computer Vision and Pattern Recognition 2025-01-31 v2

Abstract

The production of 2D animation follows an industry-standard workflow, encompassing four essential stages: character design, keyframe animation, in-betweening, and coloring. Our research focuses on reducing the labor costs in the above process by harnessing the potential of increasingly powerful generative AI. Using video diffusion models as the foundation, AniDoc emerges as a video line art colorization tool, which automatically converts sketch sequences into colored animations following the reference character specification. Our model exploits correspondence matching as an explicit guidance, yielding strong robustness to the variations (e.g., posture) between the reference character and each line art frame. In addition, our model could even automate the in-betweening process, such that users can easily create a temporally consistent animation by simply providing a character image as well as the start and end sketches. Our code is available at: https://yihao-meng.github.io/AniDoc_demo.

Keywords

Cite

@article{arxiv.2412.14173,
  title  = {AniDoc: Animation Creation Made Easier},
  author = {Yihao Meng and Hao Ouyang and Hanlin Wang and Qiuyu Wang and Wen Wang and Ka Leong Cheng and Zhiheng Liu and Yujun Shen and Huamin Qu},
  journal= {arXiv preprint arXiv:2412.14173},
  year   = {2025}
}

Comments

Project page and code: https://yihao-meng.github.io/AniDoc_demo

R2 v1 2026-06-28T20:41:00.118Z