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Papers, datasets, and resources related to 2D cartoon video research. Contributions welcome.

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Awesome License: MIT Teaser

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Awesome Animation Research

This repository provides a curated collection of research for 🎞️hand-drawn animation / 🎞️cartoon videos.

💁‍♀️What You'll Find Here: Anime Video Research. Stuff closely related to hand-drawn animation(cartoon video) that could potentially assist enthusiasts or professionals create animations. e.g. Inbetweening, Colorization, etc.

🤷‍♀️What's Not Included: General Anime Research. i.e. Anime Style Transfer, Anime Image Enhancement, Anime Image generation. If you are interested in general anime research, please refer to this cool repo: 🕶️AwesomeAnimeResearch.


🙇‍♀️Creating animation is time-consuming and often involves arduour manual work. AI tools are changing this landscape. Researchers are coping with animation-specific challenges like inbetweening and frame-to-frame color propagation.

Cartoon research is new, niche, interesting, and we look forward to more researchers, including you, contributing to it.

The repo will keep track of the latest research. Feel free to follow and star ! 🌟

New Papers

🚩【Segmentation】 Fast Leak-Resistant Segmentation for Anime Line Art   |   Icon  
Benjamin Allen, Akinobu Maejima, Ken Anjyo
[Nov.,2024] [SIGGRAPH, 2024]

🚩【Colorization】 Paint Bucket Colorization Using Anime Character Color Design Sheets   |   Icon   Icon   Icon  
Yuekun Dai, Qinyue Li, Shangchen Zhou, Yihang Luo, Chongyi Li, Chen Change Loy
[Oct.,2024] [arXiv, 2024]

🚩【Generation】 MikuDance: Animating Character Art with Mixed Motion Dynamics   |   Icon   Icon  
Jiaxu Zhang, Xianfang Zeng, Xin Chen, Wei Zuo, Gang Yu, Zhigang Tu
[Nov.,2024] [arXiv, 2024]

Datasets

Anita Dataset: An Industrial Animation Dataset   |   Icon   Icon   Icon  
Zhenglin Pan, Yu Zhu
[26 Jun., 2024] [Github Repo, 2024]

Sakuga-42M Dataset: Scaling Up Cartoon Research   |   Icon   Icon   Icon   Icon  
Zhenglin Pan, Yu Zhu, Yuxuan Mu
[13 May., 2024] [arXiv, 2024]

AnimeRun: 2D Animation Visual Correspondence from Open Source 3D Movies   |   Icon   Icon   Icon   Icon   Icon  
Li Siyao, Yuhang Li, Bo Li, Chao Dong, Ziwei Liu, Chen Change Loy
[10 Nov., 2022] [NeurIPS, 2022]

Colorization

Paint Bucket Colorization Using Anime Character Color Design Sheets   |   Icon   Icon   Icon  
Yuekun Dai, Qinyue Li, Shangchen Zhou, Yihang Luo, Chongyi Li, Chen Change Loy
[Oct.,2024] [arXiv, 2024]

LVCD: Reference-based Lineart Video Colorization with Diffusion Models   |   Icon   Icon  
Zhitong Huang, Mohan Zhang, Jing Liao
[19 Sep. 2024] [arXiv, 2024]

Continual few-shot patch-based learning for anime-style colorization   |   Icon  
Akinobu Maejima, Seitaro Shinagawa, Hiroyuki Kubo, Takuya Funatomi, Tatsuo Yotsukura, Satoshi Nakamura & Yasuhiro Mukaigawa
[09 Jul., 2024] [CVM, 2024]

Learning Inclusion Matching for Animation Paint Bucket Colorization   |   Icon   Icon   Icon   Icon   Icon  
Yuekun Dai, Shangchen Zhou, Qinyue Li, Chongyi Li, Chen Change Loy
[2024] [CVPR, 2024]

Coloring anime line art videos with transformation region enhancement network   |   Icon  
Ning Wang, Muyao Niu, Zhi Dou, Zhihui Wang, Zhiyong Wang, Zhaoyan Ming, Bin Liu, Haojie Li
[Sep., 2023] [Elsevier, 2023]

SketchBetween: Video-to-Video Synthesis for Sprite Animation via Sketches   |   Icon   Icon  
Dagmar Lukka Loftsdóttir, Matthew Guzdial
[1 Sep., 2022] [ECCV, 2022]

Animation Line Art Colorization Based on Optical Flow Method   |   Icon  
Yifeng Yu, Jiangbo Qian, Chong Wang, Yihong Dong, Baisong Liu
[27 Aug., 2022] [SSNR, 2022]

The Animation Transformer: Visual Correspondence via Segment Matching   |   Icon   Icon  
Evan Casey, Víctor Pérez, Zhuoru Li, Harry Teitelman, Nick Boyajian, Tim Pulver, Mike Manh, William Grisaitis
[6 Sep., 2021] [arXiv, 2021]

Artist-Guided Semiautomatic Animation Colorization   |   Icon  
Harrish Thasarathan, Mehran Ebrahimi
[22 Jun., 2020] [arXiv, 2020]

Line Art Correlation Matching Feature Transfer Network for Automatic Animation Colorization   |   Icon  
Zhang Qian, Wang Bo, Wen Wei, Li Hai, Liu Jun Hui
[14 Apr., 2020] [arXiv, 2020]

Deep Line Art Video Colorization with a Few References   |   Icon  
Min Shi, Jia-Qi Zhang, Shu-Yu Chen, Lin Gao, Yu-Kun Lai, Fang-Lue Zhang
[24 Mar., 2020] [arXiv, 2020]

Automatic Temporally Coherent Video Colorization   |   Icon   Icon  
Harrish Thasarathan, Kamyar Nazeri, Mehran Ebrahimi

Inbetweening & Interpolation

Skeleton-Driven Inbetweening of Bitmap Character Drawings   |   Icon   Icon  
Kirill Brodt, Mikhail Bessmeltsev
[2024] [SIGGRAPH ASIA, 2024]

Thin-Plate Spline-based Interpolation for Animation Line Inbetweening   |   Icon   Icon  
Tianyi Zhu, Wei Shang, Dongwei Ren, Wangmeng Zuo
[17 Aug., 2024] [arXiv, 2024]

ToonCrafter: Generative Cartoon Interpolation   |   Icon   Icon   Icon  
Jinbo Xing, Hanyuan Liu, Menghan Xia, Yong Zhang, Xintao Wang, Ying Shan, Tien-Tsin Wong
[29 May., 2024] [arxiv, 2024]

Joint Stroke Tracing and Correspondence for 2D Animation   |   Icon   Icon   Icon  
Haoran Mo, Chengying Gao, Ruomei Wang
[9 Apr., 2024] [SIGGRAPH, 2024]

Deep Geometrized Cartoon Line Inbetweening   |   Icon   Icon   Icon   Icon  
Li Siyao, Tianpei Gu, Weiye Xiao, Henghui Ding, Ziwei Liu, Chen Change Loy
[Nov., 2023] [ICCV 2023]

Exploring inbetween charts with trajectory-guided sliders for cutout animation   |   Icon  
T Fukusato, A Maejima, T Igarashi, T Yotsukura
[1 Sep., 2023] [MTA 2023]

Enhanced Deep Animation Video Interpolation   |   Icon  
Wang Shen, Cheng Ming, Wenbo Bao, Guangtao Zhai, Li Chen, Zhiyong Gao
[25 Jun., 2022] [arXiv, 2022]

Improving the Perceptual Quality of 2D Animation Interpolation   |   Icon  
Shuhong Chen, Matthias Zwicker
[24 Nov., 2021] [arXiv, 2021]

Deep Animation Video Interpolation in the Wild   |   Icon   Icon   Icon  
Li Siyao, Shiyu Zhao, Weijiang Yu, Wenxiu Sun, Dimitris N. Metaxas, Chen Change Loy, Ziwei Liu
[6 Apr., 2021] [arXiv, 2021]

Deep Sketch-guided Cartoon Video Inbetweening   |   Icon  
Xiaoyu Li, Bo Zhang, Jing Liao, Pedro V. Sander
[10 Aug., 2020] [arXiv, 2020]

Optical Flow Based Line Drawing Frame Interpolation Using Distance Transform to Support Inbetweenings   |   Icon  
Rei Narita, Keigo Hirakawa, Kiyoharu Aizawa
[26 Aug., 2019] [IEEE, 2019]

DiLight: Digital light table – Inbetweening for 2D animations using guidelines   |   Icon  
Leonardo Carvalho, Ricardo Marroquim, Emilio Vital Brazil
[Jun., 2017] [Elsevier, 2017]

Editing

Re:Draw -- Context Aware Translation as a Controllable Method for Artistic Production   |   Icon  
Joao Liborio Cardoso, Francesco Banterle, Paolo Cignoni, Michael Wimmer
[Jan., 2024] [*TBA 2024]

Sprite-from-Sprite: Cartoon Animation Decomposition with Self-supervised Sprite Estimation   |   Icon   Icon  
Lvmin Zhang, Tien-Tsin Wong, Yuxin Liu
[Nov., 2022] [ACM 2022]

Toonsynth: example-based synthesis of hand-colored cartoon animations   |   Icon  
M Dvorožnák, W Li, VG Kim, D Sýkora
[Jul., 2018] [TOG 2018]

Tracking & Matching

Globally Optimal Toon Tracking   |   Icon  
Haichao Zhu, Xueting Liu, Tien-Tsin Wong, Pheng-Ann Heng
[11 Jul., 2016] [TOG, 2016]

Segmentation

Fast Leak-Resistant Segmentation for Anime Line Art   |   Icon  
Benjamin Allen, Akinobu Maejima, Ken Anjyo
[Nov.,2024] [SIGGRAPH, 2024]

Stereoscopizing Cel Animations   |   Icon  
Xueting Liu, Xiangyu Mao, Xuan Yang, Linling Zhang, Tien-Tsin Wong
[11 Jul., 2016] [ACM, 2013]

3D&3DRotoscoping&3D Assistance

DrawingSpinUp: 3D Animation from Single Character Drawings   |   Icon   Icon   Icon   🤗  
Jie Zhou, Chufeng Xiao, Miu-Ling Lam, Hongbo Fu
[13 Sep. 2024] [arXiv, 2024]

Toon3D: Seeing Cartoons from a New Perspective   |   Icon   Icon   Icon   Icon   🤗  
Ethan Weber, Riley Peterlinz, Rohan Mathur, Frederik Warburg, Alexei A. Efros, Angjoo Kanazawa
[2024] [Arxiv, 2024]

Generative Methods

MikuDance: Animating Character Art with Mixed Motion Dynamics   |   Icon   Icon  
Jiaxu Zhang, Xianfang Zeng, Xin Chen, Wei Zuo, Gang Yu, Zhigang Tu
[Nov.,2024] [arXiv, 2024]

How to Contribute

We encourage animation enthusiasts, researchers, and scholars to contribute to this repository by adding relevant papers, articles, and resources. Your contributions will help build a valuable reference for anyone interested in the art and science of animation.

To contribute, simply fork this repository, make your additions or improvements, and submit a pull request. Please follow the contribution guidelines outlined in the repository's README file.


May Animation Get Better With Us.

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