# Comicolorization: Semi-Automatic Manga Colorization

arXiv: https://arxiv.org/abs/1706.06759 · HTML: https://mlsanity.com/paper/1706.06759/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jun 2017.

## Built on by (most cited first, 19 of 19)

- [PaletteNeRF: Palette-based Appearance Editing of Neural Radiance Fields](https://mlsanity.com/paper/2212.10699/) (2022)
- [AniDoc: Animation Creation Made Easier](https://mlsanity.com/paper/2412.14173/) (2024)
- [AnimeDiffusion: Anime Face Line Drawing Colorization via Diffusion Models](https://mlsanity.com/paper/2303.11137/) (2023)
- [SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution](https://mlsanity.com/paper/2201.04364/) (2022)
- [ColorizeDiffusion: Adjustable Sketch Colorization with Reference Image and Text](https://mlsanity.com/paper/2401.01456/) (2024)
- [One missing piece in Vision and Language: A Survey on Comics Understanding](https://mlsanity.com/paper/2409.09502/) (2024)
- [Focusing on Persons: Colorizing Old Images Learning from Modern Historical Movies](https://mlsanity.com/paper/2108.06515/) (2021)
- [ColorFlow: Retrieval-Augmented Image Sequence Colorization](https://mlsanity.com/paper/2412.11815/) (2024)
- [Cobra: Efficient Line Art COlorization with BRoAder References](https://mlsanity.com/paper/2504.12240/) (2025)
- [Attention-Aware Anime Line Drawing Colorization](https://mlsanity.com/paper/2212.10988/) (2022)
- [Improving Sketch Colorization using Adversarial Segmentation Consistency](https://mlsanity.com/paper/2301.08590/) (2023)
- [Adversarial Segmentation Loss for Sketch Colorization](https://mlsanity.com/paper/2102.06192/) (2021)
- [Generative Probabilistic Image Colorization](https://mlsanity.com/paper/2109.14518/) (2021)
- [DACoN: DINO for Anime Paint Bucket Colorization with Any Number of Reference Images](https://mlsanity.com/paper/2509.14685/) (2025)
- [SketchDeco: Training-Free Latent Composition for Precise Sketch Colourisation](https://mlsanity.com/paper/2405.18716/) (2024)
- [Computer-aided Colorization State-of-the-science: A Survey](https://mlsanity.com/paper/2410.02288/) (2024)
- [SSIMBaD: Sigma Scaling with SSIM-Guided Balanced Diffusion for AnimeFace Colorization](https://mlsanity.com/paper/2506.04283/) (2025)
- [Inference-time Trajectory Optimization for Structure-Preserving Manga Image Editing](https://mlsanity.com/paper/2603.27790/) (2026)
- [Studying Comics at Scale with Artificial Intelligence: The PAGE Framework and Three Studies of American Comics and Japanese Manga](https://mlsanity.com/paper/2610.13840/) (2026)

## Abstract (arXiv)

We developed "Comicolorization", a semi-automatic colorization system for manga images. Given a monochrome manga and reference images as inputs, our system generates a plausible color version of the manga. This is the first work to address the colorization of an entire manga title (a set of manga pages). Our method colorizes a whole page (not a single panel) semi-automatically, with the same color for the same character across multiple panels. To colorize the target character by the color from the reference image, we extract a color feature from the reference and feed it to the colorization network to help the colorization. Our approach employs adversarial loss to encourage the effect of the color features. Optionally, our tool allows users to revise the colorization result interactively. By feeding the color features to our deep colorization network, we accomplish colorization of the entire manga using the desired colors for each panel.