Manga Colorization¶
Manga & Comics
Open Source¶
-
GapFill Discovered by AI
2026
An interactive, deep-learning-assisted tool designed for professional anime and manga colorists to automatically detect and fill small unpainted gaps left by paint bucket tools.
animecolorizationflat-colormanga -
Enhancing Reference-based Sketch Colorization via Separating Reference Representations Discovered by AI
2025
A reference-based sketch colorization framework that decomposes the colorization process into modular stages using distinct reference representations, including embedding guidance, style modification, and low-level transfer, to eliminate spatial artifacts and enhance visual quality.
colorizationdiffusionsketch -
Image Referenced Sketch Colorization Based on Animation Creation Workflow Discovered by AI
2025
A diffusion-based sketch colorization framework inspired by real-world animation workflows, utilizing a sketch image as spatial reference and an RGB image as color reference to avoid artifacts and manual operations.
colorizationdiffusionreference-guidedsketch -
ColorComic Discovered by AI
2024
An open-source tool for colorizing black-and-white manga and manhwa PDFs locally using deep learning, supporting both automatic colorization and reference-guided modes with sparse color hints.
colorizationlocalmangapdf -
ColorFlow Discovered by AI
2024
A three-stage diffusion-based framework designed for automatic black-and-white image sequence colorization, such as cartoon or comic series. It utilizes a retrieval-augmented mechanism to preserve character and object identity consistency across multiple frames.
colorizationcomicdiffusionidentity-consistency -
Adeleine: Automatic Line Art Colorization with Hints Discovered by AI
2023
Adeleine is an open-source tool for automatic and semi-automatic line art colorization. It supports colorizing black-and-white drawings with or without user-provided color hints, leveraging deep learning models to streamline the illustration workflow.
colorizationdeep-learninglineartmanga-colorization -
Example-Based Manga Colorization Discovered by AI
2023
An exemplar-based manga colorization framework that uses a conditional generative adversarial network (cGAN) to transfer color features from a reference image to a grayscale manga or sketch while preserving structural details.
cgancolorizationmangareference-based -
Example-Based Manga Colorization cGAN Discovered by AI
2023
An example-based manga colorization system using a conditional Generative Adversarial Network (cGAN) architecture. It extracts color embeddings from a reference image using a pretrained VGG19 network and MLP, transferring consistent colors to grayscale manga panels or sketches.
cganmanga-colorizationreference-basedsketch -
inkn'hue: Enhancing Manga Colorization from Multiple Priors with Alignment Multi-Encoder VAE Discovered by AI
2023
A manga colorization framework that utilizes a multi-encoder VAE to align shading and coloring priors, enabling high-quality colorization guided by user-inputted color hints or reference images.
colorizationmanga-colorizationvae -
Manga Colorization v2 Discovered by AI
2023
An open-source automatic manga page colorization tool based on a two-stage approach that maps black-and-white manga images into a latent space for robust color distribution and refinement.
colorizationganmanga-colorization -
Eliminating Gradient Conflict in Reference-based Line-art Colorization Discovered by AI
2022
Introduces a self-guided attention (SGA) mechanism and gradient conflict elimination strategy to improve reference-based line-art colorization, addressing the optimization difficulties of attention models under multi-source supervision.
attentioncolorizationeccvlineart -
Painting Style-Aware Manga Colorization Based on Generative Adversarial Networks Discovered by AI
2021
A generative adversarial network-based manga colorization method designed to maintain painting style consistency across consecutive comic panels.
ganmanga-colorizationstyle-consistency -
Tag2Pix: Line Art Colorization Using Text Tag With SECat and Changing Loss Discovered by AI
2019
Tag2Pix is a generative adversarial network (GAN) framework for line art colorization that takes a grayscale line art and text tags as input to produce high-quality colored illustrations. It utilizes a semantic extraction network and a custom generator with SECat (Squeeze-and-Excitation Color Attention) to guide the colorization process based on user-defined tags.
colorizationganlineartmanga-colorization -
cGAN-based Manga Colorization Using a Single Training Image Discovered by AI
2017
A manga colorization method based on conditional Generative Adversarial Networks (cGAN) that can be trained using a single colorized manga image. The model addresses the scarcity of training data by learning to colorize black-and-white manga panels without relying on grayscale values.
adversarialcgancolorizationmanga -
Comicolorization: Semi-Automatic Manga Colorization Discovered by AI
2017
A semi-automatic colorization system for entire manga titles that ensures character color consistency across multiple panels using reference images.
color-consistencymanga-colorizationsemi-automatic
Proprietary / Industry Tools¶
-
Watashi Colorizer Discovered by AI
2026
An AI-powered proprietary tool designed for bulk manga, manhwa, and webtoon chapter colorization, featuring consistent character palettes, smart panel splitting, and multi-language translation.
colorizationmangatranslationwebtoon -
MangaColorizer Discovered by AI
2025
An online AI-powered manga colorization and translation tool built specifically for manga and comics. It utilizes specialized image models to add rich, consistent colors while preserving original line art and panel layouts, and offers automated translation into over 15 languages.
colorizationtranslationweb-app -
Morph AI Manga Colorizer Discovered by AI
2025
A web-based automatic manga and comic colorizer that transforms black-and-white line art and sketches into colored artwork. It supports reference-guided colorization to maintain character and lighting consistency across panels and exports high-resolution results up to 8K.
colorizationreference-guidedweb-app -
Toona Colorizer Discovered by AI
2025
An automatic AI manga colorizer that allows users to colorize black-and-white manga pages with a single click or guide the process using point-based color hints. It also includes built-in manga-optimized upscaling and editing tools.
color-hintscolorizationweb-app -
VividManga Discovered by AI
2024
An AI-powered online manga colorization platform designed for pages, panels, and line art. It features consistent character color palette definition, sequential chapter awareness to reduce page-to-page drift, and intelligent text isolation to protect speech bubbles and sound effects.
ai-coloringmanga-colorizationonline-tool -
Kyukoma AI Manga Colorizer Discovered by AI
A web-based AI colorization tool designed for manga panels, allowing creators to apply interactive color hints while preserving line art integrity.
color-hintsmanga-colorizationmanga-panelweb-tool
