{"id":4590,"url":"https://github.com/MarkMoHR/Awesome-Image-Colorization","name":"Awesome-Image-Colorization","description":":books: A collection of Deep Learning based Image Colorization and Video Colorization papers.","projects_count":156,"last_synced_at":"2026-10-08T18:00:28.634Z","repository":{"id":41374457,"uuid":"156939932","full_name":"MarkMoHR/Awesome-Image-Colorization","owner":"MarkMoHR","description":":books: A collection of Deep Learning based Image Colorization and Video Colorization papers.","archived":false,"fork":false,"pushed_at":"2026-08-27T08:51:33.000Z","size":887,"stargazers_count":1164,"open_issues_count":6,"forks_count":111,"subscribers_count":41,"default_branch":"master","last_synced_at":"2026-09-19T05:56:08.897Z","etag":null,"topics":["automatic-colorization","color-palette","color-strokes","color-transfer","colorization","computer-vision","deep-learning","graphics","image-colorization","image-colorization-paper","image-colorization-papers","papers","user-guided","user-interaction"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/MarkMoHR.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"claude":null,"gemini":null,"cursor":null,"copilot":null,"dco":null,"cla":null,"disclosure":null}},"created_at":"2018-11-10T02:27:18.000Z","updated_at":"2026-09-02T07:30:43.000Z","dependencies_parsed_at":"2026-08-21T08:04:11.224Z","dependency_job_id":null,"html_url":"https://github.com/MarkMoHR/Awesome-Image-Colorization","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/MarkMoHR/Awesome-Image-Colorization","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MarkMoHR%2FAwesome-Image-Colorization","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MarkMoHR%2FAwesome-Image-Colorization/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MarkMoHR%2FAwesome-Image-Colorization/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MarkMoHR%2FAwesome-Image-Colorization/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MarkMoHR","download_url":"https://codeload.github.com/MarkMoHR/Awesome-Image-Colorization/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MarkMoHR%2FAwesome-Image-Colorization/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":343170754,"owners_count":38125073,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-10-03T21:59:58.778Z","status":"online","status_checked_at":"2026-10-08T02:00:05.744Z","response_time":97,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"created_at":"2024-01-06T20:24:59.640Z","updated_at":"2026-10-08T18:00:28.635Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["1. Automatic Image Colorization","2. User Guided Image Colorization","3. Techniques of Improving Image Colorization","4. Video Colorization","0. Survey","3. Human-AI Collaborated Colorization System"],"sub_categories":["1.1 Software / Demo","1.2 Papers","2.5 Multi-modal","2.4 Based on language or text","2.1 Based on scribble","2.2 Based on reference image","2.3 Based on palette","2.6 Interactive Colorization","4.1 Automatically","4.2 Based on reference","4.3 Based on scribble","4.4 Based on text","4.0 Survey","4.6 Multimodal","4.5 Based on palette"],"readme":"# Awesome-Image-Colorization\n\n[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\n\n\nA collection of **Deep Learning** based Image Colorization papers and corresponding source code/demo program, including Automatic and User Guided (*i.e.* with User Interaction) colorization, as well as video colorization.\n\n\u003e Feel free to create a PR or an issue.  (Pull Request is preferred)\n\n![examples](https://github.com/MarkMoHR/Awesome-Image-Colorization/blob/master/examples.png)\n\n**Outline**\n\n- [Survey](#0-survey)\n- [Automatic Image Colorization](#1-automatic-image-colorization)\n  - [Software / Demo](#11-software--demo)\n  - [Papers](#12-papers)\n- [User Guided Image Colorization](#2-user-guided-image-colorization)\n  - [Based on scribble](#21-based-on-scribble)\n  - [Based on reference image](#22-based-on-reference-image)\n  - [Based on palette](#23-based-on-palette)\n  - [Based on language(text)](#24-based-on-language-or-text)\n  - [Multi-modal](#25-multi-modal)\n  - [Interactive Colorization](#26-interactive-colorization)\n- [Human-AI Collaborated Colorization System](#3-human-ai-collaborated-colorization-system)\n- [Video Colorization](#4-video-colorization)\n  - [Survey](#40-survey)\n  - [Automatically](#41-automatically)\n  - [Based on reference](#42-based-on-reference)\n  - [Based on scribble](#43-based-on-scribble)\n  - [Based on text](#44-based-on-text)\n  - [Based on palette](#45-based-on-palette)\n  - [Multimodal](#46-multimodal)\n\n\n---\n\n## 0. Survey\n\n| Paper | Source | Code/Project Link  |\n| --- | --- | --- |\n| [Computer-Aided Colorization State-of-the-Science: A Survey](https://ieeexplore.ieee.org/abstract/document/10892024) | TVCG 2025 | [[webpage]](https://github.com/DanielCho-HK/Colorization)  |\n| [Cartoon Image Processing: A Survey](https://link.springer.com/article/10.1007/s11263-022-01645-1) | IJCV 2022 | [[webpage]](https://github.com/Diya-R/CIP)  |\n| [Deep learning for image colorization: Current and future prospects](https://www.sciencedirect.com/science/article/pii/S0952197622001920) | EAAI 2022 |  |\n\n\n## 1. Automatic Image Colorization\n\n\n### 1.1 Software / Demo\n\n| Name | Author/Owner | Code/Project Link  |\n| --- | --- | --- |\n| DeOldify | Jason Antic | [[link]](https://github.com/jantic/DeOldify) |\n| Palette.fm | Emil Wallner | [[link]](https://palette.fm/) |\n| ArtImageHub | artimagehub.com | [[link]](https://artimagehub.com/old-photo-restoration) |\n\n\n### 1.2 Papers\n\n- Natural images\n\n| Paper | Source | Code/Project Link  |\n| --- | --- | --- |\n| [Learning Large-Scale Automatic Image Colorization](http://openaccess.thecvf.com/content_iccv_2015/papers/Deshpande_Learning_Large-Scale_Automatic_ICCV_2015_paper.pdf) | ICCV 2015 | [[project]](http://vision.cs.illinois.edu/projects/lscolor/) [[code]](https://github.com/aditya12agd5/iccv15_lscolorization) |\n| [Deep Colorization](http://openaccess.thecvf.com/content_iccv_2015/papers/Cheng_Deep_Colorization_ICCV_2015_paper.pdf) | ICCV 2015 |  |\n| [Learning Representations for Automatic Colorization](https://arxiv.org/pdf/1603.06668.pdf) | ECCV 2016 | [[project]](http://people.cs.uchicago.edu/~larsson/colorization/) [[code]](https://github.com/gustavla/autocolorize) |\n| [Colorful Image Colorization](https://arxiv.org/pdf/1603.08511.pdf) | ECCV 2016 | [[project]](http://richzhang.github.io/colorization/) [[code]](https://github.com/richzhang/colorization) |\n| [Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification](http://iizuka.cs.tsukuba.ac.jp/projects/colorization/data/colorization_sig2016.pdf) | SIGGRAPH 2016 | [[project]](http://iizuka.cs.tsukuba.ac.jp/projects/colorization/en/) [[code]](https://github.com/satoshiiizuka/siggraph2016_colorization) |\n| [Learning Diverse Image Colorization](http://openaccess.thecvf.com/content_cvpr_2017/papers/Deshpande_Learning_Diverse_Image_CVPR_2017_paper.pdf) | CVPR 2017 | [[code]](https://github.com/aditya12agd5/divcolor) |\n| [Structural Consistency and Controllability for Diverse Colorization](http://openaccess.thecvf.com/content_ECCV_2018/papers/Safa_Messaoud_Structural_Consistency_and_ECCV_2018_paper.pdf) | ECCV 2018 |  |\n| [Coloring With Limited Data: Few-Shot Colorization via Memory Augmented Networks](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yoo_Coloring_With_Limited_Data_Few-Shot_Colorization_via_Memory_Augmented_Networks_CVPR_2019_paper.pdf) | CVPR 2019 | [[project]](https://sjooyoo.github.io/MemoPainter_CVPR2019/)\u003cbr/\u003e\u003cbr/\u003e Unofficial:\u003cbr/\u003e [[code (PyTorch)]](https://github.com/dongheehand/MemoPainter-PyTorch)|\n| [ChromaGAN: Adversarial Picture Colorization with Semantic Class Distribution](http://openaccess.thecvf.com/content_WACV_2020/papers/Vitoria_ChromaGAN_Adversarial_Picture_Colorization_with_Semantic_Class_Distribution_WACV_2020_paper.pdf) | WACV 2020 | [[code]](https://github.com/pvitoria/ChromaGAN) |\n| [Instance-aware Image Colorization](http://openaccess.thecvf.com/content_CVPR_2020/papers/Su_Instance-Aware_Image_Colorization_CVPR_2020_paper.pdf) | CVPR 2020 | [[code]](https://github.com/ericsujw/InstColorization) [[project]](https://ericsujw.github.io/InstColorization/) |\n| [Pixelated Semantic Colorization](https://search.proquest.com/docview/2388669369?pq-origsite=gscholar\u0026fromopenview=true) | IJCV 2020 |  |\n| [Colorization Transformer](https://arxiv.org/abs/2102.04432) | ICLR 2021 | [[code]](https://github.com/google-research/google-research/tree/master/coltran) |\n| [Focusing on Persons: Colorizing Old Images Learning from Modern Historical Movies](https://arxiv.org/abs/2108.06515) | ACM MM 2021 | [[code]](https://github.com/BestiVictory/MHMD) |\n| [Towards Vivid and Diverse Image Colorization with Generative Color Prior](https://arxiv.org/abs/2108.08826) | ICCV 2021 | [[code]](https://github.com/ToTheBeginning/GCP-Colorization) |\n| [SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution](https://www.aaai.org/AAAI22Papers/AAAI-528.ZhangJ.pdf) (also reference based) | AAAI 2022 | |\n| [Bridging the Domain Gap towards Generalization in Automatic Colorization](https://github.com/Lhyejin/DG-Colorization) | ECCV 2022 | [[code]](https://github.com/Lhyejin/DG-Colorization) |\n| [ColorFormer: Image Colorization via Color Memory assisted Hybrid-attention Transformer](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136760020.pdf) | ECCV 2022 | [[code]](https://github.com/jixiaozhong/ColorFormer) |\n| [BigColor: Colorization using a Generative Color Prior for Natural Images](https://kimgeonung.github.io/bigcolor/) | ECCV 2022 | [[project]](https://kimgeonung.github.io/bigcolor/) [[code]](https://github.com/KIMGEONUNG/BigColor) |\n| [CT2: Colorization Transformer via Color Tokens](https://ci.idm.pku.edu.cn/Weng_ECCV22b.pdf) | ECCV 2022 | [[code]](https://github.com/shuchenweng/CT2) |\n| [Disentangled Image Colorization via Global Anchors](https://menghanxia.github.io/papers/2022_disco_main.pdf) | SIGGRAPH Asia 2022 | [[code]](https://github.com/MenghanXia/DisentangledColorization) [[project]](https://menghanxia.github.io/projects/disco.html) |\n| [UniColor: A Unified Framework for Multi-Modal Colorization with Transformer](https://arxiv.org/abs/2209.11223) (also multi-modal) | SIGGRAPH Asia 2022 | [[project]](https://luckyhzt.github.io/unicolor) |\n| [Improved Diffusion-based Image Colorization via Piggybacked Models](https://arxiv.org/abs/2304.11105) | arxiv 23.04 | [[project]](https://piggyback-color.github.io/) |\n| [DDColor: Towards Photo-Realistic and Semantic-Aware Image Colorization via Dual Decoders](https://arxiv.org/abs/2212.11613) | ICCV 2023 | [[code]](https://github.com/piddnad/DDColor) [[project]](https://www.modelscope.cn/models/damo/cv_ddcolor_image-colorization/summary) |\n| [Diffusing Colors: Image Colorization with Text Guided Diffusion](https://arxiv.org/abs/2312.04145) (also text-based) | SIGGRAPH Asia 2023 | [[project]](https://aharonazulay.github.io/project_page_colorization/) |\n| [Automatic Controllable Colorization via Imagination](https://arxiv.org/abs/2404.05661) | CVPR 2024 | [[code]](https://github.com/xy-cong/imagine-colorization) [[project]](https://xy-cong.github.io/imagine-colorization/) |\n| [Control Color: Multimodal Diffusion-based Interactive Image Colorization](https://arxiv.org/abs/2402.10855) | arxiv 24.02 | [[code]](https://github.com/ZhexinLiang/Control-Color) [[project]](https://zhexinliang.github.io/Control_Color/) |\n| [MultiColor: Image Colorization by Learning from Multiple Color Spaces](https://openreview.net/forum?id=Zo4P2F7xLY) | ACM MM 2024 |  |\n| [Image Colorization via Efficient Diffusion Model](https://ieeexplore.ieee.org/abstract/document/11442792) | TMM 2026 |  |\n| [ColorFLUX: A Structure-Color Decoupling Framework for Old Photo Colorization](https://openaccess.thecvf.com/content/CVPR2026/papers/Li_ColorFLUX_A_Structure-Color_Decoupling_Framework_for_Old_Photo_Colorization_CVPR_2026_paper.pdf) | CVPR 2026 |  |\n\n\n- Line arts\n\n| Paper | Source | Code/Project Link  |\n| --- | --- | --- |\n| [Region Assisted Sketch Colorization](https://ieeexplore.ieee.org/abstract/document/10303276/) | TIP 2023 |  |\n\n\n## 2. User Guided Image Colorization\n\n### 2.1 Based on scribble\n\n- Software / Demo\n\n| Image Type | Name | Author/Owner | Code/Project Link  |\n| --- | --- | --- | --- |\n| Line art | Petalica Paint (Old version: PaintsChainer) | Preferred Networks, Inc. | [[Petalica Paint (Online service)]](https://petalica.com/) [[PaintsChainer V1 code]](https://github.com/pfnet/PaintsChainer) |\n| Line art | Style2Paints (SEPA) | Style2Paints Research | [[link]](https://github.com/lllyasviel/style2paints) |\n\n- Papers: Natural images\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- | --- |\n| Natural Gray-Scale | [Real-Time User-Guided Image Colorization with Learned Deep Priors](https://arxiv.org/abs/1705.02999) | SIGGRAPH 2017 | [[project]](https://richzhang.github.io/ideepcolor/) [[code1]](https://github.com/junyanz/interactive-deep-colorization) [[code2]](https://github.com/richzhang/colorization-pytorch) |\n| Natural Gray-Scale | [iColoriT: Towards Propagating Local Hint to the Right Region in Interactive Colorization by Leveraging Vision Transformer](https://arxiv.org/pdf/2207.06831.pdf) | WACV 2023 | [[project]](https://pmh9960.github.io/research/iColoriT/) [[code]](https://github.com/pmh9960/iColoriT) |\n| Natural Gray-Scale | [LGA-Net: Learning Local and Global Affinities for Sparse Scribble based Image Colorization](https://orca.cardiff.ac.uk/id/eprint/180990/1/LGA-Net_ICCV2025.pdf) | ICCV 2025 | [[code]](https://github.com/HONGJINLYUCS/LGA-Net-ICCV-2025) |\n\n\n- Papers: Sketch / Line arts\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- | --- |\n| Manga | [Manga colorization](http://www.cse.cuhk.edu.hk/~ttwong/papers/manga/manga.pdf) | SIGGRAPH 2006 | [[Project]](http://www.cse.cuhk.edu.hk/~ttwong/papers/manga/manga.html) |\n| Line art / Sketch / Manga | [LazyBrush: Flexible Painting Tool for Hand-drawn Cartoons](https://dcgi.fel.cvut.cz/home/sykorad/Sykora09-EG.pdf) | Eurographics 2009 | [[Project Home \u0026 Software]](https://dcgi.fel.cvut.cz/home/sykorad/lazybrush.html) \u003cbr/\u003e\u003cbr/\u003eUnofficial:\u003cbr/\u003e [[code(Matlab)]](https://github.com/kosua20/LazyBrush-implementation) |\n| Line art / Sketch | [Outline Colorization through Tandem Adversarial Networks](https://arxiv.org/abs/1704.08834) | 1704.08834 | [[code]](https://github.com/kvfrans/deepcolor) |\n| Sketch | [Scribbler: Controlling Deep Image Synthesis with Sketch and Color](http://openaccess.thecvf.com/content_cvpr_2017/papers/Sangkloy_Scribbler_Controlling_Deep_CVPR_2017_paper.pdf) | CVPR 2017 |  |\n| Line art / Sketch | [Auto-painter: Cartoon Image Generation from Sketch by Using Conditional Generative Adversarial Networks](https://arxiv.org/pdf/1705.01908.pdf) | Neurocomputing 2018  | [[code]](https://github.com/irfanICMLL/Auto_painter) |\n| Line art | [User-Guided Deep Anime Line Art Colorization with Conditional Adversarial Networks](https://arxiv.org/pdf/1808.03240.pdf) | ACM MM 2018 | [[code]](https://github.com/orashi/AlacGAN) |\n| Line art | [Two-stage Sketch Colorization](http://www.cse.cuhk.edu.hk/~ttwong/papers/colorize/colorize.pdf) | SIGGRAPH Asia 2018 | [[Project]](https://www.cse.cuhk.edu.hk/~ttwong/papers/colorize/colorize.html) |\n| Line art | [User-Guided Line Art Flat Filling with Split Filling Mechanism](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhang_User-Guided_Line_Art_Flat_Filling_With_Split_Filling_Mechanism_CVPR_2021_paper.pdf) | CVPR 2021 | [[Project]](https://lllyasviel.github.io/SplitFilling/) [[code]](https://github.com/lllyasviel/SplitFilling) |\n| Line art | [Dual Color Space Guided Sketch Colorization](https://ieeexplore.ieee.org/abstract/document/9515572) | TIP 2021 |  |\n| Line art | [Delaunay Painting: Perceptual Image Colouring from Raster Contours with Gaps](https://onlinelibrary.wiley.com/doi/full/10.1111/cgf.14517) | CGF 2022 |  |\n| Line art | [FlatGAN: A Holistic Approach for Robust Flat-Coloring in High-Definition with Understanding Line Discontinuity](https://dl.acm.org/doi/abs/10.1145/3581783.3613788) | ACM MM 2023 | [[code]](https://github.com/hanish3464/FlatGAN) |\n| Line art | [Winding Number Features for Vector Sketch Colorization](https://onlinelibrary.wiley.com/doi/full/10.1111/cgf.15141) | CGF 2024 |  |\n| Line art | [KISSColor: Kinetic and Intuitive Stroke Stretching for Vector Drawing Colorization](https://dl.acm.org/doi/abs/10.1145/3763307) | SIGGRAPH Asia 2025 |  |\n| Line art | [Hint-AUC: Deterministic Region-based Hint Generation for Line Art Colorization Evaluation](https://ieeexplore.ieee.org/document/11714481) | TVCG 2026 |  |\n\n\n\n### 2.2 Based on reference image\n\n- Natural images\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n| Natural Gray-Scale | [Deep Exemplar-based Colorization](https://arxiv.org/pdf/1807.06587.pdf) | SIGGRAPH 2018 | [[code]](https://github.com/msracver/Deep-Exemplar-based-Colorization) |\n| Natural Gray-Scale | [Example-Based Colourization Via Dense Encoding Pyramids](http://www.shengfenghe.com/uploads/1/5/1/3/15132160/cgf_13659_rev_ev.pdf) (also palette based) | Pacific Graphics 2018 | [[code]](https://github.com/chufengxiao/Example-based-Colorization-via-Dense-Encoding-pyramids) |\n| Natural Gray-Scale | [A Superpixel-based Variational Model for Image Colorization](https://ieeexplore.ieee.org/abstract/document/8676327) | TVCG 2019 |  |\n| Natural Gray-Scale | [Automatic Example-based Image Colourisation using Location-Aware Cross-Scale Matching](https://ieeexplore.ieee.org/abstract/document/8699109) | TIP 2019 |  |\n| Natural Gray-Scale | [Stylization-Based Architecture for Fast Deep Exemplar Colorization](http://openaccess.thecvf.com/content_CVPR_2020/papers/Xu_Stylization-Based_Architecture_for_Fast_Deep_Exemplar_Colorization_CVPR_2020_paper.pdf) | CVPR 2020 | [[code]](https://github.com/xuzhongyou/Colorization) |\n| Natural Gray-Scale | [Gray2ColorNet: Transfer More Colors from Reference Image](https://dl.acm.org/doi/abs/10.1145/3394171.3413594) | ACM MM 2020 |  |\n| Natural Gray-Scale | [Globally and Locally Semantic Colorization via Exemplar-Based Broad-GAN](https://ieeexplore.ieee.org/abstract/document/9566701) | TIP 2021 |  |\n| Natural Gray-Scale | [Yes, \"Attention Is All You Need\", for Exemplar based Colorization](https://dl.acm.org/doi/abs/10.1145/3474085.3475385) | ACM MM 2021 |  |\n| Natural Gray-Scale | [SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution](https://www.aaai.org/AAAI22Papers/AAAI-528.ZhangJ.pdf) (also automatic) | AAAI 2022 | |\n| Natural Gray-Scale | [Semantic-Sparse Colorization Network for Deep Exemplar-based Colorization](https://arxiv.org/abs/2112.01335) | ECCV 2022 |  |\n| Natural Gray-Scale | [Unsupervised Deep Exemplar Colorization via Pyramid Dual Non-local Attention](https://ieeexplore.ieee.org/abstract/document/10183846) | TIP 2023 | [[code]](https://github.com/wd1511/PDNLA-Net) |\n| Natural Gray-Scale | [Lightweight Deep Exemplar Colorization via Semantic Attention-Guided Laplacian Pyramid](https://ieeexplore.ieee.org/abstract/document/10526459) | TVCG 2024 |  |\n\n- Sketch / Line arts\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n| Manga | [Comicolorization: Semi-Automatic Manga Colorization](https://arxiv.org/pdf/1706.06759.pdf) | SIGGRAPH Asia 2017 Technical Briefs | [[code]](https://github.com/DwangoMediaVillage/Comicolorization) |\n| Sketch | [TextureGAN: Controlling Deep Image Synthesis with Texture Patches](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xian_TextureGAN_Controlling_Deep_CVPR_2018_paper.pdf) | CVPR 2018 | [[code]](https://github.com/janesjanes/Pytorch-TextureGAN) |\n| Line art / Sketch | [Adversarial Colorization Of Icons Based On Structure And Color Conditions](https://arxiv.org/pdf/1910.05253.pdf) | ACM MM 2019 | [[Code]](https://github.com/jxcodetw/Adversarial-Colorization-Of-Icons-Based-On-Structure-And-Color-Conditions) |\n| Line art / Sketch | [Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence](http://openaccess.thecvf.com/content_CVPR_2020/papers/Lee_Reference-Based_Sketch_Image_Colorization_Using_Augmented-Self_Reference_and_Dense_Semantic_CVPR_2020_paper.pdf) | CVPR 2020 | [[project]](https://ssuhan.github.io/RSC_CVPR20/) |\n| Manga | [Manga Filling Style Conversion with Screentone Variational Autoencoder](http://www.cse.cuhk.edu.hk/~ttwong/papers/screenstyle/screenstyle.pdf) | SIGGRAPH Asia 2020 | [[project]](https://www.cse.cuhk.edu.hk/~ttwong/papers/screenstyle/screenstyle.html) |\n| Line art / Sketch | [Colorization of Line Drawings with Empty Pupils](https://www.gwern.net/docs/anime/2020-akita.pdf) | PG 2020 |  |\n| Line art / Sketch | [Active Colorization for Cartoon Line Drawings](https://ieeexplore.ieee.org/abstract/document/9143503) | TVCG 2020 |  |\n| Line art / Sketch | [Line Art Correlation Matching Feature Transfer Network for Automatic Animation Colorization](https://arxiv.org/abs/2004.06718) | WACV 2021 |  |\n| Line art / Sketch | [Style-Structure Disentangled Features and Normalizing Flows for Diverse Icon Colorization](https://openaccess.thecvf.com/content/CVPR2022/papers/Li_Style-Structure_Disentangled_Features_and_Normalizing_Flows_for_Diverse_Icon_Colorization_CVPR_2022_paper.pdf) | CVPR 2022 |  |\n| Line art / Sketch | [Eliminating Gradient Conflict in Reference-based Line-Art Colorization](https://arxiv.org/abs/2207.06095) | ECCV 2022 | [[code]](https://github.com/kunkun0w0/SGA) |\n| Line art / Sketch | [Self-driven Dual-path Learning for Reference-based Line Art Colorization under Limited Data](https://ieeexplore.ieee.org/abstract/document/10182273) | TCSVT 2023 |  |\n| Line art / Sketch | [FlexIcon: Flexible Icon Colorization via Guided Images and Palettes](https://dl.acm.org/doi/abs/10.1145/3581783.3612182) (also palette based) | ACM MM 2023 |  |\n| Line art / Sketch | [AnimeDiffusion: Anime Face Line Drawing Colorization via Diffusion Models](https://arxiv.org/abs/2303.11137) | TVCG 2024 | [[code]](https://github.com/xq-meng/AnimeDiffusion) |\n| Manga | [ColorFlow: Retrieval-Augmented Image Sequence Colorization](https://arxiv.org/abs/2412.11815) | arxiv 24.12 | [[code]](https://github.com/TencentARC/ColorFlow) [[webpage]](https://zhuang2002.github.io/ColorFlow/) |\n| Line art / Sketch | [MangaNinja: Line Art Colorization with Precise Reference Following](https://arxiv.org/abs/2501.08332) | CVPR 2025 | [[code]](https://github.com/ali-vilab/MangaNinjia) [[webpage]](https://johanan528.github.io/MangaNinjia/) |\n| Line art / Sketch | [Image Referenced Sketch Colorization Based on Animation Creation Workflow](https://openaccess.thecvf.com/content/CVPR2025/papers/Yan_Image_Referenced_Sketch_Colorization_Based_on_Animation_Creation_Workflow_CVPR_2025_paper.pdf) | CVPR 2025 | [[code]](https://github.com/tellurion-kanata/colorizeDiffusion) |\n| Line art / Sketch | [Cobra: Efficient Line Art COlorization with BRoAder References](https://arxiv.org/abs/2504.12240) | SIGGRAPH 2025 | [[code]](https://github.com/Zhuang2002/Cobra) [[webpage]](https://zhuang2002.github.io/Cobra/) |\n| Line art / Sketch | [MagicColor: Multi-Instance Sketch Colorization](https://arxiv.org/abs/2503.16948) | ICCV 2025 | [[code]](https://github.com/YinHan-Zhang/MagicColor) [[webpage]](https://yinhan-zhang.github.io/color/) |\n| Line art / Sketch | [ColorizeDiffusion: Improving Reference-Based Sketch Colorization with Latent Diffusion Model](https://ieeexplore.ieee.org/abstract/document/10943696) | WACV 2025 | [[code]](https://github.com/tellurion-kanata/colorizeDiffusion) |\n| Line art / Sketch | [ColorizeDiffusion v2: Enhancing Reference-based Sketch Colorization Through Separating Utilities](https://arxiv.org/abs/2504.06895) | arxiv 25.04 | [[code]](https://github.com/tellurion-kanata/colorizeDiffusion) |\n| Line art / Sketch | [MangaDiT: Reference-Guided Line Art Colorization with Hierarchical Attention in Diffusion Transformers](https://arxiv.org/abs/2508.09709) | arxiv 25.08 | |\n| Line art / Sketch | [Towards High-resolution and Disentangled Reference-based Sketch Colorization](https://arxiv.org/abs/2603.05971) | CVPR 2026 | [[code]](https://github.com/tellurion-kanata/ColorizeDiffusionXL) |\n| Line art / Sketch | [TopoColor: Topology-Aware Region Correspondence for Line Art Colorization](https://ieeexplore.ieee.org/document/11659100) | TVCG 2026 |  | \n\n\n### 2.3 Based on palette\n\n- Natural images\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n| Natural Image | [Palette-based Photo Recoloring](https://gfx.cs.princeton.edu/pubs/Chang_2015_PPR/chang2015-palette_small.pdf) | SIGGRAPH 2015 | [[project]](https://gfx.cs.princeton.edu/pubs/Chang_2015_PPR/index.php) |\n| Natural Gray-Scale | [Coloring with Words: Guiding Image Colorization Through Text-based Palette Generation](https://arxiv.org/pdf/1804.04128.pdf) (also text based) | ECCV 2018 | [[code]](https://github.com/awesome-davian/Text2Colors/) |\n| Natural Gray-Scale | [Example-Based Colourization Via Dense Encoding Pyramids](http://www.shengfenghe.com/uploads/1/5/1/3/15132160/cgf_13659_rev_ev.pdf) (also reference based) | Pacific Graphics 2018 | [[code]](https://github.com/chufengxiao/Example-based-Colorization-via-Dense-Encoding-pyramids) |\n| Natural Gray-Scale | [PalGAN: Image Colorization with Palette Generative Adversarial Networks](https://link.springer.com/chapter/10.1007/978-3-031-19784-0_16) | ECCV 2022 | [[code]](https://github.com/shepnerd/PalGAN) |\n| Natural Gray-Scale | [Exploring Palette based Color Guidance in Diffusion Models](https://arxiv.org/abs/2508.08754) | MM 2025 |  |\n\n\n- Sketch / Line arts\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n| Line art / Sketch | [FlexIcon: Flexible Icon Colorization via Guided Images and Palettes](https://dl.acm.org/doi/abs/10.1145/3581783.3612182) (also reference based) | ACM MM 2023 |  |\n| Line art / Sketch | [SketchDeco: Training-Free Latent Composition for Precise Sketch Colourisation](https://openaccess.thecvf.com/content/CVPR2026/papers/Utintu_SketchDeco_Training-Free_Latent_Composition_for_Precise_Sketch_Colourisation_CVPR_2026_paper.pdf) | CVPR 2026 | [[code]](https://github.com/CHAITron/sketchdeco-code) [[webpage]](https://chaitron.github.io/SketchDeco/) |\n\n### 2.4 Based on language or text\n\n- Natural images\n\n| Paper | Source | Code/Project Link  |\n| --- | --- |--- |\n| [Language-Based Image Editing with Recurrent Attentive Models](https://arxiv.org/pdf/1711.06288.pdf) | CVPR 2018 | [[code]](https://github.com/Jianbo-Lab/LBIE) |\n| [Coloring with Words: Guiding Image Colorization Through Text-based Palette Generation](https://arxiv.org/pdf/1804.04128.pdf) (also palette based) | ECCV 2018 | [[code]](https://github.com/awesome-davian/Text2Colors/) |\n| [Learning to Color from Language](https://arxiv.org/pdf/1804.06026.pdf) | NAACL 2018 | [[code]](https://github.com/superhans/colorfromlanguage) |\n| [L-CoDe: Language-based Colorization using Color-object Decoupled Conditions](https://ci.idm.pku.edu.cn/Weng_AAAI22.pdf) | AAAI 2022 | [[code]](https://github.com/changzheng123/L-CoDe) |\n| [L-CoDer: Language-based Colorization with Color-object Decoupling Transformer](https://ci.idm.pku.edu.cn/Weng_ECCV22g.pdf) | ECCV 2022 | [[code]](https://github.com/changzheng123/L-CoDer) |\n| [L-CoIns: Language-based Colorization with Instance Awareness](https://openaccess.thecvf.com/content/CVPR2023/papers/Chang_L-CoIns_Language-Based_Colorization_With_Instance_Awareness_CVPR_2023_paper.pdf) | CVPR 2023 |  |\n| [L-CAD: Language-based Colorization with Any-level Descriptions](https://arxiv.org/abs/2305.15217) | NeurIPS 2023 | [[code]](https://github.com/changzheng123/L-CAD) |\n| [Diffusing Colors: Image Colorization with Text Guided Diffusion](https://arxiv.org/abs/2312.04145) | SIGGRAPH Asia 2023 | [[project]](https://aharonazulay.github.io/project_page_colorization/) |\n| [COCO-LC: Colorfulness Controllable Language-based Colorization](https://dl.acm.org/doi/10.1145/3664647.3680662) | ACM MM 2024 | [[project]](https://lyf1212.github.io/COCO-LC/) [[code]](https://github.com/lyf1212/COCO-LC/) |\n| [Controllable Image Colorization with Instance-aware Texts and Masks](https://arxiv.org/abs/2505.08705) (also automatic) | arxiv 25.05 |  |\n\n- Sketch / Line arts\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n| Line art | [Tag2Pix: Line Art Colorization Using Text Tag With SECat and Changing Loss](https://arxiv.org/pdf/1908.05840.pdf) | ICCV 2019 | [[code]](https://github.com/blandocs/Tag2Pix) [[code2 (GUI)]](https://github.com/MerHS/tag2pix-gui) |\n| Scene Sketch | [Language-based Colorization of Scene Sketches](http://sweb.cityu.edu.hk/hongbofu/doc/language-based_sketch_colorization_SA19.pdf) | SIGGRAPH Asia 2019 | [[code]](https://github.com/SketchyScene/SketchySceneColorization) [[project]](https://sketchyscene.github.io/SketchySceneColorization/) |\n| Line art | [Line Art Colorization Based on Explicit Region Segmentation](https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.14396) | Pacific Graphics 2021 | [[code]](https://github.com/Ricardo-L-C/ColorizationWithRegion) |\n| Sketch | [Adding Conditional Control to Text-to-Image Diffusion Models](https://openaccess.thecvf.com/content/ICCV2023/papers/Zhang_Adding_Conditional_Control_to_Text-to-Image_Diffusion_Models_ICCV_2023_paper.pdf) | ICCV 2023 | [[code]](https://github.com/lllyasviel/ControlNet) |\n\n\n### 2.5 Multi-modal\n\n\n| Image Type | Paper | Input | Source | Code/Project Link  |\n| --- | --- |--- | --- |--- |\n| Natural Gray-Scale | [Interactive Deep Colorization Using Simultaneous Global and Local Inputs](https://ieeexplore.ieee.org/abstract/document/8683686) | stroke + palette | ICASSP 2019 |  |\n| Natural Gray-Scale | [UniColor: A Unified Framework for Multi-Modal Colorization with Transformer](https://arxiv.org/abs/2209.11223) | stroke + exemplar + text | SIGGRAPH Asia 2022 | [[project]](https://luckyhzt.github.io/unicolor) |\n| Line art | [Two-Step Training: Adjustable Sketch Colourization via Reference Image and Text Tag](https://onlinelibrary.wiley.com/doi/full/10.1111/cgf.14791) | exemplar + text | CGF 2023 | [[code]](https://github.com/tellurion-kanata/sketch_colorizer) |\n| Natural Gray-Scale | [Control Color: Multimodal Diffusion-based Interactive Image Colorization](https://arxiv.org/abs/2402.10855) | text, stroke, exemplar | arxiv 24.02 | [[code]](https://github.com/ZhexinLiang/Control-Color) [[project]](https://zhexinliang.github.io/Control_Color/) |\n| Natural Gray-Scale | [Versatile Vision Foundation Model for Image and Video Colorization](https://dl.acm.org/doi/abs/10.1145/3641519.3657509) | text, scribble, exemplar | SIGGRAPH 2024 | |\n| Line art | [OmniColor: A Unified Framework for Multi-modal Lineart Colorization](https://arxiv.org/abs/2603.27531) | text, scribble, exemplar | ECCV 2026 | [[code]](https://github.com/zhangxulu1996/OmniColor) |\n\n\n### 2.6 Interactive Colorization\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n| Natural Gray-Scale | [Deep Edge-Aware Interactive Colorization against Color-Bleeding Effects](https://arxiv.org/abs/2107.01619) | ICCV 2021 | [[project]](https://eungyeupkim.github.io/edge-enhancing-colorization/) [[code(metric)]](https://github.com/niceDuckgu/CDR)|\n| Line art | [Guiding Users to Where to Give Color Hints for Efficient Interactive Sketch Colorization via Unsupervised Region Prioritization](https://arxiv.org/abs/2210.14270) | WACV 2023 |  |\n\n\n## 3. Human-AI Collaborated Colorization System\n\n| Paper | Source | Code/Project Link  |\n| --- | --- |--- |\n| [FlatMagic: Improving Flat Colorization through AI-driven Design for Digital Comic Professionals](https://dl.acm.org/doi/abs/10.1145/3491102.3502075) | CHI 2022 | [[code]](https://github.com/Nauhcnay/flat_magic_backend) |\n| [No Pixel Left Behind: Filling Gaps in Anime Colorization](https://marc2825.github.io/GapFill/assets/GapFill_CHI.pdf) | CHI 2026 | [[code]](https://github.com/marc2825/GapFill) [[webpage]](https://marc2825.github.io/GapFill/) |\n\n\n## 4. Video Colorization\n\n### 4.0 Survey\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n|  | [Video Colorization: A Survey](https://jcst.ict.ac.cn/en/article/doi/10.1007/s11390-024-4143-z) | JCST 2024 | |\n\n### 4.1 Automatically\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n| Natural Gray-Scale | [Fully Automatic Video Colorization with Self-Regularization and Diversity](http://openaccess.thecvf.com/content_CVPR_2019/papers/Lei_Fully_Automatic_Video_Colorization_With_Self-Regularization_and_Diversity_CVPR_2019_paper.pdf) | CVPR 2019 | [[code]](https://github.com/ChenyangLEI/Fully-Automatic-Video-Colorization-with-Self-Regularization-and-Diversity) |\n| Natural Gray-Scale | [VCGAN: Video Colorization With Hybrid Generative Adversarial Network](https://ieeexplore.ieee.org/abstract/document/9721653) | TMM 2022 | [[code]](https://github.com/zhaoyuzhi/VCGAN) |\n| Natural Gray-Scale | [ColorSurge: Bringing Vibrancy and Efficiency to Automatic Video Colorization via Dual-Branch Fusion](https://dl.acm.org/doi/full/10.1145/3721238.3730736) | SIGGRAPH 2025 | [[code]](https://github.com/ABTols/ColorSurge) |\n\n\n### 4.2 Based on reference\n\n- Natural images\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n| Natural Gray-Scale | [Switchable Temporal Propagation Network](http://openaccess.thecvf.com/content_ECCV_2018/papers/Sifei_Liu_Switchable_Temporal_Propagation_ECCV_2018_paper.pdf) | ECCV 2018 |  |\n| Natural Gray-Scale | [Tracking Emerges by Colorizing Videos](http://openaccess.thecvf.com/content_ECCV_2018/papers/Carl_Vondrick_Self-supervised_Tracking_by_ECCV_2018_paper.pdf) | ECCV 2018 | [[code]](https://github.com/wbaek/tracking_via_colorization) |\n| Natural Gray-Scale | [Deep Exemplar-based Video Colorization](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang_Deep_Exemplar-Based_Video_Colorization_CVPR_2019_paper.pdf) | CVPR 2019 | [[code]](https://github.com/zhangmozhe/Deep-Exemplar-based-Video-Colorization) |\n| Natural Gray-Scale | [DeepRemaster: Temporal Source-Reference Attention Networks for Comprehensive Video Enhancement](http://iizuka.cs.tsukuba.ac.jp/projects/remastering/data/remastering_siggraphasia2019.pdf) | SIGGRAPH Asia 2019 | [[code]](https://github.com/satoshiiizuka/siggraphasia2019_remastering) [[project]](http://iizuka.cs.tsukuba.ac.jp/projects/remastering/en/index.html) |\n| Natural Gray-Scale | [Reference-Based Video Colorization with Spatiotemporal Correspondence](https://arxiv.org/abs/2011.12528) | 2011.12528 |  |\n| Natural Gray-Scale | [BiSTNet: Semantic Image Prior Guided Bidirectional Temporal Feature Fusion for Deep Exemplar-based Video Colorization](https://arxiv.org/abs/2212.02268) | TPAMI 2024 | [[code]](https://github.com/yyang181/BiSTNet) [[project]](https://yyang181.github.io/BiSTNet/) |\n| Natural Gray-Scale | [Exemplar-based Video Colorization with Long-term Spatiotemporal Dependency](https://arxiv.org/abs/2303.15081) | KBS 2024 |  |\n| Natural Gray-Scale | [ColorMNet: A Memory-based Deep Spatial-Temporal Feature Propagation Network for Video Colorization](https://arxiv.org/abs/2404.06251) | ECCV 2024 | [[code]](https://github.com/yyang181/colormnet) [[project]](https://yyang181.github.io/colormnet/) |\n\n\n- Sketch / Line arts\n\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n| Line art | [The Animation Transformer: Visual Correspondence via Segment Matching](https://arxiv.org/abs/2109.02614) | ICCV 2021 | [[App]](https://cadmium.app/) |\n| Line art | [Line Art Correlation Matching Feature Transfer Network for Automatic Animation Colorization](https://openaccess.thecvf.com/content/WACV2021/papers/Zhang_Line_Art_Correlation_Matching_Feature_Transfer_Network_for_Automatic_Animation_WACV_2021_paper.pdf) | WACV 2021 | |\n| Line art | [Deep Sketch-guided Cartoon Video Inbetweening](https://ieeexplore.ieee.org/abstract/document/9314221) | TVCG 2021 | [[code]](https://github.com/xiaoyu258/Inbetweening) |\n| Line art | [Reference-Based Deep Line Art Video Colorization](https://orca.cardiff.ac.uk/146848/1/RefLineArtVideoColorizationTVCG.pdf) | TVCG 2022 |  |\n| Line art | [Learning Inclusion Matching for Animation Paint Bucket Colorization](https://arxiv.org/abs/2403.18342) | CVPR 2024 | [[webpage]](https://ykdai.github.io/projects/InclusionMatching) [[code]](https://github.com/ykdai/BasicPBC) |\n| Line art | [Paint Bucket Colorization Using Anime Character Color Design Sheets](https://arxiv.org/abs/2410.19424v1) | arxiv 24.10 |  [[code]](https://github.com/ykdai/BasicPBC) |\n| Line art | [ToonCrafter: Generative Cartoon Interpolation](https://arxiv.org/abs/2405.17933) | SIGGRAPH Asia 2024 | [[code]](https://github.com/ToonCrafter/ToonCrafter) [[webpage]](https://doubiiu.github.io/projects/ToonCrafter/) |\n| Line art | [LVCD: Reference-based Lineart Video Colorization with Diffusion Models](https://arxiv.org/abs/2409.12960) | SIGGRAPH Asia 2024 | [[webpage]](https://luckyhzt.github.io/lvcd) |\n| Line art | [AniDoc: Animation Creation Made Easier](https://arxiv.org/abs/2412.14173) | CVPR 2025 | [[webpage]](https://yihao-meng.github.io/AniDoc_demo/) [[code]](https://github.com/yihao-meng/AniDoc) |\n| Line art | [SketchColour: Channel Concat Guided DiT-based Sketch-to-Colour Pipeline for 2D Animation](https://arxiv.org/abs/2507.01586) | arxiv 25.07 | [[webpage]](https://bconstantine.github.io/SketchColour/) [[code]](https://github.com/bconstantine/SketchColour) |\n| Line art | [AnimeColor: Reference-based Animation Colorization with Diffusion Transformers](https://arxiv.org/abs/2507.20158) | MM 2025 | [[code]](https://github.com/IamCreateAI/AnimeColor) |\n| Line art | [ToonComposer: Streamlining Cartoon Production with Generative Post-Keyframing](https://arxiv.org/abs/2508.10881) | arxiv 25.08 |  [[webpage]](https://lg-li.github.io/project/tooncomposer) [[code]](https://github.com/TencentARC/ToonComposer) |\n| Line art | [DACoN: DINO for Anime Paint Bucket Colorization with Any Number of Reference Images](https://arxiv.org/abs/2509.14685) | ICCV 2025 | [[code]](https://github.com/kzmngt/DACoN) |\n| Line art | [A Unified Framework for Industrial Cel-Animation Colorization with Temporal-Structural Awareness](https://openaccess.thecvf.com/content/ICCV2025/papers/Feng_A_Unified_Framework_for_Industrial_Cel-Animation_Colorization_with_Temporal-Structural_Awareness_ICCV_2025_paper.pdf) | ICCV 2025 |  |\n| Line art | [LongAnimation: Long Animation Generation with Dynamic Global-Local Memory](https://openaccess.thecvf.com/content/ICCV2025/papers/Chen_LongAnimation_Long_Animation_Generation_with_Dynamic_Global-Local_Memory_ICCV_2025_paper.pdf) | ICCV 2025 | [[webpage]](https://cn-makers.github.io/long_animation_web/) |\n| Line art | [TimeColor: Flexible Reference Colorization via Temporal Concatenation](https://arxiv.org/abs/2601.00296) | arxiv 26.01 | [[webpage]](https://bconstantine.github.io/TimeColor/) |\n\n\n\n### 4.3 Based on scribble\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n| Natural Gray-Scale | [SVCNet: Scribble-based Video Colorization Network with Temporal Aggregation](https://arxiv.org/abs/2303.11591) | TIP 2023 | [[code]](https://github.com/zhaoyuzhi/SVCNet) |\n\n\n### 4.4 Based on text\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n| Natural Gray-Scale | [Towards Photorealistic Video Colorization via Gated Color-Guided Image Diffusion Models](https://openreview.net/forum?id=4k79es7Guv) | ACM MM 2024 |  |\n| Natural Gray-Scale | [L-C4: Language-Based Video Colorization for Creative and Consistent Color](https://arxiv.org/abs/2410.04972) | arxiv 24.10 |  |\n| Natural Gray-Scale | [ColorDiffuser: Video Colorization with Pretrained Text-to-Image Diffusion Models](https://arxiv.org/abs/2306.01732) | ACMMM 2025 | [[code]](https://github.com/ColorDiffuser/ColorDiffuser) [[project]](https://colordiffuser.github.io/) |\n\n### 4.5 Based on palette\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n| Natural Gray-Scale | [Consistent Video Colorization via Palette Guidance](https://arxiv.org/abs/2501.19331) | arxiv 25.01 |  |\n\n### 4.6 Multimodal\n\n| Image Type | Paper | Source | Code/Project Link  |\n| --- | --- | --- |--- |\n| Natural Gray-Scale | [VanGogh: A Unified Multimodal Diffusion-based Framework for Video Colorization](https://arxiv.org/abs/2501.09499) | arxiv 25.01 | [[code]](https://github.com/BecauseImBatman0/VanGogh) [[webpage]](https://becauseimbatman0.github.io/VanGogh) |\n| Natural Gray-Scale | [UniColorFlow: A Unified Framework for Multimodal-Guided Video Colorization with Consistency Flow](https://link.springer.com/article/10.1007/s11263-026-03058-w) | IJCV 2026 |  |\n\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/markmohr%2Fawesome-image-colorization/projects"}