Awesome-Image-Colorization
:books: A collection of Deep Learning based Image Colorization and Video Colorization papers.
https://github.com/MarkMoHR/Awesome-Image-Colorization
Last synced: 4 days ago
JSON representation
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0. Survey
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1. Automatic Image Colorization
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1.1 Software / Demo
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1.2 Papers
- Learning Large-Scale Automatic Image Colorization
- Deep Colorization
- Learning Representations for Automatic Colorization
- Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification
- Learning Diverse Image Colorization
- Structural Consistency and Controllability for Diverse Colorization
- Coloring With Limited Data: Few-Shot Colorization via Memory Augmented Networks - PyTorch)|
- ChromaGAN: Adversarial Picture Colorization with Semantic Class Distribution
- Instance-aware Image Colorization
- Pixelated Semantic Colorization
- Colorization Transformer - research/google-research/tree/master/coltran) |
- Focusing on Persons: Colorizing Old Images Learning from Modern Historical Movies
- Towards Vivid and Diverse Image Colorization with Generative Color Prior - Colorization) |
- ColorFormer: Image Colorization via Color Memory assisted Hybrid-attention Transformer
- Improved Diffusion-based Image Colorization via Piggybacked Models - color.github.io/) |
- DDColor: Towards Photo-Realistic and Semantic-Aware Image Colorization via Dual Decoders - colorization/summary) |
- Region Assisted Sketch Colorization
- Automatic Controllable Colorization via Imagination - cong/imagine-colorization) [[project]](https://xy-cong.github.io/imagine-colorization/) |
- Colorful Image Colorization
- Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification
- Bridging the Domain Gap towards Generalization in Automatic Colorization - Colorization) |
- BigColor: Colorization using a Generative Color Prior for Natural Images
- MultiColor: Image Colorization by Learning from Multiple Color Spaces
- Region Assisted Sketch Colorization
- Learning Large-Scale Automatic Image Colorization
- Deep Colorization
- Learning Representations for Automatic Colorization
- Learning Diverse Image Colorization
- Coloring With Limited Data: Few-Shot Colorization via Memory Augmented Networks - PyTorch)|
- Instance-aware Image Colorization
- Structural Consistency and Controllability for Diverse Colorization
- ChromaGAN: Adversarial Picture Colorization with Semantic Class Distribution
- Image Colorization via Efficient Diffusion Model
- ColorFLUX: A Structure-Color Decoupling Framework for Old Photo Colorization
- SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution
- CT2: Colorization Transformer via Color Tokens
- Disentangled Image Colorization via Global Anchors
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2. User Guided Image Colorization
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2.1 Based on scribble
- [Petalica Paint (Online service)
- Manga colorization
- LazyBrush: Flexible Painting Tool for Hand-drawn Cartoons - implementation) |
- Outline Colorization through Tandem Adversarial Networks
- Real-Time User-Guided Image Colorization with Learned Deep Priors - deep-colorization) [[code2]](https://github.com/richzhang/colorization-pytorch) |
- Scribbler: Controlling Deep Image Synthesis with Sketch and Color
- User-Guided Deep Anime Line Art Colorization with Conditional Adversarial Networks
- Two-stage Sketch Colorization
- User-Guided Line Art Flat Filling with Split Filling Mechanism
- Dual Color Space Guided Sketch Colorization
- iColoriT: Towards Propagating Local Hint to the Right Region in Interactive Colorization by Leveraging Vision Transformer
- [link
- iColoriT: Towards Propagating Local Hint to the Right Region in Interactive Colorization by Leveraging Vision Transformer
- LGA-Net: Learning Local and Global Affinities for Sparse Scribble based Image Colorization - Net-ICCV-2025) |
- User-Guided Deep Anime Line Art Colorization with Conditional Adversarial Networks
- Auto-painter: Cartoon Image Generation from Sketch by Using Conditional Generative Adversarial Networks
- Two-stage Sketch Colorization
- Delaunay Painting: Perceptual Image Colouring from Raster Contours with Gaps
- Winding Number Features for Vector Sketch Colorization
- KISSColor: Kinetic and Intuitive Stroke Stretching for Vector Drawing Colorization
- Scribbler: Controlling Deep Image Synthesis with Sketch and Color
- Manga colorization
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2.2 Based on reference image
- Comicolorization: Semi-Automatic Manga Colorization
- TextureGAN: Controlling Deep Image Synthesis with Texture Patches - TextureGAN) |
- Deep Exemplar-based Colorization - Exemplar-based-Colorization) |
- A Superpixel-based Variational Model for Image Colorization
- Automatic Example-based Image Colourisation using Location-Aware Cross-Scale Matching
- Adversarial Colorization Of Icons Based On Structure And Color Conditions - Colorization-Of-Icons-Based-On-Structure-And-Color-Conditions) |
- Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence
- Stylization-Based Architecture for Fast Deep Exemplar Colorization
- Manga Filling Style Conversion with Screentone Variational Autoencoder
- Colorization of Line Drawings with Empty Pupils
- Active Colorization for Cartoon Line Drawings
- Line Art Correlation Matching Feature Transfer Network for Automatic Animation Colorization
- Globally and Locally Semantic Colorization via Exemplar-Based Broad-GAN
- Style-Structure Disentangled Features and Normalizing Flows for Diverse Icon Colorization
- Eliminating Gradient Conflict in Reference-based Line-Art Colorization
- Semantic-Sparse Colorization Network for Deep Exemplar-based Colorization
- AnimeDiffusion: Anime Face Line Drawing Colorization via Diffusion Models - meng/AnimeDiffusion) |
- Self-driven Dual-path Learning for Reference-based Line Art Colorization under Limited Data
- Unsupervised Deep Exemplar Colorization via Pyramid Dual Non-local Attention - Net) |
- Lightweight Deep Exemplar Colorization via Semantic Attention-Guided Laplacian Pyramid
- Deep Exemplar-based Colorization - Exemplar-based-Colorization) |
- Gray2ColorNet: Transfer More Colors from Reference Image
- Yes, "Attention Is All You Need", for Exemplar based Colorization
- FlexIcon: Flexible Icon Colorization via Guided Images and Palettes
- ColorFlow: Retrieval-Augmented Image Sequence Colorization
- MangaNinja: Line Art Colorization with Precise Reference Following - vilab/MangaNinjia) [[webpage]](https://johanan528.github.io/MangaNinjia/) |
- Image Referenced Sketch Colorization Based on Animation Creation Workflow - kanata/colorizeDiffusion) |
- Cobra: Efficient Line Art COlorization with BRoAder References
- MagicColor: Multi-Instance Sketch Colorization - Zhang/MagicColor) [[webpage]](https://yinhan-zhang.github.io/color/) |
- ColorizeDiffusion: Improving Reference-Based Sketch Colorization with Latent Diffusion Model - kanata/colorizeDiffusion) |
- ColorizeDiffusion v2: Enhancing Reference-based Sketch Colorization Through Separating Utilities - kanata/colorizeDiffusion) |
- MangaDiT: Reference-Guided Line Art Colorization with Hierarchical Attention in Diffusion Transformers
- Comicolorization: Semi-Automatic Manga Colorization
- TextureGAN: Controlling Deep Image Synthesis with Texture Patches - TextureGAN) |
- Adversarial Colorization Of Icons Based On Structure And Color Conditions - Colorization-Of-Icons-Based-On-Structure-And-Color-Conditions) |
- Manga Filling Style Conversion with Screentone Variational Autoencoder
- Stylization-Based Architecture for Fast Deep Exemplar Colorization
- Towards High-resolution and Disentangled Reference-based Sketch Colorization - kanata/ColorizeDiffusionXL) |
- Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence
- TopoColor: Topology-Aware Region Correspondence for Line Art Colorization
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2.3 Based on palette
- Example-Based Colourization Via Dense Encoding Pyramids - based-Colorization-via-Dense-Encoding-pyramids) |
- Palette-based Photo Recoloring
- SketchDeco: Decorating B&W Sketches with Colour - code) [[webpage]](https://chaitron.github.io/SketchDeco/) |
- Coloring with Words: Guiding Image Colorization Through Text-based Palette Generation - davian/Text2Colors/) |
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- Exploring Palette based Color Guidance in Diffusion Models
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- SketchDeco: Training-Free Latent Composition for Precise Sketch Colourisation - code) [[webpage]](https://chaitron.github.io/SketchDeco/) |
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
- PalGAN: Image Colorization with Palette Generative Adversarial Networks
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2.4 Based on language or text
- Diffusing Colors: Image Colorization with Text Guided Diffusion
- Coloring with Words: Guiding Image Colorization Through Text-based Palette Generation - davian/Text2Colors/) |
- Language-Based Image Editing with Recurrent Attentive Models - Lab/LBIE) |
- Learning to Color from Language
- Tag2Pix: Line Art Colorization Using Text Tag With SECat and Changing Loss - gui) |
- Line Art Colorization Based on Explicit Region Segmentation - L-C/ColorizationWithRegion) |
- L-CoIns: Language-based Colorization with Instance Awareness
- L-CAD: Language-based Colorization with Any-level Descriptions - CAD) |
- Adding Conditional Control to Text-to-Image Diffusion Models
- COCO-LC: Colorfulness Controllable Language-based Colorization - LC/) [[code]](https://github.com/lyf1212/COCO-LC/) |
- Controllable Image Colorization with Instance-aware Texts and Masks
- Language-Based Image Editing with Recurrent Attentive Models - Lab/LBIE) |
- Learning to Color from Language
- Tag2Pix: Line Art Colorization Using Text Tag With SECat and Changing Loss - gui) |
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2.5 Multi-modal
- UniColor: A Unified Framework for Multi-Modal Colorization with Transformer
- Interactive Deep Colorization Using Simultaneous Global and Local Inputs
- Two-Step Training: Adjustable Sketch Colourization via Reference Image and Text Tag - kanata/sketch_colorizer) |
- Control Color: Multimodal Diffusion-based Interactive Image Colorization - Color) [[project]](https://zhexinliang.github.io/Control_Color/) |
- Versatile Vision Foundation Model for Image and Video Colorization
- OmniColor: A Unified Framework for Multi-modal Lineart Colorization
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2.6 Interactive Colorization
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3. Human-AI Collaborated Colorization System
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3. Techniques of Improving Image Colorization
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2.6 Interactive Colorization
- Deep Edge-Aware Interactive Colorization against Color-Bleeding Effects - enhancing-colorization/) [[code(metric)]](https://github.com/niceDuckgu/CDR)|
- Line Art Colorization Based on Explicit Region Segmentation - L-C/ColorizationWithRegion) |
- FlatGAN: A Holistic Approach for Robust Flat-Coloring in High-Definition with Understanding Line Discontinuity
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4. Video Colorization
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4.0 Survey
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4.1 Automatically
- Fully Automatic Video Colorization with Self-Regularization and Diversity - Automatic-Video-Colorization-with-Self-Regularization-and-Diversity) |
- VCGAN: Video Colorization With Hybrid Generative Adversarial Network
- ColorSurge: Bringing Vibrancy and Efficiency to Automatic Video Colorization via Dual-Branch Fusion
- Fully Automatic Video Colorization with Self-Regularization and Diversity - Automatic-Video-Colorization-with-Self-Regularization-and-Diversity) |
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4.2 Based on reference
- Switchable Temporal Propagation Network
- Tracking Emerges by Colorizing Videos
- Deep Exemplar-based Video Colorization - Exemplar-based-Video-Colorization) |
- DeepRemaster: Temporal Source-Reference Attention Networks for Comprehensive Video Enhancement
- Reference-Based Video Colorization with Spatiotemporal Correspondence
- The Animation Transformer: Visual Correspondence via Segment Matching
- Line Art Correlation Matching Feature Transfer Network for Automatic Animation Colorization
- Reference-Based Deep Line Art Video Colorization
- BiSTNet: Semantic Image Prior Guided Bidirectional Temporal Feature Fusion for Deep Exemplar-based Video Colorization
- Exemplar-based Video Colorization with Long-term Spatiotemporal Dependency
- ColorMNet: A Memory-based Deep Spatial-Temporal Feature Propagation Network for Video Colorization
- ToonCrafter: Generative Cartoon Interpolation
- Deep Sketch-guided Cartoon Video Inbetweening
- Learning Inclusion Matching for Animation Paint Bucket Colorization
- Paint Bucket Colorization Using Anime Character Color Design Sheets
- LVCD: Reference-based Lineart Video Colorization with Diffusion Models
- AniDoc: Animation Creation Made Easier - meng.github.io/AniDoc_demo/) [[code]](https://github.com/yihao-meng/AniDoc) |
- SketchColour: Channel Concat Guided DiT-based Sketch-to-Colour Pipeline for 2D Animation
- AnimeColor: Reference-based Animation Colorization with Diffusion Transformers
- ToonComposer: Streamlining Cartoon Production with Generative Post-Keyframing - li.github.io/project/tooncomposer) [[code]](https://github.com/TencentARC/ToonComposer) |
- DACoN: DINO for Anime Paint Bucket Colorization with Any Number of Reference Images
- A Unified Framework for Industrial Cel-Animation Colorization with Temporal-Structural Awareness
- LongAnimation: Long Animation Generation with Dynamic Global-Local Memory - makers.github.io/long_animation_web/) |
- DeepRemaster: Temporal Source-Reference Attention Networks for Comprehensive Video Enhancement
- Switchable Temporal Propagation Network
- Tracking Emerges by Colorizing Videos
- Deep Exemplar-based Video Colorization - Exemplar-based-Video-Colorization) |
- TimeColor: Flexible Reference Colorization via Temporal Concatenation
- Reference-Based Deep Line Art Video Colorization
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4.3 Based on scribble
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4.4 Based on text
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4.5 Based on palette
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4.6 Multimodal
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Programming Languages
Categories
Sub Categories
2.2 Based on reference image
40
1.2 Papers
37
4.2 Based on reference
29
2.1 Based on scribble
22
2.3 Based on palette
21
2.4 Based on language or text
14
2.6 Interactive Colorization
6
2.5 Multi-modal
6
4.1 Automatically
4
4.4 Based on text
3
1.1 Software / Demo
3
4.0 Survey
1
4.6 Multimodal
1
4.3 Based on scribble
1
4.5 Based on palette
1