Browse State-of-the-Art › Image Colorization
Image Colorization
63 papers with code · 3 benchmarks · 3 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
3 leaderboard tables shown for this task, 3 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| ImageNet (4 rows) | DDRM | Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model | code | Syntology ran 12 of 23 samples · 11 unverified | Compare |
| CelebA (3 rows) | DDRM | Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model | code | Syntology ran 12 of 23 samples · 11 unverified | Compare |
| NIR2RGB VCIP Challange Dataset (3 rows) | ColorMamba | ColorMamba: Towards High-quality NIR-to-RGB Spectral Translation with Mamba | code | — | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
3 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
1 subtask in the archive's task tree.
Most implemented papers archive 2025-07-28
30 shown of 63 papers with code (127 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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30 Mar 2017 190 repositories listed Syntology ran 6 of 31 samples · 25 unverified · 6 pointer-only (licence)Image-to-image translation is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image using a training set of aligned image pairs.
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28 Mar 2016 39 repositories listed Syntology ran 32 of 73 samples · 41 unverified · 41 pointer-only (licence)We embrace the underlying uncertainty of the problem by posing it as a classification task and use class-rebalancing at training time to increase the diversity of colors in the result.
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9 Dec 2017 16 repositories listedWe review some of the most recent approaches to colorize gray-scale images using deep learning methods.
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4 Jul 2019 7 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)We demonstrate these properties for the tasks of MNIST digit generation and image colorization.
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14 Mar 2018 7 repositories listedOver the last decade, the process of automatic image colorization has been of significant interest for several application areas including restoration of aged or degraded images.
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20 Feb 2023 6 repositories listedRecent large-scale generative models learned on big data are capable of synthesizing incredible images yet suffer from limited controllability.
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3 Oct 2024 4 repositories listedImage-to-image translation is a topic in computer vision that has a vast range of use cases ranging from medical image translation, such as converting MRI scans to CT scans or to other MRI contrasts, to image…
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1 Dec 2022 4 repositories listed Syntology ran 12 of 23 samples · 11 unverifiedMost existing Image Restoration (IR) models are task-specific, which can not be generalized to different degradation operators.
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9 Jul 2021 4 repositories listedUnsupervised deep learning has recently demonstrated the promise of producing high-quality samples.
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4 Jul 2021 3 repositories listedDeep neural networks for automatic image colorization often suffer from the color-bleeding artifact, a problematic color spreading near the boundaries between adjacent objects.
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15 Jun 2021 3 repositories listed Syntology ran 2 of 9 samples · 7 unverifiedIn this paper, we present a fast exemplar-based image colorization approach using color embeddings named Color2Embed.
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21 Apr 2019 3 repositories listedThis paper proposes a method to colorize line art frames in an adversarial setting, to create temporally coherent video of large anime by improving existing image to image translation methods.
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8 May 2017 3 repositories listedThe system directly maps a grayscale image, along with sparse, local user "hints" to an output colorization with a Convolutional Neural Network (CNN).
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1 Jul 2016 3 repositories listedWe present a novel technique to automatically colorize grayscale images that combines both global priors and local image features.
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22 Mar 2016 3 repositories listed Syntology ran 1 of 1 samples · 0 unverifiedThis intermediate output can be used to automatically generate a color image, or further manipulated prior to image formation.
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23 Jul 2024 2 repositories listed Syntology ran 21 of 27 samples · 6 unverified · 5 pointer-only (licence)Recent studies on inverse problems have proposed posterior samplers that leverage the pre-trained diffusion models as powerful priors.
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5 Mar 2021 2 repositories listed Syntology ran 2 of 2 samples · 0 unverifiedThe high dimensionality of images presents architecture and sampling-efficiency challenges for likelihood-based generative models.
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8 Feb 2021 2 repositories listedWe present the Colorization Transformer, a novel approach for diverse high fidelity image colorization based on self-attention.
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3 Nov 2020 2 repositories listedOur method, though partly reliant on the quality of the generative network inversion, is competitive with state-of-the-art supervised and task-specific restoration methods.
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21 May 2020 2 repositories listed Syntology ran 0 of 7 samples · 7 unverifiedPrevious methods leverage the deep neural network to map input grayscale images to plausible color outputs directly.
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21 May 2025 1 repository listedSpecifically, we use 335 input-reference pairs from previous research, achieving an FID of 95.
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29 Mar 2025 1 repository listedAccurate rooftop detection from historical aerial imagery is vital for examining long-term urban development and human settlement patterns.
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19 Mar 2025 1 repository listedIn view of the lack of a comprehensive review of language-based colorization literature, we conduct a thorough analysis and benchmarking.
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1 Oct 2024 1 repository listed Syntology ran 4 of 10 samples · 6 unverifiedPhoto-realistic image restoration algorithms are typically evaluated by distortion measures (e.
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15 Aug 2024 1 repository listedTo explore global long-range dependencies and local context for efficient spectral translation, we introduce learnable padding tokens to enhance the distinction of image boundaries and prevent potential confusion within…
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29 May 2024 1 repository listedThis paper introduces a novel approach to sketch colourisation, inspired by the universal childhood activity of colouring and its professional applications in design and story-boarding.
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25 Apr 2024 1 repository listedThe NIR-to-RGB spectral domain translation is a formidable task due to the inherent spectral mapping ambiguities within NIR inputs and RGB outputs.
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8 Dec 2023 1 repository listedThis paper presents a novel approach to human image colorization by fine-tuning the InstructPix2Pix model, which integrates a language model (GPT-3) with a text-to-image model (Stable Diffusion).
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24 Oct 2023 1 repository listedExtensive experiments illustrate that the proposed FoalGAN is not only effective for appearance learning of small objects, but also outperforms other image translation methods in terms of semantic preservation and edge…
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6 Jul 2023 1 repository listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)Our method can optionally condition on the source texture in part or all of the image.
Syntology lines on 11 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections