Sketch Colorization

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Most implemented papers archive 2025-07-28

7 shown of 7 papers with code (9 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.

• ColorizeDiffusion v2: Enhancing Reference-based Sketch Colorization Through Separating Utilities
  9 Apr 2025 2 repositories listed
  To address this limitation, we conduct an in-depth analysis of the \textbf{carrier}, defined as the latent representation facilitating information transfer from reference to sketch.
• Image Referenced Sketch Colorization Based on Animation Creation Workflow
  27 Feb 2025 2 repositories listed
  To address these limitations, we propose a diffusion-based framework inspired by real-world animation production workflows.
• ColorizeDiffusion: Adjustable Sketch Colorization with Reference Image and Text
  2 Jan 2024 2 repositories listed
  Diffusion models have recently demonstrated their effectiveness in generating extremely high-quality images and are now utilized in a wide range of applications, including automatic sketch colorization.
• SketchyScene: Richly-Annotated Scene Sketches
  7 Aug 2018 2 repositories listed Syntology ran 1 of 11 samples · 10 unverified
  We contribute the first large-scale dataset of scene sketches, SketchyScene, with the goal of advancing research on sketch understanding at both the object and scene level.
• SketchDeco: Decorating B&W Sketches with Colour
  29 May 2024 1 repository listed
  This 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.
• Improving Sketch Colorization using Adversarial Segmentation Consistency
  20 Jan 2023 1 repository listed
  We leverage semantic image segmentation from a general-purpose panoptic segmentation network to generate an additional adversarial loss function.
• Adversarial Segmentation Loss for Sketch Colorization
  11 Feb 2021 1 repository listed
  Our loss function can be integrated to any baseline GAN model.

Syntology lines on 1 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.