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AI tool GapFill streamlines anime colorization by filling unpainted regions

By PulseAugur Editorial · [1 sources] ·

Researchers have developed GapFill, a novel tool designed to automate the detection and filling of small unpainted regions in anime colorization workflows. This deep-learning method analyzes surrounding areas to suggest appropriate fill colors, specifically tailored for the flat-color nature of anime-style images. A user study involving 13 professional colorists indicated that GapFill improved performance and usability compared to conventional methods, though user trust and contextual ambiguity of colors were noted as important factors for adoption. AI

IMPACT This tool could significantly speed up the digital colorization process in anime production, potentially lowering costs and increasing output.

RANK_REASON The cluster contains a research paper detailing a new AI method and tool for a specific application domain. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI tool GapFill streamlines anime colorization by filling unpainted regions

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31 / 100
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Tool
The cluster contains a research paper detailing a new AI method and tool for a specific application domain. [lever_c_demoted from research: ic=1 ai=1.0]
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paper, product
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Masahiro Kono, Akinobu Maejima, Yuki Koyama, Yotam Sechayk, Takeo Igarashi ·

    No Pixel Left Behind: Filling Gaps in Anime Colorization

    arXiv:2609.00800v1 Announce Type: cross Abstract: Animation production workflows often involve digital colorization of line art, where small unpainted regions ("gaps") frequently occur and remain an underexplored challenge. We conducted a formative study in Japanese animation (an…

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