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European Conference on Computer Vision

ECCV 2020: Computer Vision – ECCV 2020 pp 137–154Cite as

DanbooRegion: An Illustration Region Dataset

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12358))

Abstract

Region is a fundamental element of various cartoon animation techniques and artistic painting applications. Achieving satisfactory region is essential to the success of these techniques. Motivated to assist diversiform region-based cartoon applications, we invite artists to annotate regions for in-the-wild cartoon images with several application-oriented goals: (1) To assist image-based cartoon rendering, relighting, and cartoon intrinsic decomposition literature, artists identify object outlines and eliminate lighting-and-shadow boundaries. (2) To assist cartoon inking tools, cartoon structure extraction applications, and cartoon texture processing techniques, artists clean-up texture or deformation patterns and emphasize cartoon structural boundary lines. (3) To assist region-based cartoon digitalization, clip-art vectorization, and animation tracking applications, artists inpaint and reconstruct broken or blurred regions in cartoon images. Given the typicality of these involved applications, this dataset is also likely to be used in other cartoon techniques. We detail the challenges in achieving this dataset and present a human-in-the-loop workflow namely Feasibility-based Assignment Recommendation (FAR) to enable large-scale annotating. The FAR tends to reduce artist trails-and-errors and encourage their enthusiasm during annotating. Finally, we present a dataset that contains a large number of artistic region compositions paired with corresponding cartoon illustrations. We also invite multiple professional artists to assure the quality of each annotation.

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Notes

  1. 1.

    Although we encourage artists to follow these suggestions, they are not absolutely constrained to do so, in order to capture a realistic distribution of artistic region compositions.

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Author information

Authors and Affiliations

  1. Style2Paints Research, Suzhou, China

    Lvmin Zhang

  2. Soochow University, Suzhou, China

    Lvmin Zhang, Yi Ji & Chunping Liu

Authors
  1. Lvmin Zhang
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  2. Yi Ji
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  3. Chunping Liu
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Corresponding authors

Correspondence to Yi Ji or Chunping Liu .

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Editors and Affiliations

  1. University of Oxford, Oxford, UK

    Andrea Vedaldi

  2. Graz University of Technology, Graz, Austria

    Horst Bischof

  3. University of Freiburg, Freiburg im Breisgau, Germany

    Thomas Brox

  4. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Jan-Michael Frahm

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Zhang, L., Ji, Y., Liu, C. (2020). DanbooRegion: An Illustration Region Dataset. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, JM. (eds) Computer Vision – ECCV 2020. ECCV 2020. Lecture Notes in Computer Science(), vol 12358. Springer, Cham. https://doi.org/10.1007/978-3-030-58601-0_9

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  • DOI: https://doi.org/10.1007/978-3-030-58601-0_9

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