mlsanityData to 13 Oct 2026

Manga Rescreening with Interpretable Screentone Representation

arXiv 2306.04114 ↗First posted 7 Jun 2023cs.CV eess.IVcited by 0

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Abstract (arXiv)

The process of adapting or repurposing manga pages is a time-consuming task that requires manga artists to manually work on every single screentone region and apply new patterns to create novel screentones across multiple panels. To address this issue, we propose an automatic manga rescreening pipeline that aims to minimize the human effort involved in manga adaptation. Our pipeline automatically recognizes screentone regions and generates novel screentones with newly specified characteristics (e.g., intensity or type). Existing manga generation methods have limitations in understanding and synthesizing complex tone- or intensity-varying regions. To overcome these limitations, we propose a novel interpretable representation of screentones that disentangles their intensity and type features, enabling better recognition and synthesis of screentones. This interpretable screentone representation reduces ambiguity in recognizing intensity-varying regions and provides fine-grained controls during screentone synthesis by decoupling and anchoring the type or the intensity feature. Our proposed method is demonstrated to be effective and convenient through various experiments, showcasing the superiority of the newly proposed pipeline with the interpretable screentone representations.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 16 of its 41 references that are in the map. First posted on arXiv 7 Jun 2023.

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16 of 41 references.

References · 16

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4 more
  1. 2018Isolating Sources of Disentanglement in Variational Autoencoderscited by 167
  2. 2018Disentangled Sequential Autoencodercited by 118
  3. 2015Deep filter banks for texture recognition, description, and segmentationcited by 19
  4. 2019Inspecting and Interacting with Meaningful Music Representations using VAEcited by 4

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