CVPR2021

Exploiting Aliasing for Manga Restoration

Minshan Xie         Menghan Xia         Tien-Tsin Wong

Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2021),
June 2021, pp. 13400-13409.


Abstract

As a popular entertainment art form, manga enriches the line drawings details with bitonal screentones. However, manga resources over the Internet usually show screentone artifacts because of inappropriate scanning/rescaling resolution. In this paper, we propose an innovative two-stage method to restore quality bitonal manga from degraded ones. Our key observation is that the aliasing induced by downsampling bitonal screentones can be utilized as informative clues to infer the original resolution and screentones. First, we predict the target resolution from the degraded manga via the Scale Estimation Network (SE-Net) with spatial voting scheme. Then, at the target resolution, we restore the region-wise bitonal screentones via the Manga Restoration Network (MR-Net) discriminatively, depending on the degradation degree. Specifically, the original screentones are directly restored in pattern-identifiable regions, and visually plausible screentones are synthesized in pattern-agnostic regions. Quantitative evaluation on synthetic data and visual assessment on real-world cases illustrate the effectiveness of our method.







Paper

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Supplementary Material

Source Code

BibTex:

                @inproceedings{xie2021exploiting,
                  author    = {Minshan Xie, Menghan Xia, and Tien-Tsin Wong},
                  title     = {Exploiting Aliasing for Manga Restoration},
                  booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
                  year      = {2021},
                  month     = {June},
                  pages     = {13400-13409}
                }