  As a popular comic style, manga offers a unique impression by utilizing a
rich set of bitonal patterns, or screentones, for illustration. However,
screentones can easily be contaminated with visual-unpleasant aliasing and/or
blurriness after resampling, which harms its visualization on displays of
diverse resolutions. To address this problem, we propose the first manga
retargeting method that synthesizes a rescaled manga image while retaining the
screentone in each screened region. This is a non-trivial task as accurate
region-wise segmentation remains challenging. Fortunately, the rescaled manga
shares the same region-wise screentone correspondences with the original manga,
which enables us to simplify the screentone synthesis problem as an
anchor-based proposals selection and rearrangement problem. Specifically, we
design a novel manga sampling strategy to generate aliasing-free screentone
proposals, based on hierarchical grid-based anchors that connect the
correspondences between the original and the target rescaled manga.
Furthermore, a Recurrent Proposal Selection Module (RPSM) is proposed to
adaptively integrate these proposals for target screentone synthesis. Besides,
to deal with the translation insensitivity nature of screentones, we propose a
translation-invariant screentone loss to facilitate the training convergence.
Extensive qualitative and quantitative experiments are conducted to verify the
effectiveness of our method, and notably compelling results are achieved
compared to existing alternative techniques.
