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We investigate the challenges of style transfer in multi-modal visualnarratives. Among static visual narratives such as comics and manga, there aredistinct visual styles in terms of presentation. They include style featuresacross multiple dimensions, such as panel layout, size, shape, and color. Theyinclude both visual and text media elements. The layout of both text and mediaelements is also significant in terms of narrative communication. Thesequential transitions between panels are where readers make inferences aboutthe narrative world. These feature differences provide an interesting challengefor style transfer in which there are distinctions between the processing offeatures for each modality. We introduce the notion of comprehension-preservingstyle transfer (CPST) in such multi-modal domains. CPST requires not onlytraditional metrics of style transfer but also metrics of narrativecomprehension. To spur further research in this area, we present an annotateddataset of comics and manga and an initial set of algorithms that utilizeseparate style transfer modules for the visual, textual, and layout parameters.To test whether the style transfer preserves narrative semantics, we evaluatethis algorithm through visual story cloze tests inspired by work incomputational cognition of narrative systems. Understanding the connectionbetween style and narrative semantics provides insight for applications rangingfrom informational brochure designs to data storytelling.

CPST: Comprehension-Preserving Style Transfer for Multi-Modal Narratives