Summary of A Customizable Generator For Comic-style Visual Narrative, by Yi-chun Chen et al.
A Customizable Generator for Comic-Style Visual Narrative
by Yi-Chun Chen, Arnav Jhala
First submitted to arxiv on: 14 Dec 2023
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Human-Computer Interaction (cs.HC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This AI research paper presents a novel visual narrative generator that draws inspiration from comic-authoring idioms to create comic content. By integrating theoretical concepts, the generator makes sequential decisions across multiple layers, including panel composition, object positions, and narrative elements. The system’s architecture is informed by theories on comics, such as Cohn’s narrative grammar and McCloud’s panel transitions. Additionally, the generator incorporates photographic compositions inspired by the rule of thirds and overlays symbols based on action verbs using an ontology. Example outputs demonstrate the variety of generated comics across different settings. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This AI research paper makes it possible for computers to create comic strips! The system uses special rules from comic book theory to decide what goes into each panel, like where objects are placed and how scenes change. It’s a big project that brings together many ideas from experts in the field. By looking at verbs like “run” or “jump,” the computer can add fun symbols to the comics too! The system is really good at making different kinds of comic strips for different settings, which could be useful for lots of things. |
