Summary of Multimodal Markup Document Models For Graphic Design Completion, by Kotaro Kikuchi et al.
Multimodal Markup Document Models for Graphic Design Completion
by Kotaro Kikuchi, Naoto Inoue, Mayu Otani, Edgar Simo-Serra, Kota Yamaguchi
First submitted to arxiv on: 27 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Multimedia (cs.MM)
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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 paper proposes multimodal markup document models (MarkupDM) that can generate both markup language and images within interleaved multimodal documents. Unlike existing vision-and-language multimodal models, our MarkupDM tackles unique challenges critical to graphic design tasks: generating partial images that contribute to the overall appearance, often involving transparency and varying sizes, and understanding the syntax and semantics of markup languages, which play a fundamental role as a representational format of graphic designs. To address these challenges, we design an image quantizer to tokenize images of diverse sizes with transparency and modify a code language model to process markup languages and incorporate image modalities. We evaluate our approach on three graphic design completion tasks: generating missing attribute values, images, and texts in graphic design templates. Results demonstrate the effectiveness of our MarkupDM for graphic design tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about a new way to make computers generate both words and pictures within documents. This can be useful for designing graphics like logos or brochures. The computer needs to understand how to create partial images that fit together, as well as how to read and write special codes used in graphic design. The researchers created a system that can do this by combining two existing technologies: one that processes words and another that processes pictures. They tested their system on three tasks related to designing graphics and found it was very effective. |
Keywords
» Artificial intelligence » Language model » Semantics » Syntax
