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Intelligent Artistic Typography: A Comprehensive Review of Artistic Text Design and Generation (2407.14774v1)

Published 20 Jul 2024 in cs.CV, cs.AI, and cs.GR

Abstract: Artistic text generation aims to amplify the aesthetic qualities of text while maintaining readability. It can make the text more attractive and better convey its expression, thus enjoying a wide range of application scenarios such as social media display, consumer electronics, fashion, and graphic design. Artistic text generation includes artistic text stylization and semantic typography. Artistic text stylization concentrates on the text effect overlaid upon the text, such as shadows, outlines, colors, glows, and textures. By comparison, semantic typography focuses on the deformation of the characters to strengthen their visual representation by mimicking the semantic understanding within the text. This overview paper provides an introduction to both artistic text stylization and semantic typography, including the taxonomy, the key ideas of representative methods, and the applications in static and dynamic artistic text generation. Furthermore, the dataset and evaluation metrics are introduced, and the future directions of artistic text generation are discussed. A comprehensive list of artistic text generation models studied in this review is available at https://github.com/williamyang1991/Awesome-Artistic-Typography/.

Citations (2)

Summary

  • The paper provides a comprehensive taxonomy of artistic text generation techniques, categorizing methods for both static and dynamic designs.
  • It emphasizes two main approaches: artistic text stylization for visual effects and semantic typography for meaning-driven deformations.
  • The review outlines key datasets, evaluation metrics, and a roadmap for future research to advance aesthetic text design.

The paper "Intelligent Artistic Typography: A Comprehensive Review of Artistic Text Design and Generation" provides an extensive overview of artistic text generation, focusing on enhancing the aesthetic quality of text while maintaining readability. This field intersects with various application areas, such as social media, consumer electronics, fashion, and graphic design.

The authors categorize artistic text generation into two main areas: artistic text stylization and semantic typography.

Artistic Text Stylization: This involves applying effects like shadows, outlines, colors, glows, and textures to text. These enhancements aim to make the text more visually appealing while preserving its legibility.

Semantic Typography: This approach involves deforming characters to enhance their visual representation, often inspired by the semantic meaning of the text. It emphasizes the transformation of character shapes to convey a deeper connection with the text's meaning.

The paper introduces a taxonomy of these techniques, summarizing key methods and applications for both static and dynamic artistic text creation.

In addition to exploring existing methodologies, the authors discuss available datasets and evaluation metrics for assessing artistic text generation. They provide a roadmap for future research, highlighting potential advancements in this field.

The paper also compiles a comprehensive list of artistic text generation models on their GitHub repository, which serves as a valuable resource for researchers exploring this area.

Overall, the review serves as a crucial reference for understanding both the current landscape and future directions in artistic text generation.

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