Author(s)

Yekuan He ¹, Peiqi Yuan ²

Affiliation(s)

¹ Institute of International Education, Guangzhou College of Technology and Business, Foshan, 528100, China
² Physics Department, Capital Normal University, Beijing, 100080, China

Corresponding Author

Yekuan He

ABSTRACT

With the advancement of AI-generated image technology, the field of icon design has increasingly incorporated computational methods as design references. Compared to direct design by human designers, AI technology can significantly reduce time and labor costs. In response to this, this research propose the High-Quality Customized Model (HCM) for controllable stylized icon design. This research introduce the Icon-ControlNet module to achieve precise control over icon generation, ensuring high levels of customization. Additionally, article employ the IconIC module to reduce computational resource consumption and enhance generation efficiency. This article have also constructed the IconData dataset, comprising 25,000 finely annotated medium-sized images. Through extensive ablation experiments, the results were evaluated by FID and IS, effectively demonstrating the advantages of HCM in terms of icon clarity, style transfer, and diversity. This model provides a novel solution for the automation and personalization of icon design.

KEYWORDS

Diffusion model, Icon Design, HCM model, Image Generation

CITE THIS PAPER

Yekuan He, Peiqi Yuan, HCM: Icon art design based on diffusion model. Journal of Artificial Intelligence Practice (2024) Vol. 7: 25-36. DOI: http://dx.doi.org/10.23977/jaip.2024.070404.

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