Machines. Technologies. Materials.
Vol. 18 (2024), Issue 7, pg(s) 234-234

TECHNOLOGIES

Text-to-Image generative models for enhanced composite guitar production

  • 1 Warsaw University of Technology, Institute of Radioelectronics and Multimedia Technology, Warsaw, Poland; ; Sieć Badawcza Rafał Perz, Warsaw, Poland
  • 2 Warsaw University of Technology, Institute of Aeronautics and Applied Mechanics, Warsaw, Poland; Sieć Badawcza Rafał Perz, Warsaw, Poland
  • 3 Warsaw University of Technology, Institute of Radioelectronics and Multimedia Technology, Warsaw, Poland;

Abstract

This paper explores the application of text-to-image generative models in the production of composite guitars. By converting textual descriptions into detailed visual designs, we create the design process, enhance customization options, and improve overall production efficiency, offering a novel approach to guitar manufacturing

Keywords

References

  1. – Goodfellow, Ian, et al. "Generative adversarial networks." Communications of the ACM 63.11 (2020): 139-144.
  2. – Tao, Ming, et al. "Df-gan: A simple and effective baseline for text-to-image synthesis." Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2022.
  3. – Rombach, Robin, et al. "High-resolution image synthesis with latent diffusion models." Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2022.
  4. – Cimpoi, Mircea, et al. "Describing textures in the wild." Proceedings of the IEEE conference on computer vision and pattern recognition. 2014.

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