Applied and Computational Engineering
- The Open Access Proceedings Series for Conferences
Proceedings of the 4th International Conference on Computing and Data Science (CONF-CDS 2022)
Series Vol. 2 , 22 March 2023
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Style-based Image Manipulation Using the StyleGAN2-Ada Architecture
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Abstract
Style-based image manipulation is to fuse the types of two arbitrary images, which is a popular task in computer vision. StyleGAN is a sophisticated architecture for generating images of high qualities. The framework allows the generator to operate on a latent space that is disentangled and allows us to do scale-specific manipulation on the semantic information of the generated images. In this paper, the author managed to fuse the styles of two given images on a controllable degree. The resultant images have natural appearances approximating real human portraits. Our method provides qualitative results for style-fusion of two given images, which achieves satisfy. Since StyleGAN offers an unraveled latent space representing disentangled semantics, the author hopes to use it on tasks like GAN inversion and manipulate images in a fine-grained control, which is the future work.
Keywords
Style-based image manipulation, StyleGAN, GAN inversion.
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 4th International Conference on Computing and Data Science (CONF-CDS 2022)
- ISBN (Print)
- 978-1-915371-19-5
- ISBN (Online)
- 978-1-915371-20-1
- Published Date
- 22 March 2023
- Series
- Applied and Computational Engineering
- ISSN (Print)
- 2755-2721
- ISSN (Online)
- 2755-273X
- DOI
- 10.54254/2755-2721/2/20220563
- Copyright
- 22 March 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited