Document Type
Conference Paper
Publication Date
10-12-2020
Publication Source
MM '20: Proceedings of the 28th ACM International Conference on Multimedia
Abstract
In this work, we introduce a practical system which synthesizes an appealing image from natural language descriptions such that the generated image should maintain the aesthetic level of photographs. Our proposed method takes the text from the end-users via a user-friendly interface and produces a set of different label maps via the primary generator PG. Then, choosing a subset from the label maps set is performed through the primary aesthetic appreciation PAA. Next, our subset of label maps is fed into the accessory generator AG, which is the state-of-the-art image-to-image translation. Last but not least, our subset of generated images is ranked via the accessory aesthetic appreciation AAA, and the most appealing image is produced.
Inclusive pages
4485–4487
ISBN/ISSN
9781450379885
Copyright
© 2020 Copyright is held by the owner/author(s).
Publisher
Association for Computing Machinery
Keywords
Image synthesis, center anchor point, mask dataset, image aesthetics, composition rules
Sponsoring Agency
The first author would like to thank Umm Al-Qura University, in Saudi Arabia, for the continuous support. We also gratefully acknowledge the support of NVIDIA Corporation with the donation of GPU used for this research
eCommons Citation
Baraheem, Samah Saeed; Le, Trung-Nghia; and Nguyen, Tam V., "Text-to-Image Synthesis via Aesthetic Layout" (2020). Computer Science Faculty Publications. 225.
https://ecommons.udayton.edu/cps_fac_pub/225
Comments
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.