Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/25738| Title: | SVTON: Simplified Virtual Try-On |
| Authors: | Islam, T Miron, A Liu, X Li, Y |
| Keywords: | Virtual Try-on (VTON);generative adversarial network (GAN);U-Net;segmentation;Affine Transform |
| Issue Date: | 12-Dec-2022 |
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
| Citation: | Islam, T. et al. (2022) 'SVTON: Simplified Virtual Try-On', 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), Bahamas, 12-14 December, pp. 1 - 6. |
| URI: | https://bura.brunel.ac.uk/handle/2438/25738 |
| Other Identifiers: | ORCID iDs: Alina Miron https://orcid.org/0000-0002-0068-4495; Xiaohui Liu https://orcid.org/0000-0003-1589-1267; Yongmin Li https://orcid.org/0000-0003-1668-2440. |
| Appears in Collections: | Dept of Computer Science Embargoed Research Papers |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Embargoed until publication | 1.01 MB | Adobe PDF | View/Open |
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