Khan, MUG, Tariq, A, Saba, T, Rehman, A and Kolivand, H (2022) VCFN: Virtual Cloth Fitting Try-On Network. IT Professional, 24 (6). pp. 20-26. ISSN 1520-9202

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Abstract

Virtual cloth fitting network has an increasing demand with a growing online shopping trend to map target clothes on reference subject. Previous research depicts limitations in the generation of promising deformed clothes on the wearer's body while retaining the design features of cloth-like logo, text, and wrinkles. The proposed model first learns thin-plate spline transformations to warp images according to body shape, followed by a try-on module. The former model combines deformed cloth with a rendered image to generate a composition mask and outputs target body without blurry clothes while preserving critical requirements of the wearer. Experiments are performed on the Zalando dataset and the model produces fine richer details and promised generalized results.

Item Type:	Article
Additional Information:	© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords:	0806 Information Systems; Information Systems
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Divisions:	Computer Science & Mathematics
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
SWORD Depositor:	A Symplectic
Date Deposited:	21 Jun 2023 09:47
Last Modified:	02 Nov 2023 12:14
DOI or ID number:	10.1109/MITP.2022.3204063
URI:	https://researchonline.ljmu.ac.uk/id/eprint/19966

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