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http://dx.doi.org/10.9723/jksiis.2020.25.2.011

An Improved VTON (Virtual-Try-On) Algorithm using a Pair of Cloth and Human Image  

Minar, Matiur Rahman (서울과학기술대학교 전기정보공학과)
Tuan, Thai Thanh (서울과학기술대학교 전기정보공학과)
Ahn, Heejune (서울과학기술대학교 전기정보공학과)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.25, no.2, 2020 , pp. 11-18 More about this Journal
Abstract
Recently, a series of studies on virtual try-on (VTON) using images have been published. A comparison study analyzed representative methods, SCMM-based non-deep learning method, deep learning based VITON and CP-VITON, using costumes and user images according to the posture and body type of the person, the degree of occlusion of the clothes, and the characteristics of the clothes. In this paper, we tackle the problems observed in the best performing CP-VTON. The issues tackled are the problem of segmentation of the subject, pixel generation of un-intended area, missing warped cloth mask and the cost function used in the learning, and limited the algorithm to improve it. The results show some improvement in SSIM, and significantly in subjective evaluation.
Keywords
Virtual-try-on; Deep-learning; Human representation; Quality improvement; Loss function;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
연도 인용수 순위
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