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Deep garment image matting for a virtual try-on system

Research output: Chapter in Book/Report/Conference proceedingConference contribution

To improve online shopping experience, many fashion retailers try to provide high quality garment images, capturing fine details as well as various opacities. A skilled operator can deliver a satisfactory result using manual segmentation tools, but it is challenging to scale up this process to address seasonal demands. To balance the quality and the processing cost, we investigate the use of a deep learning based matting technique that can produce a high quality alpha map from an approximate garment segmentation. The proposed model adopts the deep image matting model, but we replace the refinement network with a sequence of recursive convolutional network (RCN) units. Our main motivation for this modification is that the fine garment details created by different materials are represented better with the mixture of the image features from different scales. Therefore, we need to construct deeper convolutional layers for better scale analysis but we also need to maintain the number of unknowns low as producing training data is expensive. The proposed RCN based refinement network can address these conflicting restrictions well and our experiments demonstrate that it can achieve a lower training loss and produce better prediction results than the baseline refinement model under the same training condition.
Original languageEnglish
Title of host publicationIEEE International Conference on Computer Vision Workshops (ICCVW)
PublisherInstitute of Electrical and Electronics Engineers
Number of pages4
ISBN (Electronic)978-1-7281-5024-6
ISBN (Print)978-1-7281-5024-6
DOIs
Publication statusPublished - 5 Mar 2020
EventIEEE International Conference on Computer Vision - Seoul, Korea, Republic of
Duration: 27 Oct 20192 Nov 2019
http://iccv2019.thecvf.com/

Publication series

NameProceedings of the International Conference on Computer Vision Workshop (ICCVW)
PublisherIEEE
ISSN (Print)2473-9936
ISSN (Electronic)2473-9944

Workshop

WorkshopIEEE International Conference on Computer Vision
Abbreviated titleICCV 2019
CountryKorea, Republic of
CitySeoul
Period27/10/192/11/19
Internet address

Documents

  • PID6097537

    Rights statement: © 2020 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.

    Accepted author manuscript (Post-print), 2.37 MB, PDF document

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