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Review Article | Open Access

Machine learning for digital try-on: Challenges and progress

University of Maryland, College Park, MD 20785, USA
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Abstract

Digital try-on systems for e-commerce have the potential to change people’s lives and provide notable economic benefits. However, their development is limited by practical constraints, such as accurate sizing of the body and realism of demonstrations. We enumerate three open challenges remaining for a complete and easy-to-use try-on system that recent advances in machine learningmake increasingly tractable. For each, we describethe problem, introduce state-of-the-art approaches, and provide future directions.

Keywords

machine learningdigital try-ongarmentmodelinghuman body estimationmaterial modeling

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Computational Visual Media
Volume 7 Issue 2,
June 2021
Pages 159-167
DOI: 10.1007/s41095-020-0189-1

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Cite this article:
Liang J, Lin MC. Machine learning for digital try-on: Challenges and progress. Computational Visual Media, 2021, 7(2): 159-167. https://doi.org/10.1007/s41095-020-0189-1

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Received: 24 June 2020
Accepted: 21 July 2020
Published: 23 October 2020
© The Author(s) 2020

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