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You can Try without Visiting: A Comprehensive Survey on Virtually Try-on Outfits
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  • Hajer Ghodhbani ,
  • Adel Alimi ,
  • Mohamed Neji ,
  • Imran Razzak
Hajer Ghodhbani
National Engineering School of Sfax (ENIS), National Engineering School of Sfax (ENIS)

Corresponding Author:[email protected]

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Adel Alimi
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Mohamed Neji
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Imran Razzak
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Abstract

Our work aims to conduct a comprehensive literature review of deep learning methods applied in the fashion industry and, especially, the image-based virtual fitting task by citing research works published in the last years. We have summarized their challenges, their main frameworks, the popular benchmark datasets, and the different evaluation metrics. Also, some promising future research directions are discussed to propose improvements in this research field.
Jun 2022Published in Multimedia Tools and Applications volume 81 issue 14 on pages 19967-19998. 10.1007/s11042-022-12802-6