Fashion is perceived as a meaningful way of self-expressing that people use for different purposes. It seems to be an integral part of every person in modern societies, from everyday life to exceptional events and occasions. Fashionable products are highly demanded, and consequently, fashion is perceived as a desirable and profitable industry. Although this massive demand for fashion products provides an excellent opportunity for companies to invest in fashion-related sectors, it also faces different challenges in answering their customer needs. Fashion recommender systems have been introduced to address these needs. This thesis aims to provide deeper insight into the fashion recommender system domain by conducting a comprehensive literature review on more than 100 papers in this field focusing on image-based fashion recommender systems considering computer vision advancements. Justifying fashion domain-specific characteristics, the subtle notions of this domain and their relevancy have been conceptualized. Four main tasks in image-based fashion recommender systems have been recognized, including cloth-item retrievals, Complementary item recommendation, Outfit recommendation, and Capsule wardrobes. An evolvement trajectory of image-based fashion recommender systems concerning computer vision advancements has been illustrated consists of three main eras and the most recent developments. Finally, a comparison between traditional computer vision techniques and deep learning-based has been made. Although the main objective of this literature review was to perform a comprehensive, integrated overview of researches in this field, there is still a need for conducting further studies considering image-based fashion recommender systems from a more practical perspective.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-87519 |
Date | January 2021 |
Creators | shirkhani, shaghayegh |
Publisher | Luleå tekniska universitet, Institutionen för system- och rymdteknik |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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