Automatic fashion knowledge extraction from social media

Fashion knowledge plays a pivotal role in helping people in their dressing. In this paper, we present a novel system to automatically harvest fashion knowledge from social media. It unifies three tasks of occasion, person and clothing discovery from multiple modalities of images, texts and metadata....

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Bibliographic Details
Main Authors: MA, Yunshan, LIAO, Lizi, CHUA, Tat-Seng
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2019
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Online Access:https://ink.library.smu.edu.sg/sis_research/7721
https://ink.library.smu.edu.sg/context/sis_research/article/8724/viewcontent/Automatic_Fashion_Knowledge_Extraction_from_Social_Media.pdf
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Institution: Singapore Management University
Language: English
Description
Summary:Fashion knowledge plays a pivotal role in helping people in their dressing. In this paper, we present a novel system to automatically harvest fashion knowledge from social media. It unifies three tasks of occasion, person and clothing discovery from multiple modalities of images, texts and metadata. A contextualized fashion concept learning model is applied to leverage the rich contextual information for improving the fashion concept learning performance. At the same time, to counter the label noise within training data, we employ a weak label modeling method to further boost the performance. We build a website to demonstrate the quality of fashion knowledge extracted by our system.