Please use this identifier to cite or link to this item: https://doi.org/10.1145/3343031.3350607
Title: Automatic Fashion Knowledge Extraction from Social Media
Authors: Yunshan Ma 
Lizi Liao 
Tat-Seng Chua 
Keywords: Fashion Analysis
Fashion Knowledge Extraction
Issue Date: 21-Oct-2019
Citation: Yunshan Ma, Lizi Liao, Tat-Seng Chua (2019-10-21). Automatic Fashion Knowledge Extraction from Social Media. ACM MM 2019 : 2223-2224. ScholarBank@NUS Repository. https://doi.org/10.1145/3343031.3350607
Abstract: 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. © 2019 Association for Computing Machinery.
Source Title: ACM MM 2019
URI: https://scholarbank.nus.edu.sg/handle/10635/167782
ISBN: 9781450000000
DOI: 10.1145/3343031.3350607
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