LE QUY DON
Technical University
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Large scale fashion search system with deep learning and quantization indexing

Dinh, T.H. and Van, T.P. and Thanh, T.M. and Thanh, H.N. and Hoang, A.P. (2018) Large scale fashion search system with deep learning and quantization indexing. In: 9th International Symposium on Information and Communication Technology, SoICT 2018, 6 December 2018 through 7 December 2018.

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Abstract

Recently, the problems of clothes recognition and clothing item retrieval have attracted a number of researchers, due to its practical and potential values to real-world applications. The main task is to automatically find relevant clothing items given a single user-provided image without any extra metadata. Most existing systems mainly focus on clothes classification, attribute prediction, and matching the exact in-shop items with the query image. However, these systems do not mention the problem of latency period or the amount of time that users have to wait when they query an image until the query results are retrieved. In this paper, we propose a fashion search system that automatically recognizes clothes and suggests multiple similar clothing items with an impressively low latency. Through extensive experiments, it is verified that our system outperforms almost existing systems in term of clothing item retrieval time. © 2018 Association for Computing Machinery.

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculties > Faculty of Information Technology
Identification Number: 10.1145/3287921.3287964
Uncontrolled Keywords: Deep learning; Indexing (of information); Safety devices; Clothes recognition; Existing systems; Image similarity; Potential values; Query images; Query results; Retrieval time; Search system; Search engines
Additional Information: Conference code: 143217. Language of original document: English.
URI: http://eprints.lqdtu.edu.vn/id/eprint/9491

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