Outfit Recommendation System Based on Deep Learning

DOI

10.2991/iccia-17.2017.26How to use a DOI?

Keywords

outfit recommendation, deep learning, dataset.

Abstract

In this paper, we propose an outfit recommendation system based on deep learning. Our goal is to use the system not only to judge an outfit if it is good or not but also to recommend good outfit to users when it is given a pool of cloth items. Our proposed model includes two parts: one is feature extractor based on ResNet-50, and the other is a binary classifier which is to classify the outfits into good ones and bad ones. Since our model is based on deep learning, it is necessary to use huge data to train the model. We collected a dataset which consists of 409,776 outfits with 644,192 items from the famous fashion website called Polyvore.com. With this dataset, we trained our model and the performance of it is over 84%. And our model can also recommend daily outfit to users

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ying Huang
AU  - Tao Huang
PY  - 2016/07
DA  - 2016/07
TI  - Outfit Recommendation System Based on Deep Learning
BT  - Proceedings of the 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)
PB  - Atlantis Press
SP  - 164
EP  - 168
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-17.2017.26
DO  - 10.2991/iccia-17.2017.26
ID  - Huang2016/07
ER  -