What Makes a Style: Experimental Analysis of Fashion Prediction

Moeko Takagi, Edgar Simo-Serra, Satoshi Iizuka, Hiroshi Ishikawa

研究成果: Conference contribution

14 被引用数 (Scopus)

抄録

In this work, we perform an experimental analysis of the differences of both how humans and machines see and distinguish fashion styles. For this purpose, we propose an expert-curated new dataset for fashion style prediction, which consists of 14 different fashion styles each with roughly 1,000 images of worn outfits. The dataset, with a total of 13,126 images, captures the diversity and complexity of modern fashion styles. We perform an extensive analysis of the dataset by benchmarking a wide variety of modern classification networks, and also perform an in-depth user study with both fashion-savvy and fashion-naïve users. Our results indicate that, although classification networks are able to outperform naive users, they are still far from the performance of savvy users, for which it is important to not only consider texture and color, but subtle differences in the combination of garments.

本文言語English
ホスト出版物のタイトルProceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ2247-2253
ページ数7
ISBN(電子版)9781538610343
DOI
出版ステータスPublished - 2017 7 1
イベント16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017 - Venice, Italy
継続期間: 2017 10 222017 10 29

出版物シリーズ

名前Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
2018-January

Other

Other16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017
CountryItaly
CityVenice
Period17/10/2217/10/29

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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