MISC

2013年1月1日

Paper doll parsing: Retrieving similar styles to parse clothing items

Proceedings of the IEEE International Conference on Computer Vision
  • Kota Yamaguchi
  • ,
  • M. Hadi Kiapour
  • ,
  • Tamara L. Berg

開始ページ
3519
終了ページ
3526
DOI
10.1109/ICCV.2013.437

Clothing recognition is an extremely challenging problem due to wide variation in clothing item appearance, layering, and style. In this paper, we tackle the clothing parsing problem using a retrieval based approach. For a query image, we find similar styles from a large database of tagged fashion images and use these examples to parse the query. Our approach combines parsing from: pre-trained global clothing models, local clothing models learned on the fly from retrieved examples, and transferred parse masks (paper doll item transfer) from retrieved examples. Experimental evaluation shows that our approach significantly outperforms state of the art in parsing accuracy. © 2013 IEEE.

リンク情報
DOI
https://doi.org/10.1109/ICCV.2013.437
URL
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84898779488&origin=inward
ID情報
  • DOI : 10.1109/ICCV.2013.437
  • SCOPUS ID : 84898779488

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