TY - GEN
T1 - The elements of fashion style
AU - Vaccaro, Kristen
AU - Shivakumar, Sunaya
AU - Ding, Ziqiao
AU - Karahalios, Karrie
AU - Kumar, Ranjitha
N1 - Publisher Copyright:
© 2016 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2016/10/16
Y1 - 2016/10/16
N2 - The outfits people wear contain latent fashion concepts capturing styles, seasons, events, and environments. Fashion theorists have proposed that these concepts are shaped by design elements such as color, material, and silhouette. While a dress may be "bohemian" because of its pattern, material, trim, or some combination thereof, it is not always clear how low-level elements translate to high-level styles. In this paper, we use polylingual topic modeling to learn latent fashion concepts jointly in two languages capturing these elements and styles. This latent topic formation enables translation between languages through topic space, exposing the elements of fashion style. The model is trained on a set of more than half a million outfits collected from Polyvore, a popular fashion-based social network. We present novel, data-driven fashion applications that allow users to express their desires in natural language just as they would to a real stylist, and produce tailored item recommendations for their fashion needs.
AB - The outfits people wear contain latent fashion concepts capturing styles, seasons, events, and environments. Fashion theorists have proposed that these concepts are shaped by design elements such as color, material, and silhouette. While a dress may be "bohemian" because of its pattern, material, trim, or some combination thereof, it is not always clear how low-level elements translate to high-level styles. In this paper, we use polylingual topic modeling to learn latent fashion concepts jointly in two languages capturing these elements and styles. This latent topic formation enables translation between languages through topic space, exposing the elements of fashion style. The model is trained on a set of more than half a million outfits collected from Polyvore, a popular fashion-based social network. We present novel, data-driven fashion applications that allow users to express their desires in natural language just as they would to a real stylist, and produce tailored item recommendations for their fashion needs.
KW - Elements
KW - Fashion
KW - Polylingual topic modeling
KW - Styles
UR - http://www.scopus.com/inward/record.url?scp=84995794097&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84995794097&partnerID=8YFLogxK
U2 - 10.1145/2984511.2984573
DO - 10.1145/2984511.2984573
M3 - Conference contribution
AN - SCOPUS:84995794097
T3 - UIST 2016 - Proceedings of the 29th Annual Symposium on User Interface Software and Technology
SP - 777
EP - 785
BT - UIST 2016 - Proceedings of the 29th Annual Symposium on User Interface Software and Technology
PB - Association for Computing Machinery
T2 - 29th Annual Symposium on User Interface Software and Technology, UIST 2016
Y2 - 16 October 2016 through 19 October 2016
ER -