Clothing and fashion are an integral part of our everyday lives. In this paper we present an approach to studying fashion both on the runway and in more real-world settings, computationally, and at large scale, using computer vision. Our contributions include collecting a new runway dataset, designing features suitable for capturing outfit appearance, collecting human judgments of outfit similarity, and learning similarity functions on the features to mimic those judgments. We provide both intrinsic and extrinsic evaluations of our learned models to assess performance on outfit similarity prediction as well as season, year, and brand estimation. An example application tracks visual trends as runway fashions filter down to "realway" street fashions.


Sirion Vittayakorn, Kota Yamaguchi, Alexander C. Berg, Tamara L. Berg.  Runway to Realway: Visual Analysis of Fashion
Winter Conference on Applications of Computer Vision (WACV) 2015.  Hawaii.  January 2015.


  title     = {Runway to Realway: Visual Analysis of Fashion},
  author    = {Sirion Vittayakorn, Kota Yamaguchi, Alexander C. Berg, Tamara L. Berg},
  year      = {2015},
  booktitle = {WACV}


release_runway_0.1.rtar760MBMetadata with image URLs of runway dataset v0.1