Abstract
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.
BibTeX
@inproceedings{runway2realwayWACV15,
title = {Runway to Realway: Visual Analysis of Fashion},
author = {Sirion Vittayakorn and Kota Yamaguchi and Alexander C. Berg and Tamara L. Berg},
year = {2015},
booktitle = {WACV}
}
Download
| Dataset | Size | Description |
| Runway | 760MB | Metadata with image URLs of runway dataset v0.2 |
