  What is the future of fashion? Tackling this question from a data-driven
vision perspective, we propose to forecast visual style trends before they
occur. We introduce the first approach to predict the future popularity of
styles discovered from fashion images in an unsupervised manner. Using these
styles as a basis, we train a forecasting model to represent their trends over
time. The resulting model can hypothesize new mixtures of styles that will
become popular in the future, discover style dynamics (trendy vs. classic), and
name the key visual attributes that will dominate tomorrow's fashion. We
demonstrate our idea applied to three datasets encapsulating 80,000 fashion
products sold across six years on Amazon. Results indicate that fashion
forecasting benefits greatly from visual analysis, much more than textual or
meta-data cues surrounding products.
