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What is the future of fashion? Tackling this question from a data-drivenvision perspective, we propose to forecast visual style trends before theyoccur. We introduce the first approach to predict the future popularity ofstyles discovered from fashion images in an unsupervised manner. Using thesestyles as a basis, we train a forecasting model to represent their trends overtime. The resulting model can hypothesize new mixtures of styles that willbecome popular in the future, discover style dynamics (trendy vs. classic), andname the key visual attributes that will dominate tomorrow's fashion. Wedemonstrate our idea applied to three datasets encapsulating 80,000 fashionproducts sold across six years on Amazon. Results indicate that fashionforecasting benefits greatly from visual analysis, much more than textual ormeta-data cues surrounding products.

Fashion Forward: Forecasting Visual Style in Fashion