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The evolution of clothing styles and their migration across the world isintriguing, yet difficult to describe quantitatively. We propose to discoverand quantify fashion influences from everyday images of people wearing clothes.We introduce an approach that detects which cities influence which other citiesin terms of propagating their styles. We then leverage the discovered influencepatterns to inform a forecasting model that predicts the popularity of anygiven style at any given city into the future. Demonstrating our idea withGeoStyle---a large-scale dataset of 7.7M images covering 44 major world cities,we present the discovered influence relationships, revealing how cities exertand receive fashion influence for an array of 50 observed visual styles.Furthermore, the proposed forecasting model achieves state-of-the-art resultsfor a challenging style forecasting task, showing the advantage of groundingvisual style evolution both spatially and temporally.

From Paris to Berlin: Discovering Fashion Style Influences Around the World