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arXiv 2004.01316cs.CVcs.SI

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

The University of Texas at Austin(德克萨斯大学奥斯汀分校);Facebook AI Research(Facebook人工智能研究院)

Ziad Al-Halah, Kristen Grauman

英文摘要:

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

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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