Fashion is intertwined with external cultural factors, but identifying these links remains a manual process limited to only the most salient phenomena. We propose a data-driven approach to identify specific cultural factors affecting the clothes people wear. Using large-scale datasets of news articles and vintage photos spanning a century, we introduce a multi-modal statistical model to detect influence relationships between happenings in the world and people's choice of clothing. Furthermore, we apply our model to improve the concrete vision tasks of visual style forecasting and photo timestamping on two datasets. Our work is a first step towards a computational, scalable, and easily refreshable approach to link culture to clothing.
翻译:时装与外部文化因素交织在一起,但确定这些联系仍是一个人工过程,仅限于最突出的现象。我们提议采用数据驱动方法,确定影响人们穿衣的具体文化因素。我们使用一个世纪的新闻文章和老相片的大规模数据集,采用多模式统计模型,以发现世界上发生的事情和人们选择服装之间的关系。此外,我们运用我们的模型,改进视觉风格预报和两个数据集的摄影时间戳破的具体愿景任务。我们的工作是朝着将文化与服装联系起来的计算、可扩展和易于更新的方法迈出的第一步。