论文标题
基于风格和社交活动的时尚推荐
Fashion Recommendation Based on Style and Social Events
论文作者
论文摘要
时尚推荐通常被拒绝，因为它是找到适合给定用户的查询服装或检索适合特定服装的互补物品的任务。在这项工作中，我们通过根据建议的敷料的样式添加附加语义层来解决问题。我们根据两个重要方面的样式建模：颜色组合图案背后的情绪和情感以及给定类型的社交事件所检索的服装的适当性。为了解决前者，我们依靠Shigenobu Kobayashi的颜色图像量表，这将情感模式和情绪与色彩三元组相关联。相反，通过从社交事件的图像中提取服装来分析后者。总体而言，我们集成了一个最先进的服装推荐框架样式分类器和事件分类器，以便在给定的查询上建议建议。
Fashion recommendation is often declined as the task of finding complementary items given a query garment or retrieving outfits that are suitable for a given user. In this work we address the problem by adding an additional semantic layer based on the style of the proposed dressing. We model style according to two important aspects: the mood and the emotion concealed behind color combination patterns and the appropriateness of the retrieved garments for a given type of social event. To address the former we rely on Shigenobu Kobayashi's color image scale, which associated emotional patterns and moods to color triples. The latter instead is analyzed by extracting garments from images of social events. Overall, we integrate in a state of the art garment recommendation framework a style classifier and an event classifier in order to condition recommendation on a given query.
