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.
翻译:时装建议通常会由于寻找适合特定用户的查询服装或取回服装的补充项目的任务而减少。 在这项工作中,我们通过根据拟议服装的风格增加一个语义层来解决这个问题。我们根据两个重要方面来建模样式:色彩组合模式背后的情绪和情感,以及所取回的服装对某类社会活动的适宜性。为了应对前者,我们依赖小林清野的颜色图像尺度,将情感模式和情绪与色彩三重联系起来。相反,通过从社会事件图像中提取服装来分析后者。总体而言,我们在艺术服装推荐框架中整合了一种样式分类器和一个事件分类器,以便根据给定的查询提出建议。