Fashionpedia-Ads: Do Your Favorite Advertisements Reveal Your Fashion Taste?

التفاصيل البيبلوغرافية
العنوان: Fashionpedia-Ads: Do Your Favorite Advertisements Reveal Your Fashion Taste?
المؤلفون: Shi, Mengyun, Cardie, Claire, Belongie, Serge
سنة النشر: 2023
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
الوصف: Consumers are exposed to advertisements across many different domains on the internet, such as fashion, beauty, car, food, and others. On the other hand, fashion represents second highest e-commerce shopping category. Does consumer digital record behavior on various fashion ad images reveal their fashion taste? Does ads from other domains infer their fashion taste as well? In this paper, we study the correlation between advertisements and fashion taste. Towards this goal, we introduce a new dataset, Fashionpedia-Ads, which asks subjects to provide their preferences on both ad (fashion, beauty, car, and dessert) and fashion product (social network and e-commerce style) images. Furthermore, we exhaustively collect and annotate the emotional, visual and textual information on the ad images from multi-perspectives (abstractive level, physical level, captions, and brands). We open-source Fashionpedia-Ads to enable future studies and encourage more approaches to interpretability research between advertisements and fashion taste.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2305.02360
رقم الأكسشن: edsarx.2305.02360
قاعدة البيانات: arXiv