Fashionpedia-Ads: Do Your Favorite Advertisements Reveal Your Fashion Taste?
Research output: Working paper › Preprint › Research
Standard
Fashionpedia-Ads : Do Your Favorite Advertisements Reveal Your Fashion Taste? / Shi, Mengyun; Cardie, Claire; Belongie, Serge.
arXiv.org, 2023.Research output: Working paper › Preprint › Research
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - UNPB
T1 - Fashionpedia-Ads
T2 - Do Your Favorite Advertisements Reveal Your Fashion Taste?
AU - Shi, Mengyun
AU - Cardie, Claire
AU - Belongie, Serge
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
M3 - Preprint
BT - Fashionpedia-Ads
PB - arXiv.org
ER -
ID: 384867756