Fashion Meets Computer Vision

Journal: ACM Computing Surveys • • Association for Computing Machinery • ISSN: 0360-0300

Abstract

Fashion is the way we present ourselves to the world and has become one of the world’s largest industries. Fashion, mainly conveyed by vision, has thus attracted much attention from computer vision researchers in recent years. Given the rapid development, this article provides a comprehensive survey of more than 200 major fashion-related works covering four main aspects for enabling intelligent fashion: (1) Fashion detection includes landmark detection, fashion parsing, and item retrieval; (2) Fashion analysis contains attribute recognition, style learning, and popularity prediction; (3) Fashion synthesis involves style transfer, pose transformation, and physical simulation; and (4) Fashion recommendation comprises fashion compatibility, outfit matching, and hairstyle suggestion. For each task, the benchmark datasets and the evaluation protocols are summarized. Furthermore, we highlight promising directions for future research.

Subjects & Keywords

How to Cite this Article

Wen-Huang Cheng, Sijie Song, Chieh-Yun Chen, et al. (2021). "Fashion Meets Computer Vision". ACM Computing Surveys. https://doi.org/10.1145/3447239