  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 paper 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.
