Fashion Meets Computer Vision: a Survey
Fashion Meets Computer Vision: A Survey WEN-HUANG CHENG, National Chiao Tung University and National Chung Hsing University SIJIE SONG, Peking University CHIEH-YUN CHEN, National Chiao Tung University SHINTAMI CHUSNUL HIDAYATI, Institut Teknologi Sepuluh Nopember JIAYING LIU*, Peking University 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. CCS Concepts: • General and reference Surveys and overviews; • Computing methodologies Artificial intelligence; Computer vision; Computer vision problems; Image segmentation; Object detection; Object recognition; Object identification; Matching. Additional Key Words and Phrases: Intelligent fashion, fashion detection, fashion analysis, fashion synthesis, fashion recommendation ACM Reference Format: Wen-Huang Cheng, Sijie Song, Chieh-Yun Chen, Shintami Chusnul Hidayati, and Jiaying Liu. 2021. Fashion Meets Computer Vision: A Survey. 1, 1 (January 2021), 37 pages. https://doi.org/10.1145/nnnnnnn.nnnnnnn 1 INTRODUCTION Fashion is how we present ourselves to the world. The way we dress and makeup defines our unique style and distinguishes us from other people.
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