The fashion industry is on the verge of an unprecedented change. The implementation of machine learning, computer vision, and artificial intelligence (AI) in fashion applications is opening lots of new opportunities for this industry. This paper provides a comprehensive survey on this matter, categorizing more than 580 related articles into 22 well-defined fashion-related tasks. Such structured task-based multi-label classification of fashion research articles provides researchers with explicit research directions and facilitates their access to the related studies, improving the visibility of studies simultaneously. For each task, a time chart is provided to analyze the progress through the years. Furthermore, we provide a list of 86 public fashion datasets accompanied by a list of suggested applications and additional information for each.
翻译:时装业正处在前所未有的变革的边缘,在时装应用中实施机器学习、计算机视觉和人工智能(AI)给这一行业带来了许多新的机会,本文件提供了关于这一问题的全面调查,将580多条相关文章分类为22项明确界定的时装相关任务,这种结构化的基于任务的多标签的时装研究文章分类为研究人员提供了明确的研究方向,并方便他们同时获得相关研究,提高了研究的能见度。为每项任务提供了一份时间表,以分析这些年来的进展。此外,我们还提供了一份86个公共时装数据集的清单,并附有一份推荐应用清单和每项应用的补充信息。