面向时尚推荐的计算技术：综述
Computational Technologies for Fashion Recommendation: A Survey
AI总结：
本文从技术视角系统综述时尚推荐研究，梳理其与一般推荐的差异、子任务分类、方法、数据集及局限性，并探讨未来方向及学术研究与产业需求的差距。
摘要：
时尚推荐是计算时尚研究中的一个关键研究领域，近年来在计算机视觉、多媒体和信息检索领域引起了广泛关注。由于应用的巨大需求，文献中已经提出并探索了多种时尚推荐任务，例如个性化时尚产品推荐、互补（混搭）推荐和整套穿搭推荐。持续的研究关注和进展促使我们回顾并深入理解该领域。本文从技术视角全面回顾了近年来时尚推荐的研究工作。我们首先在宏观层面介绍时尚推荐，并分析其特点以及与一般推荐任务的差异。然后，我们将不同的时尚推荐工作明确划分为若干子任务，并针对每个子任务，从问题定义、研究重点、最先进方法和局限性等方面进行重点分析。我们还总结了文献中为时尚推荐研究提出的数据集，以便为读者提供简要说明。最后，我们讨论了该领域未来研究的几个有前景的方向。总体而言，本综述系统回顾了时尚推荐研究的发展，并讨论了当前学术研究与时尚产业实际需求之间的局限性和差距。在此过程中，我们深入探讨了时尚产业如何从时尚推荐的计算技术中受益。
英文摘要：
Fashion recommendation is a key research field in computational fashion research and has attracted considerable interest in the computer vision, multimedia, and information retrieval communities in recent years. Due to the great demand for applications, various fashion recommendation tasks, such as personalized fashion product recommendation, complementary (mix-and-match) recommendation, and outfit recommendation, have been posed and explored in the literature. The continuing research attention and advances impel us to look back and in-depth into the field for a better understanding. In this paper, we comprehensively review recent research efforts on fashion recommendation from a technological perspective. We first introduce fashion recommendation at a macro level and analyse its characteristics and differences with general recommendation tasks. We then clearly categorize different fashion recommendation efforts into several sub-tasks and focus on each sub-task in terms of its problem formulation, research focus, state-of-the-art methods, and limitations. We also summarize the datasets proposed in the literature for use in fashion recommendation studies to give readers a brief illustration. Finally, we discuss several promising directions for future research in this field. Overall, this survey systematically reviews the development of fashion recommendation research. It also discusses the current limitations and gaps between academic research and the real needs of the fashion industry. In the process, we offer a deep insight into how the fashion industry could benefit from the computational technologies of fashion recommendation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
