Human shape and clothing estimation has gained significant prominence in
various domains, including online shopping, fashion retail, augmented reality
(AR), virtual reality (VR), and gaming. The visual representation of human
shape and clothing has become a focal point for computer vision researchers in
recent years. This paper presents a comprehensive survey of the major works in
the field, focusing on four key aspects: human shape estimation, fashion
generation, landmark detection, and attribute recognition. For each of these
tasks, the survey paper examines recent advancements, discusses their strengths
and limitations, and qualitative differences in approaches and outcomes. By
exploring the latest developments in human shape and clothing estimation, this
survey aims to provide a comprehensive understanding of the field and inspire
future research in this rapidly evolving domain.

该研究综述了人体形状和服装估计领域的重要工作，主要关注人体形状估计、时尚生成、关键点检测和属性识别四个方面，并讨论了最新发展、优点、局限以及方法和结果的定性差异，旨在提供对该领域的全面理解并激励未来的研究。