计算机工程与应用2025，Vol.61Issue(10)：19-35,17.DOI:10.3778/j.issn.1002-8331.2409-0340
基于图像的虚拟试衣综述——从深度学习到扩散模型
Review of Image-Based Virtual Try-on:from Deep Learning to Diffusion Models
摘要
Abstract
Image-based virtual try-on,as an economical and convenient technology in the virtual try-on domain,aims to synthesize realistic fitting effects by combining model images with clothing images.It has significant applications in online shopping,fashion design,and animation.Recently,generative large models represented by diffusion models have driven new breakthroughs and transformations in the field due to their stronger generative capabilities compared to tradi-tional deep learning methods.However,there is a lack of comprehensive analysis and overview of image-based virtual try-on in the era of large models.This paper summarizes the key techniques of image-based virtual try-on,categorizes mainstream methods into three baseline processes:data preprocessing,warping generation,and try-on result generation.It also analyzes the implementation methods used in representative literature,compares major process methods,and intro-duces commonly used datasets,evaluation metrics,and loss functions in image-based virtual try-on.Finally,the paper discusses the challenges and limitations of image-based virtual try-on in the context of large models,and outlines future development and improvement directions for relevant technologies.关键词
计算机视觉/虚拟试衣/翘曲处理/图像合成/扩散模型Key words
computer vision/virtual try-on/warping treatment/image synthesis/diffusion model分类
计算机与自动化引用本文复制引用
杨浩哲,郭楠..基于图像的虚拟试衣综述——从深度学习到扩散模型[J].计算机工程与应用,2025,61(10):19-35,17.基金项目
高等学校学科创新引智计划(B16009). （B16009）
