智能系统学报2025，Vol.20Issue(2)：265-282,18.DOI:10.11992/tis.202312041
扩散模型在计算机视觉领域的研究现状
Research status of diffusion models in computer vision
摘要
Abstract
The diffusion model is a new generative model inspired by molecular thermodynamics.This model offers stable training and low dependence on model settings,making it a popular benchmark in computer vision.In recent years,the diffusion model has been widely applied to various tasks,yielding diverse and high-quality results compared to traditional generative models.At present,the diffusion model is a prominent method in the field of computer vision.This paper provides a comprehensive overview of the diffusion model to further stimulate its development in this do-main.First,the paper compares the advantages and disadvantages of diffusion models with other generative models and introduces the underlying mathematical principles.Then,the study presents recent efforts by researchers to improve dif-fusion models,starting with common challenges and highlighting application examples in various visual tasks.Finally,the study discusses existing issues with diffusion models and outlines potential future development trends.关键词
扩散模型/去噪扩散概率模型/分数扩散模型/深度学习/计算机视觉/图像生成/生成模型/生成对抗网络Key words
diffusion model/denoising diffusion probabilistic model/score-based generative model/deep learning/com-puter vision/image generation/generative model/generative adversarial network分类
信息技术与安全科学引用本文复制引用
管凤旭,张涵宇,路斯棋,赖海涛,杜雪,郑岩..扩散模型在计算机视觉领域的研究现状[J].智能系统学报,2025,20(2):265-282,18.基金项目
国家自然科学基金项目(62101156). （62101156）
