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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 42, 2025 No. 2
623-629

Local customized image editing algorithm based on diffusion model fine tuning

Du Jiajun1
Lan Hong1
Wang Chaofan2
1. College of Information Engineering, Jiangxi University of Science & Technology, Ganzhou Jiangxi 341000, China
2. Guangdong Provincial Key Laboratory of Diabetology, Dept. of Endocrinology & Metabolism, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
DOI: 10.19734/j.issn.1001-3695.2024.04.0175

Abstract

In response to the limitations of existing image editing methods based on diffusion models, such as inflexible control over editing regions and the generation of personalized content, this paper proposed a locally customized image editing algorithm based on fine-tuning of diffusion models. Leveraging a stable diffusion model as the foundational framework, the method initially learnt concept embeddings from a given set of images and word embeddings. To enhance training efficiency and mitigate overfitting caused by limited data, the method reduced the number of training parameters during fine-tuning by analyzing the degree of parameter changes across layers during training. Subsequently, in the joint segmentation model for local selection, it obtained mask features to precisely identify the boundaries of the editing area, thereby preserving the content of non-editing areas. Finally, it jointly input the reference image, mask features, and condition text descriptions associated with customized concepts into the fine-tuning model, enabling precise generation of customized content in the editing area and enhancing flexibility in generating user-customized content in the editing area. Experimental results on the DreamBench dataset demonstrate that compared to other state-of-the-art methods, the method achieves the best experimental results, with improvements of 12.2% and 13.9% in CLIP-T and MS-SSIM, respectively. This indicates that the method outperforms mainstream methods in text alignment and structural consistency, providing users with a more accurate personalized concept image editing approach.

Foundation Support

广州市科技计划资助项目(2023A04J1087)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.04.0175
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 2
Section: Technology of Graphic & Image
Pages: 623-629
Serial Number: 1001-3695(2025)02-042-0623-07

Publish History

[2025-02-05] Printed Article

Cite This Article

杜佳俊, 兰红, 王超凡. 基于扩散模型微调的局部定制图像编辑算法 [J]. 计算机应用研究, 2025, 42 (2): 623-629. (Du Jiajun, Lan Hong, Wang Chaofan. Local customized image editing algorithm based on diffusion model fine tuning [J]. Application Research of Computers, 2025, 42 (2): 623-629. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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