Few-shot exemplar-driven inpainting with parameter-efficient diffusion fine-tuning
Regular Papers|Updated:2025-09-04
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Few-shot exemplar-driven inpainting with parameter-efficient diffusion fine-tuning
Enhanced Publication
基于参数高效扩散微调的少样本参考图驱动图像补全
“In the realm of image generation, researchers have made significant strides with text-to-image diffusion models, particularly in the area of image inpainting. A new approach, which employs a plug-and-play low-rank adaptation module and GPT-4V prompting, has been developed to enhance exemplar-driven inpainting, offering a tool for customized object inpainting with improved fidelity. This advancement lays a foundation for the construction of more personalized image inpainting systems.”
Frontiers of Information Technology & Electronic EngineeringVol. 26, Issue 8, Pages: 1428-1440(2025)
Affiliations:
1.Key Laboratory of Optoelectronics Information Technology, Ministry of Education, School of Precision Instruments and Optoelectronic Engineering, Tianjin University, Tianjin 300072, China
2.State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210008, China