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Deep Learning-Based Image and Video Inpainting: A Survey

文献类型：期刊论文

作者Quan, Weize1,2; Chen, Jiaxi1,2; Liu, Yanli3; Yan, Dong-Ming1,2; Wonka, Peter4
刊名INTERNATIONAL JOURNAL OF COMPUTER VISION
出版日期2024-01-19
页码34
ISSN号0920-5691
关键词Image inpainting Video inpainting Deep learning Content generation
DOI10.1007/s11263-023-01977-6
通讯作者Yan, Dong-Ming(yandongming@gmail.com)
英文摘要Image and video inpainting is a classic problem in computer vision and computer graphics, aiming to fill in the plausible and realistic content in the missing areas of images and videos. With the advance of deep learning, this problem has achieved significant progress recently. The goal of this paper is to comprehensively review the deep learning-based methods for image and video inpainting. Specifically, we sort existing methods into different categories from the perspective of their high-level inpainting pipeline, present different deep learning architectures, including CNN, VAE, GAN, diffusion models, etc., and summarize techniques for module design. We review the training objectives and the common benchmark datasets. We present evaluation metrics for low-level pixel and high-level perceptional similarity, conduct a performance evaluation, and discuss the strengths and weaknesses of representative inpainting methods. We also discuss related real-world applications. Finally, we discuss open challenges and suggest potential future research directions.
WOS关键词REMOVAL ; TEXTURE ; NETWORK ; CLASSIFICATION ; FRAMEWORK ; SCALE
资助项目National Natural Science Foundation of China[62102418] ; National Natural Science Foundation of China[62172415] ; National Natural Science Foundation of China[61972271] ; Beijing Science and Technology Plan Project[Z231100005923033] ; Open Project Program of National Key Laboratory of Fundamental Science on Synthetic Vision, Sichuan University[2021SCUVS002]
WOS研究方向Computer Science
语种英语
出版者SPRINGER
WOS记录号WOS:001144998000001
资助机构National Natural Science Foundation of China ; Beijing Science and Technology Plan Project ; Open Project Program of National Key Laboratory of Fundamental Science on Synthetic Vision, Sichuan University
源URL[http://ir.ia.ac.cn/handle/173211/54792]  
专题多模态人工智能系统全国重点实验室
通讯作者Yan, Dong-Ming
作者单位1.Chinese Acad Sci, Inst Automat, MAIS, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
3.Sichuan Univ, Coll Comp Sci, Chengdu, Peoples R China
4.King Abdullah Univ Sci & Technol, Comp Elect & Math Sci & Engn Div, Thuwal, Saudi Arabia
推荐引用方式
GB/T 7714		 Quan, Weize,Chen, Jiaxi,Liu, Yanli,et al. Deep Learning-Based Image and Video Inpainting: A Survey[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION,2024:34.
APA Quan, Weize,Chen, Jiaxi,Liu, Yanli,Yan, Dong-Ming,&Wonka, Peter.(2024).Deep Learning-Based Image and Video Inpainting: A Survey.INTERNATIONAL JOURNAL OF COMPUTER VISION,34.
MLA Quan, Weize,et al."Deep Learning-Based Image and Video Inpainting: A Survey".INTERNATIONAL JOURNAL OF COMPUTER VISION (2024):34.

入库方式： OAI收割

来源：自动化研究所

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