模式识别与人工智能
Wednesday, Apr. 9, 2025 Home      About Journal      Editorial Board      Instructions      Ethics Statement      Contact Us                   中文
Pattern Recognition and Artificial Intelligence  2022, Vol. 35 Issue (12): 1047-1063    DOI: 10.16451/j.cnki.issn1003-6059.202212001
Deep Learning Based Image Understanding and Its Applications Current Issue| Next Issue| Archive| Adv Search |
Image Inpainting with a Three-Stage Generative Network
SHAO Xinru1, YE Hailiang1, YANG Bing1, CAO Feilong1
1. Department of Applied Mathematics, College of Sciences, China Jiliang University, Hangzhou 310018

Download: PDF (5120 KB)   HTML (1 KB) 
Export: BibTeX | EndNote (RIS)      
Abstract  One of the research emphases of image inpainting based on deep learning is to generate color, edge and texture. However, generation methods of these three important properties need to be further improved. A three-stage generative network is proposed, and three stages tend to synthesize colors, edges and textures respectively. Specifically, the global color of the image is reconstructed in the HSV color space at the HSV color generation stage to provide color guidance for image inpainting. An edge learning framework is designed at the edge optimization stage to obtain more accurate edge information. At the texture synthesis stage, a decoder with feature bidirectional fusion is designed to enhance the details of the image. The three stages are successively connected, and each stage plays an important role in improving the performance of image inpainting. Extensive experiments demonstrate the superiority of the proposed method compared with the state-of-the-art methods.
Key wordsImage Inpainting      Generative Adversarial Networks      HSV Color Generation Model      Decoder with Bidirectional Feature Fusion     
Received: 01 November 2022     
ZTFLH: TP391  
Fund:National Natural Science Foundation of China(No.62176244,62006215), Natural Science Foundation of Zhejiang Province(No.LZ20F030001)
Corresponding Authors: CAO Feilong, Ph.D., professor. His research interests include deep learning and image processing.   
About author:: SHAO Xinru, master student. His research interests include deep learning and image processing.YE Hailiang, Ph.D., lecturer. His research interests include deep learning and image processing.YANG Bing, Ph.D., lecturer. His research interests include deep learning and image processing.
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
SHAO Xinru
YE Hailiang
YANG Bing
CAO Feilong
Cite this article:   
SHAO Xinru,YE Hailiang,YANG Bing等. Image Inpainting with a Three-Stage Generative Network[J]. Pattern Recognition and Artificial Intelligence, 2022, 35(12): 1047-1063.
URL:  
http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202212001      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2022/V35/I12/1047
Copyright © 2010 Editorial Office of Pattern Recognition and Artificial Intelligence
Address: No.350 Shushanhu Road, Hefei, Anhui Province, P.R. China Tel: 0551-65591176 Fax:0551-65591176 Email: bjb@iim.ac.cn
Supported by Beijing Magtech  Email:support@magtech.com.cn