Video super-resolution with inverse recurrent net and hybrid local fusion
文献类型：期刊论文
| 作者 | Li, Dingyi3,4; Wang, Zengfu1,2 ; Yang, Jian3,4
|
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2022-06-07 |
| 卷号 | 489 |
| 关键词 | Video super-resolution Bidirectional recurrent convolutional neural network Sliding-window Local fusion |
| ISSN号 | 0925-2312 |
| DOI | 10.1016/j.neucom.2022.03.019 |
| 通讯作者 | Li, Dingyi(lidingyi@njust.edu.cn) |
| 英文摘要 | Video super-resolution converts low-resolution videos to sharp high-resolution ones. In order to make better use of temporal information in video super-resolution, we design inverse recurrent net and hybrid local fusion. We concatenate the original low-resolution input sequence and its inverse sequence repeatedly. The new sequence is viewed as a combination of different stages, and is processed sequentially by using orent net. The outputs of the last two stages in opposite directions are fused to generate the final images. Our inverse recurrent net can extract more bidirectional temporal information in the input sequence, without adding parameter to the corresponding unidirectional recurrent net. We also propose a hybrid local fusion method which uses parallel fusion and cascade fusion for incorporating slidingwindow-based methods into our inverse recurrent net. Extensive experimental results demonstrate the effectiveness of the proposed inverse recurrent net and hybrid local fusion, in terms of visual quality and quantitative evaluations. The code will be released at https://github.com/5ofwind. (c) 2022 Elsevier B.V. All rights reserved. |
| 资助项目 | National Natural Science Foundation of China[62002168] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000782510100004 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/128595]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Li, Dingyi |
| 作者单位 | 1.Univ Sci & Technol China, Dept Automation, Hefei 230027, Anhui, Peoples R China 2.Chinese Acad Sci, Inst Intelligent Machines, Hefei 230031, Anhui, Peoples R China 3.Nanjing Univ Sci & Technol, Sch Comp Sci & Engn, Jiangsu Key Lab Image & Video Understanding Socia, Nanjing 210094, Jiangsu, Peoples R China 4.Nanjing Univ Sci & Technol, Sch Comp Sci & Engn, PCA Lab,Minist Educ, Key Lab Intelligent Percept & Syst High Dimens In, Nanjing 210094, Jiangsu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Dingyi,Wang, Zengfu,Yang, Jian. Video super-resolution with inverse recurrent net and hybrid local fusion[J]. NEUROCOMPUTING,2022,489. |
| APA | Li, Dingyi,Wang, Zengfu,&Yang, Jian.(2022).Video super-resolution with inverse recurrent net and hybrid local fusion.NEUROCOMPUTING,489. |
| MLA | Li, Dingyi,et al."Video super-resolution with inverse recurrent net and hybrid local fusion".NEUROCOMPUTING 489(2022). |
入库方式： OAI收割
来源：合肥物质科学研究院
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