DFAN: Dual Feature Aggregation Network for Lightweight Image Super-Resolution | |
Li, Shang1,2; Zhang, Guixuan2; Luo, Zhengxiong1,2; Liu, Jie2 | |
刊名 | Wireless Communications and Mobile Computing |
2022 | |
期号 | 2022页码:8116846 |
关键词 | Super-resolution Lightweight Feature aggregation |
英文摘要 | With the power of deep learning, super-resolution (SR) methods enjoy a dramatic boost in performance. However, they usually have a large model size and high computational complexity, which hinders the application in devices with limited memory and computing power. Some lightweight SR methods solve this issue by directly designing shallower architectures, but it will adversely affect the representation capability of convolutional neural networks. To address this issue, we propose the dual feature aggregation strategy for image SR. It enhances feature utilization via feature reuse, which largely improves the representation ability while only introducing marginal computational cost. Thus, a smaller model could achieve better cost-effectiveness with the dual feature aggregation strategy. Specifically, it consists of Local Aggregation Module (LAM) and Global Aggregation Module (GAM). LAM and GAM work together to further fuse hierarchical features adaptively along the channel and spatial dimensions. In addition, we propose a compact basic building block to compress the model size and extract hierarchical features in a more efficient way. Extensive experiments suggest that the proposed network performs favorably against state-of-the-art SR methods in terms of visual quality, memory footprint, and computational complexity. |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/47445] |
专题 | 数字内容技术与服务研究中心_新媒体服务与管理技术 |
通讯作者 | Liu, Jie |
作者单位 | 1.University of Chinese Academy of Sciences 2.Institute of Automation, Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Li, Shang,Zhang, Guixuan,Luo, Zhengxiong,et al. DFAN: Dual Feature Aggregation Network for Lightweight Image Super-Resolution[J]. Wireless Communications and Mobile Computing,2022(2022):8116846. |
APA | Li, Shang,Zhang, Guixuan,Luo, Zhengxiong,&Liu, Jie.(2022).DFAN: Dual Feature Aggregation Network for Lightweight Image Super-Resolution.Wireless Communications and Mobile Computing(2022),8116846. |
MLA | Li, Shang,et al."DFAN: Dual Feature Aggregation Network for Lightweight Image Super-Resolution".Wireless Communications and Mobile Computing .2022(2022):8116846. |
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