题名 | Face super resolution with a high frequency highway |
作者 | |
通讯作者 | Zeng, Dan |
发表日期 | 2024-08-01
|
DOI | |
发表期刊 | |
ISSN | 1751-9659
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EISSN | 1751-9667
|
摘要 | ["Face shape priors such as landmarks, heatmaps, and parsing maps are widely used to improve face super resolution (SR). It is observed that face priors provide locations of high-frequency details in key facial areas such as the eyes and mouth. However, existing methods fail to effectively exploit the high-frequency information by using the priors as either constraints or inputs. This paper proposes a novel high frequency highway (H2F${\\rm H}_2{\\rm F}$) framework to better utilize prior information for face SR, which dynamically decomposes the final SR face into a coarse SR face and a high frequency (HF) face. The coarse SR face is reconstructed from a low-resolution face via a texture branch, using only pixel-wise reconstruction loss. Meanwhile, the HF face is directly generated from face priors via an HF branch that employs the proposed inception-hourglass model. As a result, H2F${\\rm H}_2{\\rm F}$ allows the face priors to have a direct impact on the SR face by adding the outputs of both branches as the final result and provides an extra face editing function. Extensive experiments show that H2F${\\rm H}_2{\\rm F}$ significantly outperforms state-of-the-art face SR methods, is general for different texture branch models and face priors, and is robust to dataset mismatch and pose variations.","The method is the first to construct an HF face directly from the face priors via a high-frequency highway for face super-resolution, making it easy to understand the HF information gain. The method dynamically decomposes a final SR face into a coarse SR face and an HF face, making it possible to prevent the smoothing of HF details during learning. image"] |
关键词 | |
相关链接 | [来源记录] |
收录类别 | |
语种 | 英语
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学校署名 | 第一
; 通讯
|
资助项目 | National Natural Science Foundation of China[62206123]
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WOS研究方向 | Computer Science
; Engineering
; Imaging Science & Photographic Technology
|
WOS类目 | Computer Science, Artificial Intelligence
; Engineering, Electrical & Electronic
; Imaging Science & Photographic Technology
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WOS记录号 | WOS:001285597400001
|
出版者 | |
来源库 | Web of Science
|
引用统计 | |
成果类型 | 期刊论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/803310 |
专题 | 工学院_计算机科学与工程系 南方科技大学 |
作者单位 | 1.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen, Peoples R China 2.Southern Univ Sci & Technol, Res Inst Trustworthy Autonomous Syst, Shenzhen, Peoples R China 3.Univ Twente, Fac EEMCS, Enschede, Netherlands |
第一作者单位 | 计算机科学与工程系; 南方科技大学 |
通讯作者单位 | 计算机科学与工程系; 南方科技大学 |
第一作者的第一单位 | 计算机科学与工程系 |
推荐引用方式 GB/T 7714 |
Zeng, Dan,Jiang, Wen,Yan, Xiao,et al. Face super resolution with a high frequency highway[J]. IET IMAGE PROCESSING,2024.
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APA |
Zeng, Dan.,Jiang, Wen.,Yan, Xiao.,Fu, Weibao.,Shen, Qiaomu.,...&Tang, Bo.(2024).Face super resolution with a high frequency highway.IET IMAGE PROCESSING.
|
MLA |
Zeng, Dan,et al."Face super resolution with a high frequency highway".IET IMAGE PROCESSING (2024).
|
条目包含的文件 | 条目无相关文件。 |
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