Single depth map super-resolution via a deep feedback network

doi:10.1142/S0219691320500721

CORC > 长春光学精密机械与物理研究所 > 中国科学院长春光学精密机械与物理研究所

	Single depth map super-resolution via a deep feedback network
	G. Wu; Y. Wang and S. Li
刊名	International Journal of Wavelets, Multiresolution and Information Processing
	2021
卷号	19 期号:2
ISSN号	2196913
DOI	10.1142/S0219691320500721
英文摘要	Existing depth map-based super-resolution (SR) methods cannot achieve satisfactory results in depth map detail restoration. For example, boundaries of the depth map are always difficult to reconstruct effectively from the low-resolution (LR) guided depth map particularly at big magnification factors. In this paper, we present a novel super-resolution method for single depth map by introducing a deep feedback network (DFN), which can effectively enhance the feature representations at depth boundaries that utilize iterative up-sampling and down-sampling operations, building a deep feedback mechanism by projecting high-resolution (HR) representations to low-resolution spatial domain and then back-projecting to high-resolution spatial domain. The deep feedback (DF) block imitates the process of image degradation and reconstruction iteratively. The rich intermediate high-resolution features effectively tackle the problem of depth boundary ambiguity in depth map super-resolution. Extensive experimental results on the benchmark datasets show that our proposed DFN outperforms the state-of-the-art methods. 2021 World Scientific Publishing Company.
URL标识	查看原文
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/65633]
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	G. Wu,Y. Wang and S. Li. Single depth map super-resolution via a deep feedback network[J]. International Journal of Wavelets, Multiresolution and Information Processing,2021,19(2).
APA	G. Wu,&Y. Wang and S. Li.(2021).Single depth map super-resolution via a deep feedback network.International Journal of Wavelets, Multiresolution and Information Processing,19(2).
MLA	G. Wu,et al."Single depth map super-resolution via a deep feedback network".International Journal of Wavelets, Multiresolution and Information Processing 19.2(2021).