中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
An Efficient Information-Reinforced Lidar Deep Completion Network without RGB Guided

文献类型:期刊论文

作者M. Wei; M. Zhu; Y. Y. Zhang; J. Q. Sun and J. R. Wang
刊名Remote Sensing
出版日期2022
卷号14期号:19页码:17
DOI10.3390/rs14194689
英文摘要Due to the sparsity of point clouds obtained by LIDAR, the depth information is usually not complete and dense. The depth completion task is to recover dense depth information from sparse depth information. However, most of the current deep completion networks use RGB images as guidance, which are more like a processing method of information fusion. They are not valid when there is only sparse depth data and no other color information. Therefore, this paper proposes an information-reinforced completion network for a single sparse depth input. We use a multi-resolution dense progressive fusion structure to maximize the multi-scale information and optimize the global situation by point folding. At the same time, we re-aggregate the confidence and impose another depth constraint on the pixel depth to make the depth estimation closer to the ground trues. Our experimental results on KITTI and NYU Depth v2 datasets show that the proposed network achieves better results than other unguided deep completion methods. And it is excellent in both accuracy and real-time performance.
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语种英语
源URL[http://ir.ciomp.ac.cn/handle/181722/66603]  
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
M. Wei,M. Zhu,Y. Y. Zhang,et al. An Efficient Information-Reinforced Lidar Deep Completion Network without RGB Guided[J]. Remote Sensing,2022,14(19):17.
APA M. Wei,M. Zhu,Y. Y. Zhang,&J. Q. Sun and J. R. Wang.(2022).An Efficient Information-Reinforced Lidar Deep Completion Network without RGB Guided.Remote Sensing,14(19),17.
MLA M. Wei,et al."An Efficient Information-Reinforced Lidar Deep Completion Network without RGB Guided".Remote Sensing 14.19(2022):17.

入库方式: OAI收割

来源:长春光学精密机械与物理研究所

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