Fragmentation Guided Human Shape Reconstruction
2019
发表期刊IEEE ACCESS
ISSN2169-3536
卷号7页码:45651-45661
发表状态已发表
DOI10.1109/ACCESS.2019.2905879
摘要We present a novel semantic-driven multi-view reconstruction technique for producing realistic 3D human models. Our approach borrows the fragmentation concept in Cubism style painting, where the human body is decomposed into semantically meaningful fragments for conveying space and movement. We first employ deep learning-based skeleton estimation for warping a proxy human model under the canonical pose to the target multi-view input. It also conducts 3D fragment labeling on the warped model to separate different human body parts. Finally, we utilize the normal, depth, and fragment label of the proxy model as priors in the multi-view stereo reconstruction process. The comprehensive experiments have shown that our reconstruction technique outperforms the state-of-the-art methods in robustness and accuracy, especially near occlusion boundaries and on textureless regions. In particular, it manages to significantly reduce the "adhesive" artifacts commonly observed in MVS that incorrectly stitches different body parts.
关键词3D Reconstruction human shape semantic analysis multi-view stereo
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收录类别SCI ; SCIE ; EI
语种英语
资助项目SHEITC[2018-RGZN-01011]
WOS研究方向Computer Science ; Engineering ; Telecommunications
WOS类目Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号WOS:000465620900001
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
EI入藏号20191806845576
EI主题词Adhesives ; Deep learning ; Image reconstruction ; Semantics ; Textures
EI分类号Data Processing and Image Processing:723.2
原始文献类型Article
来源库IEEE
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文献类型期刊论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/34290
专题信息科学与技术学院_硕士生
信息科学与技术学院_PI研究组_虞晶怡组
作者单位
1.University of Chinese Academy of Sciences, Beijing, China
2.DGene Inc., Shanghai, China
3.School of Information Science and Technology, ShanghaiTech University, Shanghai, China
推荐引用方式
GB/T 7714
Yingliang Zhang,Xi Luo,Wei Yang,et al. Fragmentation Guided Human Shape Reconstruction[J]. IEEE ACCESS,2019,7:45651-45661.
APA Yingliang Zhang,Xi Luo,Wei Yang,&Jingyi Yu.(2019).Fragmentation Guided Human Shape Reconstruction.IEEE ACCESS,7,45651-45661.
MLA Yingliang Zhang,et al."Fragmentation Guided Human Shape Reconstruction".IEEE ACCESS 7(2019):45651-45661.
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