Shape-Aware Human Pose and Shape Reconstruction Using Multi-View Images
Junbang Liang, Ming C. Lin
Abstract
We propose a scalable neural network framework to reconstruct the 3D mesh of a human body from multi-view images, in the subspace of the SMPL model [23] . Use of multi-view images can significantly reduce the projection ambiguity of the problem, increasing the reconstruction accuracy of the 3D human body under clothing. Our experiments show that this method benefits from the synthetic dataset generated from our pipeline since it has good flexibility of variable control and can provide ground-truth for validation. Our method outperforms existing methods on real-world images, especially on shape estimations.
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Install the CLIlune papers fulltext 294329be-ada3-4c5b-9214-bf9ab97838ccCited by top-tier papers17
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- Multiview Human Body Reconstruction from Uncalibrated CamerasZhixuan Yu, Linguang Zhang, Yuanlu Xu, Chengcheng Tang et al.NeurIPS 2022 · 24 citations
- Delving Deep into Pixel Alignment Feature for Accurate Multi-View Human Mesh RecoveryKai Jia, Hongwen Zhang, Liang An, Yebin LiuAAAI 2023 · 17 citations
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