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Reconstructing 3D Human Pose by Watching Humans in the Mirror

2021-04-01 · CVPR 2021 1 · Qi Fang, Qing Shuai, Junting Dong, Hujun Bao, Xiaowei Zhou

In this paper, we introduce the new task of reconstructing 3D human pose from a single image in which we can see the person and the person's image through a mirror. Compared to general scenarios of 3D pose estimation from a single view, the mirror reflection provides an additional view for resolving the depth ambiguity. We develop an optimization-based approach that exploits mirror symmetry constraints for accurate 3D pose reconstruction. We also provide a method to estimate the surface normal of the mirror from vanishing points in the single image. To validate the proposed approach, we collect a large-scale dataset named Mirrored-Human, which covers a large variety of human subjects, poses and backgrounds. The experiments demonstrate that, when trained on Mirrored-Human with our reconstructed 3D poses as pseudo ground-truth, the accuracy and generalizability of existing single-view 3D pose estimators can be largely improved.

📄 PDF Abstract BibTeX arXiv:2104.00340

Code (1)

zju3dv/EasyMocap pytorch

Tasks

3D Pose EstimationPose Estimation

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