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Found 3 papers, 1 papers with code
SRNet: Improving Generalization in 3D Human Pose Estimation with a Split-and-Recombine Approach
With the reduced dimensionality of less relevant body areas, the training set distribution within network branches more closely reflects the statistics of local poses instead of global body poses, without sacrificing information important for joint inference.
Ranked #20 on
Monocular 3D Human Pose Estimation
on Human3.6M
DeepFuse: An IMU-Aware Network for Real-Time 3D Human Pose Estimation from Multi-View Image
In this paper, we propose a two-stage fully 3D network, namely \textbf{DeepFuse}, to estimate human pose in 3D space by fusing body-worn Inertial Measurement Unit (IMU) data and multi-view images deeply.
Ranked #5 on
3D Human Pose Estimation
on Total Capture
Structure-Aware 3D Hourglass Network for Hand Pose Estimation from Single Depth Image
Experimental results show that the proposed structure-aware 3D hourglass network is able to achieve a mean joint error of 7. 4 mm in MSRA and 8. 9 mm in NYU datasets, respectively.
