3D Human Pose Estimation is the task of estimating the pose of a human from a picture or set of video frames.
( Image credit: 3d-pose-baseline )
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Most 3d human pose estimation methods assume that input -- be it images of a scene collected from one or several viewpoints, or from a video -- is given.
In this work, we propose a multi-task framework for jointly estimating 2D or 3D human poses from monocular color images and classifying human actions from video sequences.
Although significant improvement has been achieved in 3D human pose estimation, most of the previous methods only consider a single-person case.
Our approach is self-improving by nature, since better network estimates can lead the optimization to better solutions, while more accurate optimization fits provide better supervision for the network.
#2 best model for 3D Human Pose Estimation on 3DPW (using extra training data)
It consists of two separate steps: (1) estimating the 2D poses in multi-view images and (2) recovering the 3D poses from the multi-view 2D poses.
#2 best model for 3D Human Pose Estimation on Human3.6M (using extra training data)
Although existing CNN-based temporal frameworks attempt to address the sensitivity and drift problems by concurrently processing all input frames in the sequence, the existing state-of-the-art CNN-based framework is limited to 3d pose estimation of a single frame from a sequential input.
#11 best model for 3D Human Pose Estimation on Human3.6M
Although significant improvement has been achieved recently in 3D human pose estimation, most of the previous methods only treat a single-person case.
In the second stage, a fully-connected neural network turns the possibly partial (on account of occlusion) 2D pose and 3D pose features for each subject into a complete 3D pose estimate per individual.
#6 best model for 3D Human Pose Estimation on MPI-INF-3DHP
We present a bundle-adjustment-based algorithm for recovering accurate 3D human pose and meshes from monocular videos.
#3 best model for 3D Human Pose Estimation on 3DPW (using extra training data)