This is the implementation of the approach described in the paper:
Taosha Fan, Kalyan Vasudev Alwala, Donglai Xiang, Weipeng Xu, Todd Murphey, Mustafa Mukadam. Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation. In IEEE/CVF International Conference on Computer Vision (ICCV), 2021.
More demos are available at https://sites.google.com/view/scope-human
git clone https://github.com/fantaosha/SCOPE.git
cd SCOPE
export SCOPE_ROOT=$(pwd)
mkdir build
cd build
cmake ../C++
make -j4Download the SMPL model and extract these.pkl files to $SCOPE_ROOT/model.
cd $SCOPE_ROOT/model
python3 preprocess.py smpl_male.npz YOUR_SMPL_MALE.pklcd $SCOPE_ROOT
./build/bin/run --model ./model/smpl_male.npz --prior ./model/joint_prior.json --keypoint ./examples/keypoints.json --result ./examples/results.jsonThe 2D and 3D keypoints estimates from AlphaPose and VideoPose3D can be downloaded from Google Drive.
0: nose
1: left eye
2: right eye
3: left ear
4: right ear
5: left upper arm
6: right upper arm
7: left elbow
8: right elow
9: left wrist
10: right wrist
11: left hip
12: right hip
13: left knee
14: right knee
15: left ankle
16: right ankle
17: head top
18: thorax
19: middle hip
20: left big toe
21: right big toe
22: left small toe
23: right small toe
24: left heel
25: right heel
26: chest
27: neck0: middile hip
1: left hip
2: left knee
3: left ankle
4: right hip
5: right knee
6: right ankle
7: chest
8: thorax
9: neck
10: head top
11: left upper arm
12: left elbow
13: left wrist
14: right upper arm
15: right elbow
16: right wrist@article{fan2021revitalizing,
title={Revitalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation},
author={Fan, Taosha and Alwala, Kalyan Vasudev and Xiang, Donglai and Xu, Weipeng and Murphey, Todd and Mukadam, Mustafa},
journal={Proceedings of the IEEE/CVF International Conference on Computer Vision},
year={2021}
}