Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation

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Deep Learning SCOPE
Overview

Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation

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

Install

git clone https://github.com/fantaosha/SCOPE.git
cd SCOPE
export SCOPE_ROOT=$(pwd)
mkdir build
cd build
cmake ../C++
make -j4

Usage

SMPL Model

Download the SMPL model and extract these.pkl files to $SCOPE_ROOT/model.

Preprocess

cd $SCOPE_ROOT/model
python3 preprocess.py smpl_male.npz YOUR_SMPL_MALE.pkl

Run

cd $SCOPE_ROOT
./build/bin/run --model ./model/smpl_male.npz --prior ./model/joint_prior.json --keypoint ./examples/keypoints.json --result ./examples/results.json

Dataset

2D and 3D Keypoints

The 2D and 3D keypoints estimates from AlphaPose and VideoPose3D can be downloaded from Google Drive.

2D Keypoint Index

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: neck

3D Keypoint Index

0: 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

Citation

@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}
}
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Comments
  • Replace Eigen::Matrix3X<double>

    Replace Eigen::Matrix3X

    Hi Taosha,

    In "C++/scope/utils/Setup.cpp", there are two places with "Eigen::Matrix3X", which seem to cause compilation error: "error: ‘Matrix3X’ is not a member of ‘Eigen’;". I fixed that by replacing them with "Eigen::Matrix<double, 3, Eigen::Dynamic>". Would you consider updating them in the repo?

    Thank you! Muchen

    opened by MuchenSun 2
  • error: ‘Matrix3X’ is not a member of ‘Eigen’

    error: ‘Matrix3X’ is not a member of ‘Eigen’

    This is a wonderful job! The following error occurred during compilation: SCOPE/C++/scope/utils/Setup.cpp:195:36: error: ‘Matrix3X’ is not a member of ‘Eigen’; did you mean ‘Matrix3Xd’? 195 | Measurements = Eigen::Map<Eigen::Matrix3X>( | ^~~~~~~~ | Matrix3Xd

    Excuse me, is there something wrong with the Eigen version I installed? What is the correct Eigen version?

    opened by Allen-lz 1
  • How to do inference using SMPL-H model?

    How to do inference using SMPL-H model?

    Thank you for your great work! I've seen that you have showed the results of applying your method on smpl-h. Could you please tell me how to use smpl-h for inference rather than smpl. THANK YOU VERY MUCH !!!!!

    opened by luyr 1
  • Could you please release the code of training the joint prior from a scratch?

    Could you please release the code of training the joint prior from a scratch?

    Thank you for sharing this awesome work! I was trying to reproduce the normalizing flow used in the joint prior parts, and I noticed that the network structure (e.g. the PReLU implementation) might be different from the RealNVP, or Low-capacity version of normalizing flows mentioned in https://arxiv.org/abs/2003.10350 Could you please release the method or the code for training this network?

    opened by Phonicavi 3
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Taosha Fan
Taosha Fan
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