Official code of Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement
Junuk Cha, Muhammad Saqlain, GeonU Kim, Mingyu Shin, Seungryul Baek
In the Wild Input | Output |
---|---|
git clone https://github.com/JunukCha/MultiPerson.git
cd MultiPerson
Anaconda must be installed in your computer.
source install.sh
If it has been installed well so far, it has a folder tree structure as shown below and your virtual environment name is set to 'MultiPerson'.
.MultiPerson
├── configs
├── demo_image
├── lib
├── .gitignore
├── README.md
├── demo.py
├── install.sh
├── requirements.txt
└── YOLOv4
For Yolo, download yolov4.pth and place it as below.
.MultiPerson
└── YOLOv4
└── weight
└── yolov4.pth
- Download data in Google Drive and place them as below.
- Download "basicModel_neutral_lbs_10_207_0_v1.0.0.pkl" from SMPL web page and place it as below.
.MultiPerson
├── data
│ ├── base
│ │ ├── 32_to_122.npy
│ │ └── joint_info.pkl
│ ├── checkpoints
│ │ ├── inverse_kinematics.pth
│ │ ├── model_checkpoint.pt
│ │ ├── pose_estimator.pth
│ │ └── transformer.pth
│ └── smpl
│ ├── basicModel_neutral_lbs_10_207_0_v1.0.0.pkl
│ ├── h36m_mean_beta.npy
│ ├── J_regressor_extra.npy
│ ├── J_regressor_h36m.npy
│ └── smpl_mean_params.npz
In 'yolov4.pth', the key name 'neek' of the parameter should be changed to 'neck'.
python change_param_key.py
python demo.py --img demo_image/demo1.jpg
@inproceedings{cha2022multi,
title={Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement},
author={Cha, Junuk and Saqlain, Muhammad and Kim, GeonU and Shin, Mingyu and Baek, Seungryul},
booktitle={ECCV},
year={2022},
}