gpastal24 / Faster-VoxelPose

Official implementation of Faster VoxelPose: Real-time 3D Human Pose Estimation by Orthographic Projection

Faster VoxelPose

This is the official implementation for:

Faster VoxelPose: Real-time 3D Human Pose Estimation by Orthographic Projection,
Hang Ye, Wentao Zhu, Chunyu Wang, Rujie Wu, and Yizhou Wang
ECCV 2022

Environment

conda install pytorch torchvision cudatoolkit=<your cuda version>
pip install -r requirements.txt

Data

We use the Shelf/Campus and CMU Panoptic datasets. Please refer to VoxelPose for detailed instructions.

The directory tree should look like this:

${ROOT}
|-- data
    |-- Panoptic
        |-- 16060224_haggling1
        |   |-- hdImgs
        |   |-- hdvideos
        |   |-- hdPose3d_stage1_coco19
        |   |-- calibration_160224_haggling1.json
        |-- 160226_haggling1  
        |-- ...
    |-- Shelf
    |   |-- Camera0
    |   |-- ...
    |   |-- Camera4
    |   |-- actorsGT.mat
    |   |-- calibration_shelf.json
    |   |-- pred_shelf_maskrcnn_hrnet_coco.pkl
    |-- Campus
    |   |-- Camera0
    |   |-- Camera1
    |   |-- Camera2
    |   |-- actorsGT.mat
    |   |-- calibration_campus.json
    |   |-- pred_campus_maskrcnn_hrnet_coco.pkl
    |-- panoptic_training_pose.pkl

Training

CMU Panoptic dataset

Train and validate on the five selected camera views. You can specify the GPU devices and batch size per GPU in the config file.

python run/train.py --cfg configs/panoptic/jln64.yaml

Shelf/Campus datasets

python run/train.py --cfg configs/shelf/jln64.yaml
python run/train.py --cfg configs/campus/jln64.yaml

Evaluation

CMU Panoptic dataset

Evaluate the models. It will print evaluation results to the screen./

python run/validate.py --cfg configs/panoptic/jln64.yaml

Shelf/Campus datasets

It will print the PCP results to the screen.

python run/validate.py --cfg configs/shelf/jln64.yaml
python run/validate.py --cfg configs/campus/jln64.yaml

Citation

If you use our code or models in your research, please cite with:

@inproceedings{fastervoxelpose,
    author={Ye, Hang and Zhu, Wentao and Wang, Chunyu and Wu, Rujie and Wang, Yizhou},
    title={Faster VoxelPose: Real-time 3D Human Pose Estimation by Orthographic Projection},
    booktitle = {European Conference on Computer Vision (ECCV)},
    year = {2022}
}