This repository provides a code base to evaluate the trained models of the paper Cross-Modal Deep Variational Hand Pose Estimation and reproduce the numbers of Table 2. It is a modified version of the code found here by Christian Zimmermann, adapted to run our model.
Recommended system (tested):
Python packages used by the example provided and their recommended version:
In order to use the training and evaluation scripts you need download and preprocess the datasets.
python create_binary_db.py
cd ./data/stb/
matlab -nodesktop -nosplash -r "create_db"
Paper | Code |
---|---|
H | hand_side_invariance |
S | scale_invariance |
python evaluate_model.py
This project is licensed under the terms of the GPL v2 license. By using the software, you are agreeing to the terms of the license agreement.
If you use this code in your research, please cite us as follows:
@inproceedings{spurr2018cvpr,
author = {Spurr, Adrian and Song, Jie and Park, Seonwook and Hilliges, Otmar},
title = {Cross-modal Deep Variational Hand Pose Estimation},
booktitle = {CVPR},
year = {2018},
location = {Salt Lake City, USA},
}