This project implements the codes for the paper '3D Hand Pose Estimation with a Single Infrared Camera via Domain Transfer Learning' published in ISMAR'20.
conda env create -f environment.yml
You can download the pretrained models in the following link: https://www.dropbox.com/sh/54pmyizj95636zz/AAA-Y-gIQclrSK61gjuqgr3Ha?dl=0
You can download the datasets in the following link: https://www.dropbox.com/sh/9dlvpb2vm57moj1/AADGXiwvfFfhoMdnkeDQsiQJa?dl=0
You can test it on our dataset by launching:
python Demo/runDemo_dataset.py
You can test it using SR300 realsense camera in real-time by launching:
python Demo/runDemo_realtime.py
If you think this code is useful for your research, consider citing:
@INPROCEEDINGS{ismar20_gypark,
title = {3D Hand Pose Estimation with a Single Infrared Camera via Domain Transfer Learning},
author = {Park, Gabyong and Kim, Tae-Kyun and Woo, Woontack},
booktitle = {ISMAR},
year = {2020}
}
This work was partly supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT) (No.2019-0-01270, WISE AR UI/UX Platform Development for Smartglasses) and Next-Generation Information Computing Development Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT (NRF-2017M3C4A7066316).