Authors: Yikun Li, Lambert Schomaker, Hamidreza Kasaei
This dataset contains 500 models as well as their grasp affordance from five categories (mug, lamp, chair, knife, and guitar). 25 example models with grasp affordance are shown below:
An animation example:
- unzip the dataset.zip file.
- run the model_reviewer.py viewing the models with grasp affordance.
Latest version available on arXiv | Video
Please adequately refer to the papers any time this code is being used. If you do publish a paper where this dataset helped your research, we encourage you to cite the following paper in your publications:
@inproceedings{li2020learning,
title={Learning to grasp 3d objects using deep residual u-nets},
author={Li, Yikun and Schomaker, Lambert and Kasaei, S Hamidreza},
booktitle={2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)},
pages={781--787},
year={2020},
organization={IEEE}
}
- Please use the following email addresses if you have questions or want to contribute to this project: