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This repository was archived by the owner on May 28, 2025. It is now read-only.
If you have not downloaded the dataset before, run the following script.
cd /path/to/hicodet
bash download.sh
If you have previously downloaded the dataset, simply create a soft link.
cd /path/to/hicodet
ln -s /path/to/hico_20160224_det ./hico_20160224_det
Install the lightweight deep learning library Pocket if you haven't yet.
Make sure the environment you created for Pocket is activated. You are good to go!
Citation
If you find our work useful for your research, please consider citing us:
@inproceedings{zhang2023pvic,
author = {Zhang, Frederic Z. and Yuan, Yuhui and Campbell, Dylan and Zhong, Zhuoyao and Gould, Stephen},
title = {Exploring Predicate Visual Context in Detecting Human–Object Interactions},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2023},
pages = {10411-10421},
}
@inproceedings{zhang2022upt,
author = {Zhang, Frederic Z. and Campbell, Dylan and Gould, Stephen},
title = {Efficient Two-Stage Detection of Human-Object Interactions with a Novel Unary-Pairwise Transformer},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2022},
pages = {20104-20112}
}
@inproceedings{zhang2021scg,
author = {Zhang, Frederic Z. and Campbell, Dylan and Gould, Stephen},
title = {Spatially Conditioned Graphs for Detecting Human–Object Interactions},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2021},
pages = {13319-13327}
}
Dataset Class
The implementation of the dataset class can be found in hicodet.py. Refer to the documentation to find out more about its usage. For convenience, the dataset class has been included in the Pocket library, accessible via pocket.data.HICODet.
