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---
license: mit
---
# OPDMulti: Openable Part Detection for Multiple Objects
This repository contains the latest model file for the [OPDMulti](https://github.com/3dlg-hcvc/OPDMulti) project.
Please refer there for more information about the proect and implementation.
[arXiv](https://arxiv.org/abs/2303.14087) [Website](https://3dlg-hcvc.github.io/OPDMulti/)
## Citation
If you find this code useful, please consider citing:
```bibtex
@article{sun2023opdmulti,
title={OPDMulti: Openable Part Detection for Multiple Objects},
author={Sun, Xiaohao and Jiang, Hanxiao and Savva, Manolis and Chang, Angel Xuan},
journal={arXiv preprint arXiv:2303.14087},
year={2023}
}
@article{mao2022multiscan,
title={MultiScan: Scalable RGBD scanning for 3D environments with articulated objects},
author={Mao, Yongsen and Zhang, Yiming and Jiang, Hanxiao and Chang, Angel and Savva, Manolis},
journal={Advances in Neural Information Processing Systems},
volume={35},
pages={9058--9071},
year={2022}
}
@inproceedings{jiang2022opd,
title={OPD: Single-view 3D openable part detection},
author={Jiang, Hanxiao and Mao, Yongsen and Savva, Manolis and Chang, Angel X},
booktitle={Computer Vision--ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23--27, 2022, Proceedings, Part XXXIX},
pages={410--426},
year={2022},
organization={Springer}
}
@inproceedings{cheng2022masked,
title={Masked-attention mask transformer for universal image segmentation},
author={Cheng, Bowen and Misra, Ishan and Schwing, Alexander G and Kirillov, Alexander and Girdhar, Rohit},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={1290--1299},
year={2022}
}
```
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