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hecpg's Introduction

HECPG: Hyperbolic Embedding and Confident Patch-Guided Network for Point Cloud Matching (TGRS 2024)

PyTorch implementation of the paper: HECPG: Hyperbolic Embedding and Confident Patch-Guided Network for Point Cloud Matching.

HECPG architecture

Environment and Data Preparation

The codes of our project mainly base on GeoTransformer, please follow it.

Usage

To train a model:

python trainval.py

To test a model:

python test.py --snapshot=weights_path --benchmark=3DMatch
python eval.py --benchmark=3DMatch --method=ransac

Citation

If you find our work useful in your research, please consider citing:

@article{xie2024hecpg,
  title={HECPG: Hyperbolic Embedding and Confident Patch-Guided Network for Point Cloud Matching},
  author={Xie, Yifan and Zhu, Jihua and Li, Shiqi and Hu, Naiwen and Shi, Pengcheng},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
  year={2024},
  volume={62},
  number={},
  pages={1-12},
  publisher={IEEE}
}

Acknowledgement

This code is developed heavily relying on GeoTransformer, PREDATOR and hyp-ViT. Thanks for these great projects.

hecpg's People

Contributors

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Watchers

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Forkers

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hecpg's Issues

代码报错提示

您好，我在运行训练代码时出现报错，问题在于hy_attention.py 中的第50行： b, num_centroids, c = h.shape ，输出h维度分别为torch.Size([1,244,1024]) torch.Size([1,291,1024]) torch.Size([1,1,244,256])， h 变为了四维向量，请告诉我是哪里配置出现问题吗？期待您的回复于解答，非常感谢。运行错误提示见下图：
微信图片_20240604162803

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