| --- |
| license: other |
| tags: |
| - keypoint-matching |
| - superpoint |
| - superglue |
| - inverse-graphics |
| --- |
| |
| # Weights for *Structure from Duplicates* (SfD) |
|
|
| Pretrained checkpoints used by the SfD preprocessing pipeline |
| ([Tianhang-Cheng/SfD](https://github.com/Tianhang-Cheng/SfD)). They are hosted here instead of in the |
| git repository to keep clones small. |
|
|
| | file | size | what it is | |
| | --- | --- | --- | |
| | `keypoint_matching/superpoint_v1.pth` | 5 MB | SuperPoint detector/descriptor | |
| | `keypoint_matching/superglue_indoor.pth` | 46 MB | SuperGlue matcher, indoor weights | |
| | `keypoint_matching/superglue_outdoor.pth` | 46 MB | SuperGlue matcher, outdoor weights | |
|
|
| ## Usage |
|
|
| From a clone of the repo, all three land in `preprocess/keypoint_matching/weights/`: |
|
|
| ```bash |
| python download_assets.py --weights |
| ``` |
|
|
| The pipeline also fetches them lazily the first time the matcher is constructed, so this step is |
| optional. |
|
|
| Directly: |
|
|
| ```python |
| from huggingface_hub import hf_hub_download |
| |
| hf_hub_download("TianhangCheng7/DuplicateWeight", "keypoint_matching/superpoint_v1.pth") |
| ``` |
|
|
| ## License / attribution |
|
|
| SuperPoint and SuperGlue were released by Magic Leap, Inc. and are mirrored here under the original |
| [SuperGluePretrainedNetwork](https://github.com/magicleap/SuperGluePretrainedNetwork) terms, which |
| allow **non-commercial research use only**. Please cite the original works: |
|
|
| ``` |
| @inproceedings{detone2018superpoint, |
| title={SuperPoint: Self-Supervised Interest Point Detection and Description}, |
| author={DeTone, Daniel and Malisiewicz, Tomasz and Rabinovich, Andrew}, |
| booktitle={CVPR Deep Learning for Visual SLAM Workshop}, |
| year={2018} |
| } |
| @inproceedings{sarlin2020superglue, |
| title={SuperGlue: Learning Feature Matching with Graph Neural Networks}, |
| author={Sarlin, Paul-Edouard and DeTone, Daniel and Malisiewicz, Tomasz and Rabinovich, Andrew}, |
| booktitle={CVPR}, |
| year={2020} |
| } |
| ``` |
|
|
| If you use SfD: |
|
|
| ``` |
| @inproceedings{cheng2023structure, |
| title={Structure from Duplicates: Neural Inverse Graphics from a Pile of Objects}, |
| author={Cheng, Tianhang and Ma, Wei-Chiu and Guan, Kaiyu and Torralba, Antonio and Wang, Shenlong}, |
| booktitle={Thirty-seventh Conference on Neural Information Processing Systems}, |
| year={2023} |
| } |
| ``` |
|
|
