| ---
|
| license: mit
|
| pipeline_tag: other
|
| tags:
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| - pose-estimation
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| - point-cloud
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| - 3d
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| - cvpr2022
|
| ---
|
|
|
| # CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wild — Pretrained Models
|
|
|
| Pretrained model checkpoints for [CPPF (CVPR 2022)](https://openaccess.thecvf.com/content/CVPR2022/html/You_CPPF_Towards_Robust_Category-Level_9D_Pose_Estimation_in_the_Wild_CVPR_2022_paper.html), a sim-to-real method for category-level 9D pose estimation trained solely on synthetic ShapeNet models.
|
|
|
| - **Code**: https://github.com/qq456cvb/CPPF
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| - **Project page**: https://qq456cvb.github.io/projects/cppf
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| - **Companion dataset (training/eval data)**: https://huggingface.co/datasets/qq456cvb/CPPF
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|
|
| ## Contents
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|
|
| One folder per ShapeNet category, each containing:
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|
|
| | File | Description |
|
| |---|---|
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| | `point_encoder_epochbest.pth` | Point encoder weights (best epoch) |
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| | `ppf_encoder_epochbest.pth` | PPF encoder weights (best epoch) |
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| | `.hydra/*.yaml` | Hydra config snapshot used for training |
|
|
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| Categories: `bathtub`, `bed`, `bookshelf`, `bottle`, `bowl`, `bowl_reg` (regression variant), `camera`, `can`, `chair`, `laptop`, `laptop_aux` (auxiliary lid/base segmenter), `mug`, `sofa`, `table`.
|
|
|
| ## Usage
|
|
|
| Download and place the category folders under `checkpoints/` in the [CPPF repository](https://github.com/qq456cvb/CPPF):
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|
|
| ```bash
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| pip install -U "huggingface_hub[cli]"
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| hf download qq456cvb/CPPF --local-dir checkpoints
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| ```
|
|
|
| ## Citation
|
|
|
| ```bibtex
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| @inproceedings{you2022cppf,
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| title={CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wild},
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| author={You, Yang and Shi, Ruoxi and Wang, Weiming and Lu, Cewu},
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| booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
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| year={2022}
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| }
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| ```
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|
|
