| --- |
| license: mit |
| library_name: torch-pointcloud |
| tags: |
| - point-cloud |
| - 3d |
| - pytorch |
| - torch-pointcloud |
| - act |
| - self-supervised |
| datasets: |
| - shapenet |
| --- |
| |
| # Model card for act.dvae.runpei-dong |
|
|
| An ACT self-supervised pretraining model (masked point transformer distilled from a 2D image transformer). Pretrained on ShapeNet-55. |
|
|
| ## Model Details |
|
|
| - **Model Type:** Self-supervised pretraining |
| - **Model Stats:** |
| - Params (M): 116.2 |
| - **Dataset:** ShapeNet-55 |
| - **Paper:** [Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?](https://arxiv.org/abs/2212.08320) |
| - **Converted from:** [RunpeiDong/ACT](https://github.com/RunpeiDong/ACT) (MIT) |
| - **Library:** [torch-pointcloud](https://github.com/arthurdjn/pytorch-pointcloud) |
|
|
| ## Install |
|
|
| ```bash |
| pip install torch-pointcloud |
| ``` |
|
|
| ## Usage |
|
|
| ```python |
| import torch |
| import torch_pointcloud as tp |
| from torch_pointcloud.utils.data import collate |
| |
| model, info = tp.create_model( |
| "act.dvae.runpei-dong", |
| pretrained=True, |
| return_info=True, |
| ) |
| model = model.eval() |
| |
| # synthetic sample with the keys a dataset provides |
| num_points = 8192 |
| sample = { |
| "pos": torch.randn(num_points, 3), |
| } |
| data = collate([sample]) |
| |
| with torch.no_grad(): |
| out = model(data.get("x"), data["pos"], data["batch"]) |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{dong2023act, |
| title = {Autoencoders as Cross-Modal Teachers: Can Pretrained {2D} Image Transformers Help {3D} Representation Learning?}, |
| author = {Dong, Runpei and Qi, Zekun and Zhang, Linfeng and Zhang, Junbo and Sun, Jianjian and Ge, Zheng and Yi, Li and Ma, Kaisheng}, |
| booktitle = {ICLR}, |
| year = {2023} |
| } |
| |
| @article{chang2015shapenet, |
| author = {Chang, Angel X. and Funkhouser, Thomas and Guibas, Leonidas and Hanrahan, Pat and Huang, Qixing and Li, Zimo and Savarese, Silvio and Savva, Manolis and Song, Shuran and Su, Hao and Xiao, Jianxiong and Yi, Li and Yu, Fisher}, |
| title = {{ShapeNet}: An Information-Rich {3D} Model Repository}, |
| journal = {arXiv preprint arXiv:1512.03012}, |
| year = {2015}, |
| } |
| |
| @software{dujardin2026pytorchpointcloud, |
| author = {Arthur Dujardin}, |
| title = {PyTorch PointCloud}, |
| year = {2026}, |
| doi = {10.5281/zenodo.22159632}, |
| url = {https://github.com/arthurdjn/pytorch-pointcloud}, |
| } |
| ``` |
|
|
