dmlc--dgl
esang
4fb50be4d9
* some modifications for pointnet2 * temporarily save changes * move files to new directory point_transformer * implement point transformer for classification * restore train_cls in pointnet * implement point transformer for partseg * fix point transformer for nan loss * modify point transformer for cls * modify training setting * update transformer for cls * update code * update code for latest performance * update the example index * some minor changes Co-authored-by: Tong He <hetong007@gmail.com>
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1.1 KiB
Point Transformer
This model is implemented on August 27, 2021 when there is no official code released.
Thus we implemented this model based on the code from https://github.com/qq456cvb/Point-Transformers.
This is a reproduction of the paper: Point Transformer.
Performance
| Task | Dataset | Metric | Score - Paper | Score - DGL (Adam) | Score - DGL (SGD) | Time(s) - DGL |
|---|---|---|---|---|---|---|
| Classification | ModelNet40 | Accuracy | 93.7 | 92.0 | 91.5 | 117.0 |
| Part Segmentation | ShapeNet | mIoU | 86.6 | 84.3 | 85.1 | 260.0 |
- Time(s) are the average training time per epoch, measured on EC2 p3.8xlarge instance w/ Tesla V100 GPU.
How to Run
For point cloud classification, run with
python train_cls.py --opt [sgd/adam]
For point cloud part-segmentation, run with
python train_partseg.py --opt [sgd/adam]