| --- |
| license: cc-by-nc-sa-4.0 |
| tags: |
| - point-cloud |
| - semantic-segmentation |
| - instance-segmentation |
| - pointcept |
| --- |
| |
| # Checkpoints for the submission "relabelling voxel indices" |
|
|
| Weights of the models we trained for the paper, to be read with the code release (an overlay |
| on [Pointcept](https://github.com/Pointcept/Pointcept) `v1.7.0`). Every model here was trained |
| **from scratch** with Pointcept's unmodified model code; no third-party weights are included. |
|
|
| Layout: `exp/<dataset>/<config>/model/model_best.pth` plus the run's `train.log`. The directory |
| name is the Pointcept configuration that trained it; a second seed ends in `-seed1`. Each file |
| holds the model `state_dict` (plus `epoch` and `best_metric_value`); optimizer state is removed. |
| `SHA256SUMS` lists the hashes. The published LitePT-S checkpoints the paper also reads are not |
| copied here: they are on [prs-eth/LitePT](https://huggingface.co/prs-eth/LitePT). |
|
|
| | dataset | checkpoints | |
| |---|---| |
| | ScanNet v2 | `semseg-litept-v1m1-0-small`, `semseg-litept-v1m1-0b-small-scaleaug`, `semseg-litept-v1m1-0-small-train3tau`, `semseg-litept-v1m2-0-small` (+ `-seed1`), `semseg-pt-v3m1-0-base`, `semseg-spunet-v1m1-0-base`, `semseg-pt-v2m2-0-base`, `insseg-pointgroup-v1m1-0-spunet-base` | |
| | nuScenes | `semseg-litept-v1m1-0-small` (+ `-seed1`), `semseg-litept-v1m1-0b-small-scaleaug` (+ `-seed1`), `semseg-litept-v1m2-0-small`, `semseg-litept-v1m2-0b-small-scaleaug`, `semseg-pt-v3m1-0-base`, `semseg-spunet-v1m1-0-base` | |
|
|
| ## Licence and data terms |
|
|
| These weights are released for **non-commercial research only**, under |
| [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/), because of the data |
| they were trained on: |
|
|
| * **nuScenes** is provided by Motional under CC BY-NC-SA 4.0 and the |
| [nuScenes Terms of Use](https://www.nuscenes.org/terms-of-use). The nuScenes checkpoints are |
| shared under the same licence. This release is not endorsed by Motional. |
| Caesar et al., *nuScenes: A multimodal dataset for autonomous driving*, CVPR 2020. |
| * **ScanNet** may be used for non-commercial research and educational purposes only, under |
| the [ScanNet Terms of Use](https://kaldir.vc.in.tum.de/scannet/ScanNet_TOS.pdf). No ScanNet |
| data is included here. Dai et al., *ScanNet: Richly-annotated 3D Reconstructions of Indoor |
| Scenes*, CVPR 2017. |
|
|
| The training and model code (Pointcept, LitePT) is MIT-licensed and is not included here. |
|
|
