| --- |
| license: mit |
| pipeline_tag: image-segmentation |
| library_name: pytorch |
| tags: |
| - point-cloud |
| - point-cloud-backbone |
| - graph-learning |
| - pytorch |
| authors: |
| - Yuanwen Yue |
| - Damien Robert |
| - Jianyuan Wang |
| - Sunghwan Hong |
| - Jan Dirk Wegner |
| - Christian Rupprecht |
| - Konrad Schindler |
| --- |
| |
| This repository contains model weights for **LitePT: Lighter Yet Stronger Point Transformer**, a lightweight, high-performance 3D point cloud architecture. |
|
|
| LitePT embodies the simple principle "convolutions for low-level geometry, attention for high-level relations" and strategically places only the required operations at each hierarchy level. LitePT is equipped with a novel, parameter-free 3D positional encoding, PointROPE. The resulting model achieves state-of-the-art performance while being significantly more efficient. |
|
|
| ## Paper & Resources |
| - **Paper:** [LitePT: Lighter Yet Stronger Point Transformer](https://huggingface.co/papers/2512.13689) |
| - **Arxiv:** [https://arxiv.org/abs/2512.13689](https://arxiv.org/abs/2512.13689) |
| - **Project Page:** [https://litept.github.io/](https://litept.github.io/) |
| - **Codebase:** [https://github.com/prs-eth/LitePT](https://github.com/prs-eth/LitePT) |
|
|
| ## Models |
| We release the pretrained model weights for the benchmarks we reported in our paper. |
|
|
| ### Semantic segmentation |
| | Model | Params | Benchmark | val mIoU | Config | Checkpoint | |
| |:-|-:|:-:|:-:|:-:|:-:| |
| | LitePT-S | 12.7M | NuScenes | 82.2 | [link](https://github.com/prs-eth/LitePT/blob/main/configs/nuscenes/semseg-litept-small-v1m1.py) | [Download](https://huggingface.co/yuanwenyue/LitePT/blob/main/nuscenes-semseg-litept-small-v1m1/model/model_best.pth) | |
| | LitePT-S | 12.7M | Waymo | 73.1 |[link](https://github.com/prs-eth/LitePT/blob/main/configs/waymo/semseg-litept-small-v1m1.py) | [Download](https://huggingface.co/yuanwenyue/LitePT/blob/main/waymo-semseg-litept-small-v1m1/model/model_best.pth) | |
| | LitePT-S | 12.7M | ScanNet | 76.5 |[link](https://github.com/prs-eth/LitePT/blob/main/configs/scannet/semseg-litept-small-v1m1.py) | [Download](https://huggingface.co/yuanwenyue/LitePT/blob/main/scannet-semseg-litept-small-v1m1/model/model_best.pth) | |
| | LitePT-S | 12.7M | Structured3D | 83.6 | [link](https://github.com/prs-eth/LitePT/blob/main/configs/structured3d/semseg-litept-small-v1m1.py) | [Download](https://huggingface.co/yuanwenyue/LitePT/blob/main/structured3d-semseg-litept-small-v1m1/model/model_best.pth) | |
| | LitePT-B | 45.1M | Structured3D | 85.1 | [link](https://github.com/prs-eth/LitePT/blob/main/configs/structured3d/semseg-litept-base-v1m1.py) | [Download](https://huggingface.co/yuanwenyue/LitePT/blob/main/structured3d-semseg-litept-base-v1m1/model/model_best.pth) | |
| | LitePT-L | 85.9M | Structured3D | 85.4 | [link](https://github.com/prs-eth/LitePT/blob/main/configs/structured3d/semseg-litept-large-v1m1.py) | [Download](https://huggingface.co/yuanwenyue/LitePT/blob/main/structured3d-semseg-litept-large-v1m1/model/model_best.pth) | |
|
|
| ### Instance segmentation |
| | Model | Params | Benchmark | mAP<sub>25</sub> | mAP<sub>50</sub> | mAP | Config | Checkpoint | |
| |:-|-:|:-:|:-:|:-:|:-:|:-:|:-:| |
| | LitePT-S* | 16.0M | ScanNet | 78.5 | 64.9 | 41.7 | [link](https://github.com/prs-eth/LitePT/blob/main/configs/scannet/insseg-litept-small-v1m2.py) | [Download](https://huggingface.co/yuanwenyue/LitePT/blob/main/scannet-insseg-litept-small-v1m2/model/model_best.pth) | |
| | LitePT-S* | 16.0M | ScanNet200 | 40.3 | 33.1 | 22.2 | [link](https://github.com/prs-eth/LitePT/blob/main/configs/scannet200/insseg-litept-small-v1m2.py) | [Download](https://huggingface.co/yuanwenyue/LitePT/blob/main/scannet200-insseg-litept-small-v1m2/model/model_best.pth) | |
| ### Object detection |
| | Model | Params | Benchmark | mAPH | Config | Checkpoint | |
| |:-|-:|:-:|:-:|:-:|:-:| |
| | LitePT | 9.0M | Waymo | 70.7 | link | [Download](https://huggingface.co/yuanwenyue/LitePT/blob/main/waymo-objdet-litept-small-v1m3/model/model_best.pth) | |
|
|
| ## Citation |
|
|
| ``` |
| @article{yuelitept2025, |
| title={{LitePT: Lighter Yet Stronger Point Transformer}}, |
| author={Yue, Yuanwen and Robert, Damien and Wang, Jianyuan and Hong, Sunghwan and Wegner, Jan Dirk and Rupprecht, Christian and Schindler, Konrad}, |
| journal={arXiv preprint arXiv:2512.13689}, |
| year={2025} |
| } |
| ``` |
