library_name: pytorch
tags:
- point-cloud
- point-cloud-backbone
- self-supervised-learning
- lidar
- forest
- pytorch
authors:
- Yuanwen Yue
- Stefano Puliti
- Damien Robert
- Atakan Topaloğlu
- Binbin Xiang
- Maciej Wielgosz
- Jan Dirk Wegner
- Rasmus Astrup
- Christian Rupprecht
- Konrad Schindler
This repository contains model weights for the paper Toward A Foundation Model for Forest Point Clouds.
ForPT pretrains a LitePT backbone on a large corpus of unlabeled airborne (ALS), UAV (ULS) and mobile (MLS) laser scans covering diverse forest ecosystems. It is evaluated on four forestry tasks: semantic segmentation, instance segmentation, tree species classification and tree age regression. Self-supervised pretraining accelerates convergence, improves performance when annotations are scarce, and transfers better than task-specific supervised pretraining.
Paper & Resources
- Arxiv: https://arxiv.org/abs/2609.24787
- Project Page: https://prs-eth.github.io/ForPT
- Codebase: https://github.com/prs-eth/ForPT
Models
We release the pretrained backbone and the downstream models for the benchmarks reported in our paper.
Pretrained backbone
Downstream tasks (100% labels)
| Task | Benchmark | Model | Config | Checkpoint |
|---|---|---|---|---|
| Semantic segmentation | FOR-instanceV2 | LitePT-scratch | link | Download |
| ForPT-linear probing | link | Download | ||
| ForPT-decoder probing | link | Download | ||
| ForPT-finetune | link | Download | ||
| Instance segmentation | FOR-instanceV2 | Coming soon | - | - |
| Species classification | FOR-species20K | LitePT-scratch | link | Download |
| ForPT-linear probing | link | Download | ||
| ForPT-finetune | link | Download | ||
| Age regression | FORage | LitePT-scratch | link | Download |
| ForPT-linear probing | link | Download | ||
| ForPT-finetune | link | Download |
To download all checkpoints into the layout expected by the configs, run from the root of the ForPT codebase:
hf download prs-eth/ForPT --local-dir weights --exclude ".gitattributes" --exclude "README.md"
Citation
@article{yue2026forpt,
title={Toward a foundation model for forest point clouds},
author={Yue, Yuanwen and Puliti, Stefano and Robert, Damien and Topalo{\u{g}}lu, Atakan and Xiang, Binbin and Wielgosz, Maciej and Wegner, Jan Dirk and Astrup, Rasmus and Rupprecht, Christian and Schindler, Konrad},
journal={arXiv preprint arXiv:2609.24787},
year={2026}
}