license: other
tags:
- tree-height-estimation
- species-identification
- remote-sensing
- forest-monitoring
- drone-imagery
- ecology
- uav
- vision
- fine-grained-classification
- biodiversity
DINOvTree 🦖🌳
This repository contains the model weights for the DINOvTree model introduced in our paper:
Estimating Individual Tree Height and Species from UAV Imagery
Authors: Jannik Endres, Etienne Laliberté, David Rolnick, Arthur Ouaknine
Our model, DINOvTree, leverages a Vision Foundation Model (VFM) to extract features and predicts the height and species of the center tree in the input image with two separate heads.
Note: For full installation, training, and evaluation instructions, please refer to our GitHub repository.
📦 Model Weights & Datasets
We publish the model weights of DINOvTree in Base size for three distinct datasets.
| Dataset | Weights File | Description |
|---|---|---|
| Quebec Trees | dinovtreeb_quebectrees.pth |
Temperate Forest |
| BCI | dinovtreeb_bci.pth |
Tropical Forest |
| Quebec Plantations | dinovtreeb_quebecplantations.pth |
Boreal Plantation |
⚖️ License
The VFM of our checkpoint was initialized with DINOv3 weights, which are licensed under the DINOv3 License. The heads and our changes to the VFM weights are licensed under the Apache License 2.0.
📚 Citation
If you find our work useful, please consider citing our paper:
@article{endres2026treeheightspecies,
title = {Estimating Individual Tree Height and Species from UAV Imagery},
author = {Endres, Jannik and Lalibert{\'e}, Etienne and Rolnick, David and Ouaknine, Arthur},
journal = {arxiv:2603.23669 [cs.CV]},
year = {2026}
}