---
license: other
license_name: license
license_link: LICENSE
---

# Wild-Places: A Large-Scale Dataset for Lidar Place Recognition in Unstructured Natural Environments
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This repository contains pre-trained checkpoints for the dataset introduced in the paper *Wild-Places: A Large-Scale Dataset for Lidar Place Recognition in Unstructured Natural Environments*, which has been published at ICRA2023.  

If you find this dataset helpful for your research, please cite our paper using the following reference:
```
@inproceedings{2023wildplaces,
  title={Wild-places: A large-scale dataset for lidar place recognition in unstructured natural environments},
  author={Knights, Joshua and Vidanapathirana, Kavisha and Ramezani, Milad and Sridharan, Sridha and Fookes, Clinton and Moghadam, Peyman},
  booktitle={2023 IEEE international conference on robotics and automation (ICRA)},
  pages={11322--11328},
  year={2023},
  organization={IEEE}
}
```

## Download Instructions

Our dataset can be downloaded through [The CSIRO Data Access Portal](https://data.csiro.au/collection/csiro:56372?q=wild-places&_st=keyword&_str=1&_si=1). Detailed instructions for downloading the dataset can be found in the README file provided on the data access portal page. 

## Training and Benchmarking
Here we provide pre-trained checkpoints and results for benchmarking several state-of-the-art LPR methods on the Wild-Places dataset.

**Update Nov. 2025**:  With the release of Wild-Places v3.0, we have also re-run training for two state-of-the-art methods (LoGG3D-Net, MinkLoc3Dv2) on the Wild-Places dataset using expanded batch sizes to provide new training checkpoints which better reflect the capabilities of recent state-of-the-art GPUs.  We provide checkpoints and benchmarked results for both the recently trained models and the checkpoints released with the ICRA2023 paper.

### Checkpoints
|Release| Model      | Checkpoint |
|------------|------------|------------|
|ICRA2023| TransLoc3D | [Link](https://huggingface.co/CSIRORobotics/Wild-Places/resolve/main/ICRA_2023_checkpoints/TransLoc3D.pth)       |
|ICRA2023| MinkLoc3DV2  | [Link](https://huggingface.co/CSIRORobotics/Wild-Places/resolve/main/ICRA_2023_checkpoints/MinkLoc3Dv2.pth)       |
|ICRA2023| LoGG3D-Net | [Link](https://huggingface.co/CSIRORobotics/Wild-Places/resolve/main/ICRA_2023_checkpoints/LoGG3D-Net.pth)       |
|2025 Re-Training| MinkLoc3DV2  | [Link](https://huggingface.co/CSIRORobotics/Wild-Places/resolve/main/2025_updated_checkpoints/MinkLoc3Dv2.pth)       |
|2025 Re-Training| LoGG3D-Net  | [Link](https://huggingface.co/CSIRORobotics/Wild-Places/resolve/main/2025_updated_checkpoints/LoGG3D-Net.pth)       


For further instructions on training and evaluating these checkpoints on the Wild-Places dataset, please follow the instructions found at the [Wild-Places GitHub](https://github.com/csiro-robotics/Wild-Places)