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README.md

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-license: other
-license_name: license
-license_link: LICENSE
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+---
+license: other
+license_name: license
+license_link: LICENSE
+---
+<div align="center">
+<h1>WildCross: A Cross-Modal Large Scale Benchmark for Place Recognition and Metric Depth Estimation in Natural Environments</h1>
+
+[**Joshua Knights**](https://scholar.google.com/citations?user=RxbGr2EAAAAJ&hl=en)<sup>1,2</sup> · **Joseph Reid**<sup>1</sup> · [**Mark Cox**](https://scholar.google.com/citations?user=Bk3UD4EAAAAJ&hl=en)<sup>1</sup>
+<br>
+[**Kaushik Roy**](https://bit0123.github.io/)<sup>1</sup> · [**David Hall**](https://scholar.google.com/citations?user=dosODoQAAAAJ&hl=en)<sup>1</sup> · [**Peyman Moghadam**](https://scholar.google.com.au/citations?user=QAVcuWUAAAAJ&hl=en)<sup>1,2</sup>
+
+<sup>1</sup>DATA61, CSIRO&emsp;&emsp;&emsp;<sup>2</sup>Queensland University of Technology
+<br>
+
+<a href=""><img src='https://img.shields.io/badge/arXiv-WildCross-red' alt='Paper PDF'></a>
+<a href=''><img src='https://img.shields.io/badge/Project_Page-WildCross-green' alt='Project Page'></a>
+<a href='https://huggingface.co/CSIRORobotics/WildCross'><img src='https://img.shields.io/badge/Dataset_Download-WildCross-blue'></a>
+</div>
+
+This repository contains the pre-trained checkpoints for a variety of tasks on the WildCross benchmark
+
+![teaser](./teaser.png)
+
+If you find this repository useful or use the WildCross dataset in your work, please cite us using the following:
+```
+@misc{knights2025wildcross,
+  title={{WildCross: A Cross-Modal Large Scale Benchmark for Place Recognition and Metric Depth Estimation in Natural Environments}},
+  author={Joshua Knights, Joseph Reid, Mark Cox, Kaushik Roy, David Hall, Peyman Moghadam},
+  year={2025},
+  eprint={xxxxxxxxx},
+  archivePrefix={arXiv},
+  primaryClass={cs.CV},
+  url={https://arxiv.org/abs/xxxxxxxxxx},
+}
+
+
+```
+
+## Download Instructions
+Our dataset can be downloaded through the [**CSIRO Data Access Portal**]('').  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 for a variety of tasks on WildCross. 
+
+**Visual Place Recognition**
+### Checkpoints
+| Model      | Checkpoint Folder|
+|------------|------------|
+| NetVlad | [Link](https://huggingface.co/CSIRORobotics/WildCross/tree/main/VPR/NetVLAD)       |
+| MixVPR | [Link](https://huggingface.co/CSIRORobotics/WildCross/tree/main/VPR/MixVPR)       |
+| SALAD | [Link](https://huggingface.co/CSIRORobotics/WildCross/tree/main/VPR/SALAD)       |
+| BoQ | [Link](https://huggingface.co/CSIRORobotics/WildCross/tree/main/VPR/BoQ)       |
+
+**Cross Modal Place Recognition**
+### Checkpoints
+| Model      | Checkpoint Folder|
+|------------|------------|
+| Lip-Loc (ResNet50) | [Link](https://huggingface.co/CSIRORobotics/WildCross/tree/main/crossmodal/resnet50)       |
+| Lip-Loc (Dino-v2)  | [Link](https://huggingface.co/CSIRORobotics/WildCross/tree/main/crossmodal/dinov2)       |
+| Lip-Loc (Dino-v3) | [Link](https://huggingface.co/CSIRORobotics/WildCross/tree/main/crossmodal/dinov3)       |
+
+**Metric Depth Estimation**
+### Checkpoints
+| Model      | Checkpoint Folder|
+|------------|------------|
+| DepthAnythingV2-vits | [Link](https://huggingface.co/CSIRORobotics/WildCross/resolve/main/DepthAnythingV2/finetuned/vits.pth)       |
+| DepthAnythingV2-vitb | [Link](https://huggingface.co/CSIRORobotics/WildCross/resolve/main/DepthAnythingV2/finetuned/vitb.pth)       |
+| DepthAnythingV2-vitl | [Link](https://huggingface.co/CSIRORobotics/WildCross/resolve/main/DepthAnythingV2/finetuned/vitl.pth)       |
+
+For instructions on how to use these checkpoints for training or evaluation, further instructions can be found on the [WildCross GitHub repository]().