ori-drs/oxford_spires_dataset

We present the Oxford Spires Dataset, captured in and around well-known landmarks in Oxford using a custom-built multi-sensor perception unit as well as a millimetre-accurate map from a terrestrial LiDAR scanner (TLS). The perception unit includes three global shutter colour cameras, an automotive 3D LiDAR scanner, and an inertial sensor — all precisely calibrated.

• Project page
• Paper
• Arxiv
• Video
• Code

Sample Usage

Download the Dataset

You can download the dataset from Hugging Face using the provided script. You can specify which folders to download by changing the example_pattern. Core sequences are also defined in the script.

python scripts/dataset_download.py

Install Python Tools

Install oxspires_tools to access Python utilities for using the dataset:

pip install .

To enable C++/Python bindings (requires PCL and Octomap):

BUILD_CPP=1 pip install .

Alternatively, use the provided Docker container:

docker compose -f .docker/oxspires/docker-compose.yml run --build oxspires_utils

Generate Depth Images

The following script downloads synchronised images and LiDAR data from a sequence on Hugging Face and generates depth images, LiDAR overlaid on camera images, and surface normal images:

python scripts/generate_depth.py

Citation

If you use The Oxford Spires Dataset in your research, please cite the following paper:

@article{tao2025spires,
title={The Oxford Spires Dataset: Benchmarking Large-Scale LiDAR-Visual Localisation, Reconstruction and Radiance Field Methods},
author={Tao, Yifu and Mu{\~n}oz-Ba{\~n}{\'o}n, Miguel {\'A}ngel and Zhang, Lintong and Wang, Jiahao and Fu, Lanke Frank Tarimo and Fallon, Maurice},
journal={International Journal of Robotics Research}, 
year={2025},
}