Add a bit more info to the dataset README

README.md

@@ -1,8 +1,57 @@
 ---
 license: cc-by-nc-sa-4.0
+tags:
+- robotics
+- computer-vision
+- lidar
+- slam
+- 3d-reconstruction
+- novel-view-synthesis
+size_categories:
+- 10GB<n<100GB
+pretty_name: 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](https://dynamic.robots.ox.ac.uk/datasets/oxford-spires/)
-- [Arxiv](https://arxiv.org/abs/2411.10546)
-- [video](https://youtu.be/AKZ-YrOob_4?si=rY94Gn96V2zfQBNH)
-- [code](https://github.com/ori-drs/oxford_spires_dataset)
+
+# Oxford Spires Dataset
+
+A large-scale multi-modal dataset for benchmarking LiDAR-Visual localisation, reconstruction and radiance field methods, captured at historic landmarks in Oxford.
+
+## Dataset Description
+
+The Oxford Spires Dataset provides high-quality sensor data with millimetre-accurate ground truth for evaluating SLAM, Structure-from-Motion, Multi-view Stereo, and radiance field methods (NeRF, 3D Gaussian Splatting).
+
+### Sensors
+- **3 RGB Cameras**: Global shutter, 1.6MP (1440×1080), 20Hz, 126°×92.4° FoV
+- **LiDAR**: Hesai QT64, 64 channels, 10Hz, 104° FoV, 60m range
+- **IMU**: 400Hz
+- **Ground Truth**: Millimetre-accurate 3D models from Leica RTC360 terrestrial scanner
+
+### Coverage
+- **6 Historic Sites**: Bodleian Library, Blenheim Palace, Christ Church College, Keble College, Radcliffe Observatory Quarter, New College
+- **24 Sequences**: ~400m average distance per sequence
+- **Scale**: ~1 hectare average area per site
+
+### Benchmarks
+- Localisation evaluation
+- 3D reconstruction quality assessment  
+- Novel-view synthesis (including challenging out-of-sequence poses)
+
+## Links
+- [Project Page](https://dynamic.robots.ox.ac.uk/datasets/oxford-spires/)
+- [Paper (arXiv)](https://arxiv.org/abs/2411.10546)
+- [Video](https://youtu.be/AKZ-YrOob_4?si=rY94Gn96V2zfQBNH)
+- [Code & Tools](https://github.com/ori-drs/oxford_spires_dataset)
+
+## Citation
+
+```bibtex
+@misc{tao2024oxfordspiresdatasetbenchmarking,
+      title={The Oxford Spires Dataset: Benchmarking Large-Scale LiDAR-Visual Localisation, Reconstruction and Radiance Field Methods}, 
+      author={Yifu Tao and Miguel Ángel Muñoz-Bañón and Lintong Zhang and Jiahao Wang and Lanke Frank Tarimo Fu and Maurice Fallon},
+      year={2024},
+      eprint={2411.10546},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2411.10546}, 
+}
+```