# Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset

arXiv: https://arxiv.org/abs/2002.10152 · HTML: https://mlsanity.com/paper/2002.10152/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Feb 2020.

## Built on by (most cited first, 28 of 28)

- [Visual Cross-View Metric Localization with Dense Uncertainty Estimates](https://mlsanity.com/paper/2208.08519/) (2022)
- [Convolutional Cross-View Pose Estimation](https://mlsanity.com/paper/2303.05915/) (2023)
- [Hyperdimensional computing as a framework for systematic aggregation of image descriptors](https://mlsanity.com/paper/2101.07720/) (2021)
- [Learning Dense Flow Field for Highly-accurate Cross-view Camera Localization](https://mlsanity.com/paper/2309.15556/) (2023)
- [Probabilistic Visual Place Recognition for Hierarchical Localization](https://mlsanity.com/paper/2105.03091/) (2021)
- [DurLAR: A High-fidelity 128-channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-modal Autonomous Driving Applications](https://mlsanity.com/paper/2406.10068/) (2024)
- [MSSPlace: Multi-Sensor Place Recognition with Visual and Text Semantics](https://mlsanity.com/paper/2407.15663/) (2024)
- [Beyond ANN: Exploiting Structural Knowledge for Efficient Place Recognition](https://mlsanity.com/paper/2103.08366/) (2021)
- [Probabilistic Appearance-Invariant Topometric Localization with New Place Awareness](https://mlsanity.com/paper/2107.07707/) (2021)
- [Deep Declarative Dynamic Time Warping for End-to-End Learning of Alignment Paths](https://mlsanity.com/paper/2303.10778/) (2023)
- [Tight Integration of Feature-based Relocalization in Monocular Direct Visual Odometry](https://mlsanity.com/paper/2102.01191/) (2021)
- [Unsupervised Quality Prediction for Improved Single-Frame and Weighted Sequential Visual Place Recognition](https://mlsanity.com/paper/2307.01464/) (2023)
- [ImPosing: Implicit Pose Encoding for Efficient Visual Localization](https://mlsanity.com/paper/2205.02638/) (2022)
- [CPO: Change Robust Panorama to Point Cloud Localization](https://mlsanity.com/paper/2207.05317/) (2022)
- [Learning to Predict Repeatability of Interest Points](https://mlsanity.com/paper/2105.03578/) (2021)
- [Is That Rain? Understanding Effects on Visual Odometry Performance for Autonomous UAVs and Efficient DNN-based Rain Classification at the Edge](https://mlsanity.com/paper/2407.12663/) (2024)
- [Flexible and Efficient Spatio-Temporal Transformer for Sequential Visual Place Recognition](https://mlsanity.com/paper/2510.04282/) (2025)
- [Deep auxiliary learning for visual localization using colorization task](https://mlsanity.com/paper/2107.00222/) (2021)
- [RADA: Robust Adversarial Data Augmentation for Camera Localization in Challenging Weather](https://mlsanity.com/paper/2112.02469/) (2021)
- [Mobile Mapping Mesh Change Detection and Update](https://mlsanity.com/paper/2303.07182/) (2023)
- [ANNA: A Deep Learning Based Dataset in Heterogeneous Traffic for Autonomous Vehicles](https://mlsanity.com/paper/2401.11358/) (2024)
- [SID: Stereo Image Dataset for Autonomous Driving in Adverse Conditions](https://mlsanity.com/paper/2407.04908/) (2024)
- [Robust Vehicle Localization and Tracking in Rain using Street Maps](https://mlsanity.com/paper/2409.01038/) (2024)
- [NPSim: Nighttime Photorealistic Simulation From Daytime Images With Monocular Inverse Rendering and Ray Tracing](https://mlsanity.com/paper/2502.10720/) (2025)
- [Towards classification-based representation learning for place recognition on LiDAR scans](https://mlsanity.com/paper/2511.00738/) (2025)
- [Virtual-point-based Solutions to Handle Generalized Absolute Pose Problem](https://mlsanity.com/paper/2606.09294/) (2026)
- [WildCity: A Real-World City-Scale Testbed for Rendering, Simulation, and Spatial Intelligence](https://mlsanity.com/paper/2607.06838/) (2026)
- [A Multi-Vehicle Dataset with Camera, LiDAR, and Radar Sensors and Scanned 3D Models for Custom Auto-Annotation using RTK-GNSS](https://mlsanity.com/paper/2609.12871/) (2026)

## Abstract (arXiv)

We describe the release of reference data towards a challenging long-term localisation and mapping benchmark based on the large-scale Oxford RobotCar Dataset. The release includes 72 traversals of a route through Oxford, UK, gathered in all illumination, weather and traffic conditions, and is representative of the conditions an autonomous vehicle would be expected to operate reliably in. Using post-processed raw GPS, IMU, and static GNSS base station recordings, we have produced a globally-consistent centimetre-accurate ground truth for the entire year-long duration of the dataset. Coupled with a planned online benchmarking service, we hope to enable quantitative evaluation and comparison of different localisation and mapping approaches focusing on long-term autonomy for road vehicles in urban environments challenged by changing weather.