# OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving

arXiv: https://arxiv.org/abs/2205.14087 · HTML: https://mlsanity.com/paper/2205.14087/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 54 references that are in the map.
- First posted on arXiv 27 May 2022.

## Builds on (most cited first, 14 of 14)

- [CARLA: An Open Urban Driving Simulator](https://mlsanity.com/paper/1711.03938/) (2017)
- [Unsupervised Learning of Depth and Ego-Motion from Video](https://mlsanity.com/paper/1704.07813/) (2017)
- [BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation](https://mlsanity.com/paper/1808.00897/) (2018)
- [GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose](https://mlsanity.com/paper/1803.02276/) (2018)
- [DeMoN: Depth and Motion Network for Learning Monocular Stereo](https://mlsanity.com/paper/1612.02401/) (2016)
- [DeepV2D: Video to Depth with Differentiable Structure from Motion](https://mlsanity.com/paper/1812.04605/) (2018)
- [RegNet: Multimodal Sensor Registration Using Deep Neural Networks](https://mlsanity.com/paper/1707.03167/) (2017)
- [Monocular 3D Object Detection: An Extrinsic Parameter Free Approach](https://mlsanity.com/paper/2106.15796/) (2021)
- [BALM: Bundle Adjustment for Lidar Mapping](https://mlsanity.com/paper/2010.08215/) (2020)
- [Online Temporal Calibration for Monocular Visual-Inertial Systems](https://mlsanity.com/paper/1808.00692/) (2018)
- [CRLF: Automatic Calibration and Refinement based on Line Feature for LiDAR and Camera in Road Scenes](https://mlsanity.com/paper/2103.04558/) (2021)
- [Joint Camera Intrinsic and LiDAR-Camera Extrinsic Calibration](https://mlsanity.com/paper/2202.13708/) (2022)
- [Online Extrinsic Calibration based on Per-Sensor Ego-Motion Using Dual Quaternions](https://mlsanity.com/paper/2101.11440/) (2021)
- [CROON: Automatic Multi-LiDAR Calibration and Refinement Method in Road Scene](https://mlsanity.com/paper/2203.03182/) (2022)

## Built on by (most cited first, 18 of 18)

- [Towards Knowledge-driven Autonomous Driving](https://mlsanity.com/paper/2312.04316/) (2023)
- [OmniHD-Scenes: A Next-Generation Multimodal Dataset for Autonomous Driving](https://mlsanity.com/paper/2412.10734/) (2024)
- [From Indoor to Open World: Revealing the Spatial Reasoning Gap in MLLMs](https://mlsanity.com/paper/2512.19683/) (2025)
- [INF: Implicit Neural Fusion for LiDAR and Camera](https://mlsanity.com/paper/2308.14414/) (2023)
- [CoSEC: A Coaxial Stereo Event Camera Dataset for Autonomous Driving](https://mlsanity.com/paper/2408.08500/) (2024)
- [SensorX2car: Sensors-to-car calibration for autonomous driving in road scenarios](https://mlsanity.com/paper/2301.07279/) (2023)
- [EvTTC: An Event Camera Dataset for Time-to-Collision Estimation](https://mlsanity.com/paper/2412.05053/) (2024)
- [Poses as Queries: Image-to-LiDAR Map Localization with Transformers](https://mlsanity.com/paper/2305.04298/) (2023)
- [Improving Extrinsics between RADAR and LIDAR using Learning](https://mlsanity.com/paper/2305.10594/) (2023)
- [Multi-LiDAR Localization and Mapping Pipeline for Urban Autonomous Driving](https://mlsanity.com/paper/2311.01823/) (2023)
- [High-precision visual navigation device calibration method based on collimator](https://mlsanity.com/paper/2502.18012/) (2025)
- [ThermRad: A Multi-modal Dataset for Robust 3D Object Detection under Challenging Conditions](https://mlsanity.com/paper/2308.10161/) (2023)
- [TOMD: A Trail-based Off-road Multimodal Dataset for Traversable Pathway Segmentation under Challenging Illumination Conditions](https://mlsanity.com/paper/2506.21630/) (2025)
- [Revisiting Stereo Triangulation in UAV Distance Estimation](https://mlsanity.com/paper/2306.08939/) (2023)
- [Targetless 6DoF Calibration of LiDAR and 2D Scanning Radar Based on Cylindrical Occupancy](https://mlsanity.com/paper/2503.17002/) (2025)
- [Multi-View In-Cabin Monitoring System for Public Transport Vehicles](https://mlsanity.com/paper/2606.11739/) (2026)
- [Geometry-Preserving in 3D Gaussian Splatting for LiDAR-Camera Extrinsic Calibration](https://mlsanity.com/paper/2606.20103/) (2026)
- [Automatic Reproducible Camera Intrinsic Calibration](https://mlsanity.com/paper/2609.10082/) (2026)

## Abstract (arXiv)

Accurate sensor calibration is a prerequisite for multi-sensor perception and localization systems for autonomous vehicles. The intrinsic parameter calibration of the sensor is to obtain the mapping relationship inside the sensor, and the extrinsic parameter calibration is to transform two or more sensors into a unified spatial coordinate system. Most sensors need to be calibrated after installation to ensure the accuracy of sensor measurements. To this end, we present OpenCalib, a calibration toolbox that contains a rich set of various sensor calibration methods. OpenCalib covers manual calibration tools, automatic calibration tools, factory calibration tools, and online calibration tools for different application scenarios. At the same time, to evaluate the calibration accuracy and subsequently improve the accuracy of the calibration algorithm, we released a corresponding benchmark dataset. This paper introduces various features and calibration methods of this toolbox. To our knowledge, this is the first open-sourced calibration codebase containing the full set of autonomous-driving-related calibration approaches in this area. We wish that the toolbox could be helpful to autonomous driving researchers. We have open-sourced our code on GitHub to benefit the community. Code is available at https://github.com/PJLab-ADG/SensorsCalibration.