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Awesome LIDAR

A curated list of awesome LIDAR sensors and its applications.

LIDAR is a remote sensing sensor that uses laser light to measure the surroundings in ~cm accuracy. The sensory data is usually referred as point cloud which means set of data points in 3D or 2D. The list contains hardwares, datasets, point cloud-processing algorithms, point cloud frameworks, simulators etc.

Contributions are welcome! Please check out our guidelines.



  • Any list item with an OctoCat :octocat: has a GitHub repo or organization
  • Any list item with a RedCircle πŸ”΄ has YouTube videos or channel
  • Any list item with a Paper πŸ“° has a scientific paper or detailed description



  • Ford Dataset - The dataset is time-stamped and contains raw data from all the sensors, calibration values, pose trajectory, ground truth pose, and 3D maps. The data is Robot Operating System (ROS) compatible.
  • Audi A2D2 Dataset - The dataset features 2D semantic segmentation, 3D point clouds, 3D bounding boxes, and vehicle bus data.
  • Waymo Open Dataset - The dataset contains independently-generated labels for lidar and camera data, not simply projections.
  • Oxford RobotCar - The Oxford RobotCar Dataset contains over 100 repetitions of a consistent route through Oxford, UK, captured over a period of over a year.
  • EU Long-term Dataset - This dataset was collected with our robocar (in human driving mode of course), equipped up to eleven heterogeneous sensors, in the downtown (for long-term data) and a suburb (for roundabout data) of MontbΓ©liard in France. The vehicle speed was limited to 50 km/h following the French traffic rules.
  • NuScenes - Public large-scale dataset for autonomous driving.
  • Lyft - Public dataset collected by a fleet of Ford Fusion vehicles equipped with LIDAR and camera.
  • KITTI - Widespread public dataset, pirmarily focusing on computer vision applications, but also contains LIDAR point cloud.
  • Semantic KITTI - Dataset for semantic and panoptic scene segmentation.
  • CADC - Canadian Adverse Driving Conditions Dataset - Public large-scale dataset for autonomous driving in adverse weather conditions (snowy weather).
  • UofTPed50 Dataset - University of Toronto, aUToronto's self-driving car dataset, which contains GPS/IMU, 3D LIDAR, and Monocular camera data. It can be used for 3D pedestrian detection.
  • PandaSet Open Dataset - Public large-scale dataset for autonomous driving provided by Hesai & Scale. It enables researchers to study challenging urban driving situations using the full sensor suit of a real self-driving-car.
  • Cirrus dataset A public datatset from non-uniform distribution of LIDAR scanning patterns with emphasis on long range. In this dataset Luminar Hydra LIDAR is used. The dataset is available at the Volvo Cars Innovation Portal.
  • USyd Dataset- The Univerisity of Sydney Campus- Dataset - Long-term, large-scale dataset collected over the period of 1.5 years on a weekly basis over the University of Sydney campus and surrounds. It includes multiple sensor modalities and covers various environmental conditions. ROS compatible




Basic matching algorithms​

Semantic segmentation​

Simultaneous localization and mapping SLAM and LIDAR-based odometry and or mapping LOAM​

Object detection and object tracking​



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