* [ Papers With Code ](https://www.paperswithcode.com/datasets) \- Thousands of machine learning datasets provided by Papers With Code. 
  * [ KITTI-360 ](https://github.com/autonomousvision/kitti360Scripts) \- This large-scale dataset contains 320k images and 100k laser scans in a driving distance of 73.7km. 
  * [ waymo_ros ](https://github.com/YonoHub/waymo_ros) \- This is a ROS package to connect Waymo open dataset to ROS. 
  * [ waymo-open-dataset ](https://github.com/waymo-research/waymo-open-dataset) \- The Waymo Open Dataset is comprised of high-resolution sensor data collected by Waymo self-driving cars in a wide variety of conditions. 
  * [ Ford Autonomous Vehicle Dataset ](https://avdata.ford.com/home/default.aspx) \- Ford presents a challenging multi-agent seasonal dataset collected by a fleet of Ford autonomous vehicles at different days and times. 
  * [ awesome-robotics-datasets ](https://github.com/sunglok/awesome-robotics-datasets) \- A collection of useful datasets for robotics and computer vision. 
  * [ nuscenes-devkit ](https://github.com/nutonomy/nuscenes-devkit) \- The devkit of the nuScenes dataset. 
  * [ dataset-api ](https://github.com/ApolloScapeAuto/dataset-api) \- This is a repo of toolkit for ApolloScape Dataset, CVPR 2019 Workshop on Autonomous Driving Challenge and ECCV 2018 challenge. 
  * [ utbm_robocar_dataset ](https://github.com/epan-utbm/utbm_robocar_dataset) \- EU Long-term Dataset with Multiple Sensors for Autonomous Driving. 
  * [ DBNet ](https://github.com/driving-behavior/DBNet) \- A Large-Scale Dataset for Driving Behavior Learning. 
  * [ argoverse-api ](https://github.com/argoai/argoverse-api) \- Official GitHub repository for Argoverse dataset. 
  * [ DDAD ](https://github.com/TRI-ML/DDAD) \- A new autonomous driving benchmark from TRI (Toyota Research Institute) for long range (up to 250m) and dense depth estimation in challenging and diverse urban conditions. 
  * [ pandaset-devkit ](https://github.com/scaleapi/pandaset-devkit) \- Public large-scale dataset for autonomous driving provided by Hesai & Scale. 
  * [ a2d2_to_ros ](https://gitlab.com/MaplessAI/external/a2d2_to_ros) \- Utilities for converting A2D2 data sets to ROS bags. 
  * [ awesome-satellite-imagery-datasets ](https://github.com/chrieke/awesome-satellite-imagery-datasets) \- List of satellite image training datasets with annotations for computer vision and deep learning. 
  * [ sentinelsat ](https://github.com/sentinelsat/sentinelsat) \- Search and download Copernicus Sentinel satellite images. 
  * [ adas-dataset-form ](https://www.flir.com/oem/adas/adas-dataset-form/) \- Thermal Dataset for Algorithm Training. 
  * [ h3d ](https://usa.honda-ri.com/h3d) \- The H3D is a large scale full-surround 3D multi-object detection and tracking dataset from Honda. 
  * [ Mapillary Vistas Dataset ](https://www.mapillary.com/dataset/vistas) \- A diverse street-level imagery dataset with pixel‑accurate and instance‑specific human annotations for understanding street scenes around the world. 
  * [ TensorFlow Datasets ](https://www.tensorflow.org/datasets/catalog/overview) \- TensorFlow Datasets provides many public datasets as tf.data.Datasets. 
  * [ racetrack-database ](https://github.com/TUMFTM/racetrack-database) \- Contains center lines (x- and y-coordinates), track widths and race lines for over 20 race tracks (mainly F1 and DTM) all over the world. 
  * [ BlenderProc ](https://github.com/DLR-RM/BlenderProc) \- A procedural Blender pipeline for photorealistic training image generation. 
  * [ Atlatec Sample Map Data ](https://www.atlatec.de/getsampledata.html) \- 3D map for autonomous driving and simulation created from nothing but two cameras and GPS in downtown San Francisco. 
  * [ Lyft Level 5 Dataset ](https://self-driving.lyft.com/level5/data/) \- Level 5 is developing a self-driving system for the Lyft network. We're collecting and processing data from our autonomous fleet and sharing it with you. 
  * [ holicity ](https://github.com/zhou13/holicity) \- A City-Scale Data Platform for Learning Holistic 3D Structures. 
  * [ UTD19 ](https://utd19.ethz.ch/) \- Largest multi-city traffic dataset publically available. 
  * [ ASTYX HIRES2019 DATASET ](http://www.pinchofintelligence.com/visualising-lidar-and-radar-in-virtual-reality/) \- Automotive Radar Dataset for Deep Learning Based 3D Object Detection. 
  * [ Objectron ](https://github.com/google-research-datasets/Objectron/) \- A collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment. 
  * [ ONCE dataset ](https://once-for-auto-driving.github.io/index.html) \- A large-scale autonomous driving dataset with 2D&3D object annotations.