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Name Sensing Modalities Year (published) Labelled (benchmark) Recording area Size Categories / Remarks Link
Ford AV Dataset [ref]Visual camera (7), 3D LiDAR (4)20206 DoF PoseMichigan 1.6 TB (amount of frames not given); Seasonal variation in weather, lighting, construction and traffic conditionsDataset Website
Toyota Research Institute DDAD [ref]Visual camera (6), 3D LiDAR2020DepthSan Francisco, Bay Area, Cambridge, Detroit, Ann Arbor, Tokyo, Odaiba Labeled: 99k frames (camera); 200 scenesLong-range depth (~250m)Dataset Website
PandaSet [ref]3D LiDAR (2), Visual cameras (6), GNSS and inertial sensors20203D bounding boxSan Francisco, El Camino Real48k frames (camera), 16k frames (LiDAR), 100+ scenes28 classes, 37 semantic segmentation labels; Solid state LiDARDataset Website
CADC [ref]Visual camera (8), 3D LiDAR20203D bounding boxesWaterloo (Canada) Labeled: 56k frames (camera), 7k frames (LiDAR); Raw: 263k frames (camera), 32k frames (LiDAR)Car, Pedestrian, Truck, Bus, Garbage Containers on Wheels, Traffic Guidance Objects, Bicycle, Pedestrian With Object, Horse and Buggy, Animals; Adverse Weather conditions, different intensities of snowfallDataset Website
Astyx HiRes2019 [ref]Radar, Visual camera, 3D LiDAR20193D bounding boxesn.a. 500 frames (5000 annotated objects)Car, Bus, Cyclist, Motorcyclist, Person, Trailer, TruckDataset Website
A2D2 [ref]Visual cameras (6); 3D LiDAR (5); Bus data20192D/3D bounding boxes, 2D/3D instance segmentationGaimersheim, Ingolstadt, Munich40k frames (semantics), 12k frames (3D objects), 390k frames unlabeledCar, Bicycle, Pedestrian, Truck, Small vehicles, Traffic signal, Utility vehicle, Sidebars, Speed bumper, Curbstone, Solid line, Irrelevant signs, Road blocks, Tractor, Non-drivable street, Zebra crossing, Obstacles / trash, Poles, RD restricted area, Animals, Grid structure, Signal corpus, Drivable cobbleston, Electronic traffic, Slow drive area, Nature object, Parking area, Sidewalk, Ego car, Painted driv. instr., Traffic guide obj., Dashed line, RD normal street, Sky, Buildings, Blurred area, Rain dirtDataset Website
A*3D Dataset [ref]Visual cameras (2); 3D LiDAR20193D bounding boxesSingapore39k frames, 230k objectsCar, Van, Bus, Truck, Pedestrians, Cyclists, and Motorcyclists; Afternoon and night, wet and dryDataset Website
EuroCity Persons [ref]Visual camera; Announced: stereo, LiDAR, GNSS and intertial sensors20192D bounding boxes12 countries in Europe, 27 cities47k frames, 258k objectsPedestrian, Rider, Bicycle, Motorbike, Scooter, Tricycle, Wheelchair, Buggy, Co-Rider; Highly diverse: 4 seasons, day and night, wet and dryDataset Website
Oxford RobotCar [ref] (2016),[ref] (2019)2016: Visual cameras (fisheye & stereo), 2D & 3D LiDAR, GNSS, and inertial sensors; 2019: Radar, 3D Lidar (2), 2D LiDAR (2), visual cameras (6), GNSS and inertial sensors2016, 2019noOxford2016: 11,070,651 frames (stereo), 3,226,183 frames (3D LiDAR); 2019: 240k scans (Radar), 2.4M frames (LiDAR)Long-term autonomous driving. Various weather conditions, including heavy rain, night, direct sunlight and snow.Dataset Website 2016, Dataset Website 2019
Waymo Open Dataset [ref]3D LiDAR (5), Visual cameras (5)20193D bounding box, Trackingn.a.200k frames, 12M objects (3D LiDAR), 1.2M objects (2D camera)Vehicles, Pedestrians, Cyclists, SignsDataset Website
Lyft Level 5 AV Dataset 2019 [ref]3D LiDAR (5), Visual cameras (6)20193D bounding boxn.a.55k framesSemantic HD map includedDataset Website
Argoverse [ref]3D LiDAR (2), Visual cameras (9, 2 stereo)20193D bounding box, Tracking, ForecastingPittsburgh, Pennsylvania, Miami, Florida113 scenes, 300k trajectoriesVehicle, Pedestrian, Other Static, Large Vehicle, Bicycle, Bicyclist, Bus, Other Mover, Trailer, Motorcyclist, Moped, Motorcycle, Stroller, Emergency Vehicle, Animal, Wheelchair, School Bus; Semantic HD maps (2) includedDataset Website
nuScenes dataset [ref] Visual cameras (6), 3D LiDAR, Radars (5) 2019 3D bounding box Boston, Singapore 1000 scenes, 1.4M frames (camera, Radar), 390k frames (3D LiDAR) Car or Van or SUV, Truck, Pickup Truck, Front Of Semi Truck, Bendy Bus, Rigid Bus, Construction Vehicle, Motorcycle, Bicycle, Bicycle Rack, Trailer, Police Vehicle, Ambulance, Train, Adult Pedestrian, Child Pedestrian, Construction Worker, Stroller, Wheelchair, Portable Personal Mobility Vehicle, Traffic Police, Other Police, Animal, Traffic Cone, Temporary Traffic Barrier, Pushable Pullable Object, Debris Dataset Website
BLVD [ref] Visual (Stereo) camera, 3D LiDAR 2019 3D bounding box, Tracking, Interaction, Intention Changshu 120k frames, 249,129 objects Vehicle, Pedestrian, Rider during day and night Dataset Website
H3D dataset [ref] Visual cameras (3), 3D LiDAR 2019 3D bounding box San Francisco 27,721 frames, 1,071,302 objects Car, Pedestrian, Cyclist, Truck, Misc, Animal, Motorcyclist, Bus Dataset Website
ApolloScape [ref] Visual (Stereo) camera, 3D LiDAR, GNSS and inertial sensors 2018, 2019 2D/3D pixel-level segmentation, lane marking, instance segmentation, Depth n.a. 143,906 frames, 89,430 objects Rover, Sky, Car, Motobicycle, Bicycle, Person, Rider, Truck, Bus, Tricycle, Road, Sidewalk, Traffic Cone, Road Pile, Fence, Traffic Light, Pole, Traffic Sign, Wall, Dustbin, Billboard, Building, Bridge, Tunnel, Overpass, Vegetation Dataset Website
DBNet dataset [ref]3D LiDAR, Dashboard visual camera, GNSS 2018 Driving behaviours (Vehicle speed and wheel angles) Multiple areas in China Over 10k frames In total seven datasets with different test scenarios, such as seaside roads, school areas, mountain roads Dataset Website
KAIST multispectral dataset [ref] Visual (Stereo) and thermal camera, 3D LiDAR, GNSS and inertial sensors 2018 2D bounding box, drivable region, image enhancement, depth, colorization Seoul 7,512 frames, 308,913 objects Person, Cyclist, Car during day and night, fine time slots (sunrise, afternoon,...) Dataset Website
Multi-spectral Object Detection dataset [ref] Visual and thermal cameras 2017 2D bounding box University environment in Japan 7,512 frames, 5,833 objects Bike, Car, Car Stop, Color Cone, Person during day and night Dataset Website
Multi-spectral Semantic Segmentation dataset [ref] Visual and thermal camera 2017 2D pixel-level segmentation n.a. 1569 frames Bike, Car, Person, Curve, Guardrail, Color Cone, Bump during day and night Dataset Website
Multi-modal Panoramic 3D Outdoor (MPO) dataset [ref] Visual camera, LiDAR and GNSS 2016 Place categorization Fukuoka 650 scans (dense), 34200 scans (sparse) No dynamic objects Dataset Website
KAIST multispectral pedestrian [ref] Visual and thermal camera 2015 2D bounding box Seoul 95,328 frames, 103,128 objects Person, People, Cyclist during day and night Dataset Website
KITTI [ref] (2012), [ref] (2013) Visual (Stereo) camera, 3D LiDAR, GNSS and inertial sensors 2012, 2013, 2015 2D, 3D bounding box, visual odometry, road detection, optical flow, tracking, depth, 2D instance and pixel-level segmentation Karlsruhe 7481 frames (training) 80.256 objects Car, Van, Truck, Pedestrian, Person (sitting), Cyclist, Tram, Misc Dataset Website
The Málaga Stereo and Laser Urban dataset [ref] Visual (Stereo) camera, 5x 2D LiDAR (yielding 3D information), GNSS and inertial sensors 2014 no Málaga 113,082 frames, 5,654.6 s (camera); >220,000 frames, ~5,000 s (LiDARs) n.a. Dataset Website