List of Datasets

Automotive

Waymo Open Dataset

Autonomous-driving perception

Paper-era Perception collection: 1150 twenty-second scenes with five cameras, five lidars, ego poses and human 2D/3D box/tracking annotations.

Metadata: Complete Metadata curator reviewed Released 2019

Primary places to inspect, download, read about, or reproduce the dataset.

Supplementary

Not reported

Quick facts

Vehicle type
Automotive
Environment
Outdoor
Data origin
Real-world
Sensor count
10
Ground truth
Available
Calibration
Parameters Only
Annotations
Available

Sensor overview

High-level sensor availability before the detailed sensor records below.

Cameras

5 reported

IMUs

Not reported

GNSS

Not reported

LiDAR

5 reported

Radar

Not reported

Magnetometers

Not reported

Barometers

Not reported

UWB

Not reported

Ground truth

Reference scope, method, rate, coverage, and provenance.

Scope Method Reference system Count Rate Coverage Reference provenance
External
Measured using equipment independent of the platform’s normal onboard sensor pipeline.
Derived
Computed primarily from the dataset’s own recorded sensors.
Hybrid
Combines independent reference equipment with onboard measurements.
6DoF Other Not reported Not reported Not reported Full Reference provenance
External
Measured using equipment independent of the platform’s normal onboard sensor pipeline.
Derived
Computed primarily from the dataset’s own recorded sensors.
Hybrid
Combines independent reference equipment with onboard measurements.
Unknown
Reference notes
Vehicle-to-global ENU transforms are supplied; their estimator/survey origin and quantified accuracy are not specified. Per-return poses are the same coherent source, not extra references.
3D position + heading Manual annotation Not reported Not reported 10 Hz Partial · Train/Validation Labeled Objects Within Valid Range/Visibility and Outside No-Label Zones Reference provenance
External
Measured using equipment independent of the platform’s normal onboard sensor pipeline.
Derived
Computed primarily from the dataset’s own recorded sensors.
Hybrid
Combines independent reference equipment with onboard measurements.
Derived
Reference notes
3D boxes include dimensions and heading plus identities. Seven box parameters do not mean a 7-DoF ego pose.
2D Manual annotation Not reported Not reported 10 Hz Partial · Train/Validation Visible 2D Vehicle/Pedestrian/Cyclist Instances Reference provenance
External
Measured using equipment independent of the platform’s normal onboard sensor pipeline.
Derived
Computed primarily from the dataset’s own recorded sensors.
Hybrid
Combines independent reference equipment with onboard measurements.
Derived
Reference notes
Separate image box annotation with tracking identities; not pixel instance-segmentation masks.

Calibration and synchronization

Reported calibration level, reproducibility signals, and supporting notes.

Level
Parameters Only
Processed parameters
Available
Raw calibration data
Not reported
Calibration targets
Not reported

Parameters only

Processed calibration parameters are reported, but raw calibration data is not reported.

Notes

Sensor-to-vehicle extrinsics provided; raw calibration recordings are not established.

Known or intentional limitations

Reported constraints and characteristics to check before using the dataset.

Public annotation coverage excludes held-out test labels and no-label zones.

Rolling shutter, cropped camera views and restricted LiDAR ranges affect sensor coverage.

Geographic domain shift and object-class imbalance influence reported perception performance.

Counts and annotation inventory describe the analysed 2020 Perception release, not the current download catalog. Later Perception extensions and the separate Motion and End-to-End datasets are outside this entry’s quantitative scope.

The official download route requires Google sign-in and dataset terms; archive inventory and access were not verified behind authentication.

Ego-pose metadata has no established independent generation or accuracy guarantee in the analysed source.

Cameras

Camera 1

Model
Not reported
Setup
Mono
Count
3
Effective cameras
3
Modality
Rgb
Resolution
1920 x 1280
Rate
10 Hz
Shutter
Rolling
Lens type
Not Reported
HFOV
Not reported
VFOV
Not reported
Notes
Front/front-left/front-right group. Models are not specified; rolling timing/readout varies by scene.

Camera 2

Model
Not reported
Setup
Mono
Count
2
Effective cameras
2
Modality
Rgb
Resolution
1920 x 1040
Rate
10 Hz
Shutter
Rolling
Lens type
Not Reported
HFOV
Not reported
VFOV
Not reported
Notes
Side-left/side-right group. Models are not specified; rolling timing/readout varies by scene.

IMUs

Not reported

GNSS

Not reported

LiDAR

LiDAR 1

Model or name
LiDAR 1
Count
1
Dimensions
3
Rate
10 Hz
Channels
Not reported
Range
75 m

LiDAR 2

Model or name
LiDAR 2
Count
4
Dimensions
3
Rate
10 Hz
Channels
Not reported
Range
20 m

Radar

Not reported

Additional sensors

Not reported

Annotations

Reported annotation availability and task support.

Availability
Available
Format
3D oriented boxes and separately annotated 2D image boxes with tracking identities; signs are 3D-only in the stated taxonomy.
Class count
[vehicle pedestrian cyclist sign]
Semantic segmentation Not reported
Instance segmentation Not reported
Object detection Available
Optical flow Not reported
Depth ground truth Not reported

Citation

Citation key and BibTeX kept at the end of the page for reference.

Citation key
sun2020waymo

BibTeX

@misc{sun2020waymo,
  title = {Scalability in Perception for Autonomous Driving: Waymo Open Dataset},
  author = {Pei Sun and Henrik Kretzschmar and Xerxes Dotiwalla and Aurélien Chouard and Vijaysai Patnaik and Paul Tsui and James Guo and Yin Zhou and Yuning Chai and Benjamin Caine and Vijay Vasudevan and Wei Han and Jiquan Ngiam and Hang Zhao and Aleksei Timofeev and Scott Ettinger and Maxim Krivokon and Amy Gao and Aditya Joshi and Sheng Zhao and Shuyang Cheng and Yu Zhang and Jonathon Shlens and Zhifeng Chen and Dragomir Anguelov},
  year = {2020},
  eprint = {1912.04838v7},
  archivePrefix = {arXiv}
}

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