List of Datasets

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TartanAir

Synthetic visual SLAM and multimodal learning

Simulated stereo trajectories across diverse virtual environments, with poses, depth, semantic labels, static-scene optical flow and sampled LiDAR.

Metadata: Complete Metadata curator reviewed Released 2020

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

Supplementary

Not reported

Quick facts

Vehicle type
Other
Environment
Indoor, Outdoor
Data origin
Simulation
Sensor count
3
Ground truth
Available
Calibration
Not reported
Annotations
Available

Sensor overview

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

Cameras

2 reported

IMUs

Not reported

GNSS

Not reported

LiDAR

1 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.
Derived
Accuracy notes
Exact simulator state is not a numeric real-world positioning error.
Reference notes
Simulator camera poses, internally defined in the virtual environment; no external physical metrology.
Other 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.
Derived
Reference notes
Depth comes from the renderer; disparity is a conversion of the same depth source, not a second independent reference.
Other 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.
Derived
Reference notes
Simulator semantic labels; selected paper does not define a complete released label taxonomy.
Other Other Not reported Not reported Not reported Partial · Static-Scene Frame Pairs and Valid Non-Occluded/In-View Pixels 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
Optical flow uses depth/pose warping. Do not infer dynamic-object true motion labels from this static-scene construction.

Calibration and synchronization

Reported calibration level, reproducibility signals, and supporting notes.

Level
Not reported
Processed parameters
Not reported
Raw calibration data
Not reported
Calibration targets
Not reported

Calibration data

Calibration reproducibility details are not reported.

Notes

Not reported

Known or intentional limitations

Reported constraints and characteristics to check before using the dataset.

Synthetic optics, noise and motion blur differ from real sensors.

Depth/pose-derived optical flow is defined for static scenes and masked invalid pixels.

Success-only trajectory error can hide failed runs; report robustness alongside accuracy.

Sequence count and storage retain the analysed 2020 collection scope, rather than a current TartanAir V2 inventory. Virtual lidar and calibration packaging remain incompletely specified.

Cameras

Camera 1

Model
Not reported
Setup
Stereo
Count
1
Effective cameras
2
Modality
Rgb
Resolution
Not reported
Rate
Not reported
Shutter
Not Reported
Lens type
Not Reported
HFOV
Not reported
VFOV
Not reported
Notes
Virtual stereo RGB rig. Paper does not state released resolution, frame cadence or shutter type; depth/semantic outputs are labels from this acquisition, not extra physical cameras.

IMUs

Not reported

GNSS

Not reported

LiDAR

LiDAR 1

Model or name
LiDAR 1
Count
1
Dimensions
3
Rate
Not reported
Channels
Not reported
Range
Not reported

Radar

Not reported

Additional sensors

Not reported

Annotations

Reported annotation availability and task support.

Availability
Available
Format
Not reported
Class count
Not reported
Semantic segmentation Available
Instance segmentation Not reported
Object detection Not reported
Optical flow Available
Depth ground truth Available

Citation

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

Citation key
wang2020tartanair

BibTeX

@misc{wang2020tartanair,
  title = {TartanAir: A Dataset to Push the Limits of Visual SLAM},
  author = {Wenshan Wang and Delong Zhu and Xiangwei Wang and Yaoyu Hu and Yuheng Qiu and Chen Wang and Yafei Hu and Ashish Kapoor and Sebastian Scherer},
  year = {2020},
  eprint = {2003.14338v2},
  archivePrefix = {arXiv}
}

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