Platform not reported

WildCross

Cross-modal place recognition and metric depth estimation

Eight forest traversals spanning fourteen months, with about 476K sequential color images, semi-dense depth and surface normals, SLAM-derived camera poses and dense lidar submaps.

Metadata: Partial Metadata needs review

Quick facts

Vehicle type
Not reported
Environment
Outdoor
Data origin
Real-world
Sensor count
2
Ground truth
Available
Calibration
Not reported
Annotations
Available

Sensor overview

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

Ground truth

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

Ground-truth references for WildCross
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 LiDAR SLAM Lidar-inertial SLAM Not reported 15 Hz 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
SLAM trajectory interpolation, camera extrinsic transformation and ICP alignment of session maps. No independently validated numeric accuracy is reported.
Other Other Not reported Not reported 15 Hz 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
Semi-dense ray-distance depth per image, projected from global lidar maps with normal-based filtering and generalized hidden point removal. Full coverage describes frames, not all pixels.

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

Image rectification uses calibrated distortion parameters; camera-to-SLAM extrinsics transform image poses. Availability of raw calibration sequences is not established.

Known or intentional limitations

Reported constraints and characteristics to check before using the dataset.

Metric depth is semi-dense; visibility filtering does not imply labels for every pixel.

Camera pose and depth references derive from lidar maps/SLAM; independent numeric accuracy remains unestablished.

Reverse trajectories create challenging viewpoint changes within and across sessions.

Exact quantitative VPR averages differ between Section V-A prose and Tables IV/V.

Cameras

forward_rgb

Model
Not reported
Setup
Not Reported
Count
1
Effective cameras
1
Modality
Rgb
Resolution
Not reported
Rate
15 Hz
Shutter
Not Reported
Lens type
Not Reported
HFOV
Not reported
VFOV
Not reported
Notes
Rectified images extracted from forward-facing video. Depth and surface normals are derived annotations, not a separate RGB-D device.

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

Pitot tube

Not reported

Additional sensors

Not reported

Annotations

Reported annotation availability and task support.

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

Citation

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

Citation key
Not reported

BibTeX

Not reported

Dataset corrections

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