AerialMetric-ECCV2026

This repository is the main dataset hub for the paper AerialMetric: Benchmarking and Adapting UAV Monocular Metric Depth Estimation in the Real World. It includes more than 65k aerial image-depth pairs, and all depth maps are metric.

• Project homepage: https://kuieless.github.io/AerialMetric-ECCV2026-page/
• Repository: https://github.com/kuieless/AerialMetric-ECCV2026

It contains the training data, test data, and the moge2-aerial weights used by the project.

Files

Depth data

• Train-Split/AerialMetric-Oblique/: oblique assets and merged metadata (25 scenes)
• Train-Split/AerialMetric-Synthetic/: synthetic assets
• Test-Split/AerialMetric-Decoupled/: decoupled assets (4 pitch angles x 2 altitudes x 2 FOV angles)
• Test-Split/AerialMetric-Wild/: wild assets (100 scenes)

Metadata

• Train-Split/AerialMetric-Oblique/final_merged.csv: merged metadata table for the project.
• Test-Split/AerialMetric-Decoupled-Full-Metadata.zip: provides reconstructed outputs and flight parameters for the decoupled test data.

Weight

• weights/: moge2-aerial weights

Demo

• demo/: 12 RGB images paired with their corresponding metric-depth visualizations.
• demo/demo.parquet: 12 paired records used by the Dataset Viewer.

Notes

• This repository consolidates the AerialMetric dataset release into one place.