AirZoo: A Unified Large-Scale Dataset for Grounding Aerial Geometric 3D Vision
Paper • 2604.26567 • Published • 2
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AirZoo Data
Synthetic aerial training renders from the AirZoo project (RGB, metric depth, and poses).
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Renders were produced with Cesium for Unreal, Unreal Engine, and AirSim. Their licenses and terms still apply. Access here does not allow redistribution of the data.
Contents
AirZoo_TrainingData/— sequence archives
Related
- Engine: https://huggingface.co/datasets/choyaa/AirZoo-Engine
- Code: https://github.com/nudt-sawlab/AirZoo
- Benchmarks: https://huggingface.co/datasets/RingoWRW97/AirZoo-Real
- Website: https://nudt-sawlab.github.io/AirZoo/
Citation
@article{cheng2026airzoo,
title={AirZoo: A Unified Large-Scale Dataset for Grounding Aerial Geometric 3D Vision},
author={Cheng, Xiaoya and Wu, Rouwan and Liu, Xinyi and Cui, Zeyu and Liu, Yan and Zhao, Na and Liu, Yu and Zhang, Maojun and Yan, Shen},
journal={arXiv preprint arXiv:2604.26567},
year={2026}
}
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