NLIP-lab/AeroCaps

Aerial Mirage: Unmasking Hallucinations in Large Vision Language Models

This repository hosts the AeroCaps dataset as a Hugging Face dataset.

The lack of image-caption datasets for drone imagery poses a significant challenge for training and evaluating drone image captioning. To address this gap, we contribute the first Aerial-view Image Captioning dataset. This contains atleast four captions per image. AeroCaps is introduced in WACV 2025.

Dataset Structure

Column	Type	Description
image	Image	Aerial-view photograph
captions	string	Comma-separated reference captions

Usage

from datasets import load_dataset

ds = load_dataset("NLIP-lab/AeroCaps")
sample = ds["train"][0]
print(sample["captions"])
sample["image"].show()

📜 Citation

If you use AeroCaps in your research, please cite:

@InProceedings{Debolena_WACV25,
    author    = {Basak, Debolena and Bhatt, Soham and Kanduri, Sahith and Desarkar, Maunendra Sankar},
    title     = {Aerial Mirage: Unmasking Hallucinations in Large Vision Language Models},
    booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
    month     = {February},
    year      = {2025},
    pages     = {5500-5508}
}

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⚖️ License

The AeroCaps dataset is intended for research purposes. Please see the the HF dataset card for terms.