Dataset · Hugging Face

QCRI/DisasterVQA

Name: DisasterVQA
Creator: QCRI
License: cc-by-sa-4.0
Keywords: task_categories:visual-question-answering, task_categories:image-to-text, task_categories:question-answering, task_ids:visual-question-answering, source_datasets:Incidents1M, source_datasets:CrisisMMD, source_datasets:MEDIC, language:en, license:cc-by-sa-4.0, size_categories:1K<n<10K, format:imagefolder, modality:image, modality:text, library:datasets, library:mlcroissant

DisasterVQA: A Visual Question Answering Benchmark Dataset for Disaster Scenes Dataset Summary DisasterVQA is a benchmark dataset for evaluating Vision-Language Models (VLMs) on disaster-response visual question answering. It contains 1,395 real-world disaster images and 4,405 expert-curated question–answer pairs covering floods, wildfires, and earthquakes. The dataset includes three question types: Binary (Yes/No) Multiple-Choice Open-Ended Questions span… See the full description on the dataset page: https://huggingface.co/datasets/QCRI/DisasterVQA.

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Author / organization	QCRI
License (as declared)	cc-by-sa-4.0
Downloads	168 (as reported by Hugging Face)
Likes	1
Created	14 May 2026
Last updated at source	20 May 2026

DisasterVQAdisaster-responsehumanitariancrisis-informaticsVQAVLMvision-language-modelsdamage-assessmentsituational-awareness

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16 Oct 2026 Description: DisasterVQA: A Visual Question Answering Benchmark Dataset for Disaster Scenes Dataset Summary DisasterVQA is a benchmark dataset for evaluating Vision-Language Models (VLMs) on disaster-response visual question answering. It contains 1,395 → DisasterVQA: A Visual Question Answering Benchmark Dataset for Disaster Scenes Dataset Summary DisasterVQA is a benchmark dataset for evaluating Vision-Language Models (VLMs) on disaster-response visual question answering. It contains 1,395

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