Dataset · Hugging Face

anwan/DisasterVQA

Name: DisasterVQA
Creator: anwan
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/anwan/DisasterVQA.

View on Hugging FaceReport an issue

Author / organization	anwan
License (as declared)	cc-by-sa-4.0
Downloads	165 (as reported by Hugging Face)
Likes	0
Created	16 July 2026
Last updated at source	16 July 2026

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

Embed this entry

<iframe src="https://silytics.si/embed/item/d4b12658-7b67-46c4-94d8-c91bd51e6c4c" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 16 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.