OCR Visual Question Answering Dataset

OCR VQA is a multimodal dataset for visual question answering tasks based on text extracted from images via optical character recognition. The dataset was created by qnguyen3 and uploaded to Hugging Face in October 2023. Specific details on the number of images, questions, or data volume are not provided in the available metadata.

Use Cases

• Train models to answer questions about text content extracted from images using OCR.
• Benchmark Visual Question Answering (VQA) systems on text-heavy images and documents.
• Develop and evaluate multimodal reasoning models that integrate recognized image text with natural language queries.

Strengths

• Dataset is hosted on a major platform (Hugging Face) with a specific last update timestamp (2023-10-23).
• Focuses on a defined multimodal task combining OCR, image, and text data.

Limitations

• No quantitative information is available on dataset size, number of rows, or sample counts.
• The license, data collection method, and geographic or temporal coverage are unknown.

Provenance

Source

Hugging Face, uploaded by user qnguyen3.

Collection Method

null

Time Range

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Freshness

Last updated in October 2023.

Geography

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