wabdalm/kvqa
KVQA: Knowledge-aware Visual Question Answering KVQA is a visual question-answering dataset created by Sanket Shah, Anand Mishra, Naganand Yadati, and Partha Pratim Talukdar at IIIT Hyderabad / IISc. It is designed for questions about named entities in images that require world knowledge and reasoning over a knowledge graph. The original release contains 24,602 images, approximately 183,000 manually verified question-answer pairs, more than 18,000 named entities, and a… See the full description on the dataset page: https://huggingface.co/datasets/wabdalm/kvqa.
| Author / organization | wabdalm |
|---|---|
| License (as declared) | other |
| Downloads | 707 (as reported by Hugging Face) |
| Likes | 1 |
| Created | 6 September 2026 |
| Last updated at source | 7 September 2026 |
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