Datasets › VQA-HAT

VQA-HAT (VQA Human Attention)

Introduced by Abhishek Das et al. in Human Attention in Visual Question Answering: Do Humans and Deep Networks Look at the Same Regions?17 Jun 2016 archive 2025-07-28

VQA-HAT (Human ATtention) is a dataset to evaluate the informative regions of an image depending on the question being asked about it. The dataset consists of human visual attention maps over the images in the original VQA dataset. It contains more than 60k attention maps.

Source: Human Attention in Visual Question Answering:

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Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 27 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

Question Answering Visual Question Answering (VQA)Probabilistic Deep Learning

License archive 2025-07-28

Unknown

Modalities archive 2025-07-28

Images

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

VQA-HAT

1 variant name, as the archive lists them.

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