Datasets › ViQuAE

ViQuAE

Introduced by Paul Lerner et al. in ViQuAE, a Dataset for Knowledge-based Visual Question Answering about Named Entities11 Jul 2022 archive 2025-07-28

ViQuAE is a dataset for KVQAE (Knowledge-based Visual Question Answering about named Entities), a task which consists in answering questions about named entities grounded in a visual context using a Knowledge Base. It is the first KVQAE dataset to cover a wide range of entity types (e.g. persons, landmarks, and products). We argue that KVQAE is a clear, well-defined task that can be evaluated easily, making it suitable to track the progress of multimodal entity representation’s quality. Multimodal entity representation is a central issue that will allow to make human-machine interactions more natural. For example, while watching a movie, one might wonder ‘‘Where did I already see this actress?’’ or ‘‘Did she ever win an Oscar?’’

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 13 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

License archive 2025-07-28

CC BY 4.0

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • ViQuAE

1 variant name, as the archive lists them.

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