{"url":"/dataset/fsvqa","name":"FSVQA","full_name":"Full-Sentence Visual Question Answering","description_markdown":"Full-Sentence Visual Question Answering (FSVQA) dataset, consisting of nearly 1 million pairs of questions and full-sentence answers for images, built by applying a number of rule-based natural language processing techniques to original VQA dataset and captions in the MS COCO dataset.\r\n\r\nSource: [The Color of the Cat is Gray: 1 Million Full-Sentences Visual Question Answering (FSVQA)](https://arxiv.org/abs/1609.06657)","description_withheld":null,"homepage":"https://www.mi.t.u-tokyo.ac.jp/static/projects/fsvqa/","introduced_date":"2016-09-21","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-color-of-the-cat-is-gray-1-million-full","title":"The Color of the Cat is Gray: 1 Million Full-Sentences Visual Question Answering (FSVQA)","first_author":"Andrew Shin","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["FSVQA"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}