VQG is a collection of datasets for visual question generation. VQG questions were collected by crowdsourcing the task on Amazon Mechanical Turk (AMT). The authors provided details on the prompt and the specific instructions for all the crowdsourcing tasks in this paper in the supplementary material. The prompt was successful at capturing nonliteral questions. Images were taken from the MSCOCO dataset.
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The large-scale MUSIC-AVQA dataset of musical performance contains 45,867 question-answer pairs, distributed in 9,288 videos for over 150 hours. All QA pairs types are divided into 3 modal scenarios, which contain 9 question types and 33 question templates. Finally, as an open-ended problem of our AVQA tasks, all 42 kinds of answers constitute a set for selection.
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