A Corpus of Natural Language for Visual Reasoning
We present a new visual reasoning language dataset, containing 92,244 pairs of examples of natural statements grounded in synthetic images with 3,962 unique sentences. We describe a method of crowdsourcing linguistically-diverse data, and present an analysis of our data. The data demonstrates a broad set of linguistic phenomena, requiring visual and set-theoretic reasoning. We experiment with various models, and show the data presents a strong challenge for future research.
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Question AnsweringVisual Question Answering (VQA)Visual ReasoningSimilar Papers 제목 키워드 기반
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