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A Corpus for Reasoning About Natural Language Grounded in Photographs

2018-11-01
Alane Suhr, Stephanie Zhou, Iris Zhang, Huajun Bai, Yoav Artzi

Abstract

We introduce a new dataset for joint reasoning about language and vision. The data contains 107,296 examples of English sentences paired with web photographs. The task is to determine whether a natural language caption is true about a photograph. We present an approach for finding visually complex images and crowdsourcing linguistically diverse captions. Qualitative analysis shows the data requires complex reasoning about quantities, comparisons, and relationships between objects. Evaluation of state-of-the-art visual reasoning methods shows the data is a challenge for current methods.

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URL

https://arxiv.org/abs/1811.00491

PDF

https://arxiv.org/pdf/1811.00491


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