Papers with visual-textual correspondences

1 papers
Quantifying the Visual Concreteness of Words and Topics in Multimodal Datasets (N18-1)

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Challenge: Existing work suggests that concepts with concrete visual manifestations are easier to learn than abstract ones.
Approach: They propose an algorithm for automatically computing the visual concreteness of words and topics within multimodal datasets.
Outcome: The proposed algorithm predicts the capacity of machine learning algorithms to learn textual/visual relationships.

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