Beyond Literal Visual Modeling: Understanding Image Metaphor Based On Literal-Implied Concept Mapping

MULTIMEDIA MODELING (MMM 2020), PT I(2020)

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摘要
Existing ultimedia content understanding tasks focus on modeling the literal semantics of multimedia documents. This study explores the possibility of understanding the implied meaning behind the literal semantics. Inspired by human's implied imagination process, we introduce a three-step solution framework based on the mapping from literal to implied concepts by integrating external knowledge. Experiments on self-collected metaphor image dataset validate the effectiveness in identifying accurate implied concepts for further metaphor understanding in controlled environment.
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关键词
Image metaphor understanding, Concept mapping, External knowledge
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