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arXiv 2212.06629cs.CVcs.AI

Aligning Visual and Lexical Semantics

University of Trento(特伦托大学)

Fausto Giunchiglia, Mayukh Bagchi, Xiaolei Diao

英文摘要:

We discuss two kinds of semantics relevant to Computer Vision (CV) systems - Visual Semantics and Lexical Semantics. While visual semantics focus on how humans build concepts when using vision to perceive a target reality, lexical semantics focus on how humans build concepts of the same target reality through the use of language. The lack of coincidence between visual and lexical semantics, in turn, has a major impact on CV systems in the form of the Semantic Gap Problem (SGP). The paper, while extensively exemplifying the lack of coincidence as above, introduces a general, domain-agnostic methodology to enforce alignment between visual and lexical semantics.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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