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.
Aligning Visual and Lexical Semantics / Giunchiglia, Fausto; Bagchi, Mayukh; Diao, Xiaolei. - 13971:(2023), pp. 294-302. (Intervento presentato al convegno iConference 2023 tenutosi a Barcelona and Virtual nel March 13 - 17, 2023) [10.1007/978-3-031-28035-1_20].
Aligning Visual and Lexical Semantics
Giunchiglia, Fausto;Bagchi, Mayukh
;Diao, Xiaolei
2023-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
