Aligning Visual and Lexical Semantics
This addresses a foundational issue in computer vision systems, but the approach appears incremental as it builds on existing concepts without specifying novel breakthroughs.
The paper tackles the semantic gap problem in computer vision by addressing the misalignment between visual and lexical semantics, and introduces a domain-agnostic methodology to enforce alignment between them.
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.