mlsanityData to 7 Oct 2026

Aligning Visual and Lexical Semantics

arXiv 2212.06629 ↗First posted 13 Dec 2022cs.CV cs.AIcited by 7

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Abstract (arXiv)

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.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 6 of its 19 references that are in the map. First posted on arXiv 13 Dec 2022.

Builds on

6 of 19 references.

References · 6

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  2. 2020From ImageNet to Image Classification: Contextualizing Progress on Benchmarkscited by 90
  3. 2019Continual egocentric object recognitioncited by 12
  4. 2021Towards Visual Semanticscited by 12
  5. 2021Object Recognition as Classification via Visual Propertiescited by 5
  6. 2022Visual Ground Truth Construction as Faceted Classificationcited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 1; 2025: 0; 2026: 2.

7 papers.