Visual Concept Embedding

Visual Concept Embedding is a computational representation that encodes the meaning of visual concepts in a continuous vector space, distinguished by its integration of semantic knowledge with perceptual features to enable reasoning about visual content.

52

Publications

3.4K

Citations

197

Authors

85

Institutions

Publications per year

2017–2026

38

Authors

197

  1. JM
    Jiayuan Mao

    Tsinghua University, China

    3 publications · 92 citations

    3

    h-index

  2. JF
    Jianping Fan

    University of North Carolina at Charlotte, United States

    3 publications · 110 citations

    3

    h-index

  3. WY
    Wan Y. Kwok

    National Institute of Mental Health, United States

    2 publications · 339 citations

    2

    h-index

  4. RC
    Riquan Chen

    Sun Yat-sen University, China

    2 publications · 101 citations

    2

    h-index

  5. LS
    Larry S. Davis

    University of Maryland, College Park, United States

    2 publications · 240 citations

    2

    h-index

1–5 of 197

Venues

  1. arXiv (Cornell University)

    Repository · 7 publications · 588 citations

    7

    h-index

  2. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 2 publications · 51 citations

    2

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 99 citations

    2

    h-index

  4. ArXiv.org

    Repository · 2 publications · 32 citations

    2

    h-index

  5. 1

    h-index

1–5