Multimodal Metric Learning

Multimodal Metric Learning is a metric learning framework that learns a unified distance function across multiple modalities by preserving semantic similarity relationships while accounting for cross-modal variations in feature representation.

75

Publications

4.6K

Citations

287

Authors

133

Institutions

Publications per year

2017–2026

57

Authors

287

  1. YS
    Yinghuan Shi

    Nanjing University, China

    4 publications · 125 citations

    4

    h-index

  2. HY
    Hujun Yin

    University of Manchester, United Kingdom

    4 publications · 125 citations

    4

    h-index

  3. JH
    Jing Huo

    Nanjing University, China

    4 publications · 125 citations

    4

    h-index

  4. YG
    Yang Gao

    Nanjing University, China

    4 publications · 125 citations

    4

    h-index

  5. QH
    Qinghua Hu

    Tianjin University, China

    3 publications · 97 citations

    3

    h-index

1–5 of 287

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 121 citations

    5

    h-index

  2. IEEE Transactions on Multimedia

    4 publications · 148 citations

    4

    h-index

  3. Pattern Recognition

    4 publications · 129 citations

    4

    h-index

  4. IEEE Transactions on Image Processing

    3 publications · 196 citations

    3

    h-index

  5. Information Fusion

    2 publications · 146 citations

    2

    h-index

1–5