Cross-view Image Retrieval

Cross-View Image Retrieval is a type of image retrieval task that involves matching images across different views or modalities, such as aerial to ground-level, satellite to map, or 3D to 2D representations, where the distinguishing characteristic is the significant geometric and appearance discrepancy between the source and target views.

20

Publications

2.8K

Citations

70

Authors

36

Institutions

Publications per year

2017–2026

15

Authors

70

  1. AL
    An-An Liu

    Tianjin University, China

    3 publications · 81 citations

    3

    h-index

  2. WL
    Wenhui Li

    Tianjin University, China

    2 publications · 55 citations

    2

    h-index

  3. YS
    Yuming Shen

    University of Oxford, United Kingdom

    2 publications · 305 citations

    2

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  4. XL
    Xianglong Liu

    Beihang University, China

    2 publications · 305 citations

    2

    h-index

  5. YS
    Yuting Su

    Tianjin University, China

    2 publications · 46 citations

    2

    h-index

1–5 of 70

Venues

  1. Remote Sensing

    2 publications · 163 citations

    2

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  2. IEEE Transactions on Multimedia

    2 publications · 82 citations

    2

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  3. arXiv (Cornell University)

    Repository · 2 publications · 42 citations

    2

    h-index

  4. 1

    h-index

  5. IEEE Signal Processing Letters

    1 publications · 23 citations

    1

    h-index

1–5