Saliency Detection

Saliency Detection is a computational method in computer vision that identifies the most visually prominent regions or objects in a scene by differentiating them from the background based on intrinsic features such as contrast, color, motion, or context, within the framework of scene understanding.

3.4K

Publications

286.8K

Citations

8K

Authors

1.6K

Institutions

Publications per year

2017–2026

1.8K

Authors

8K

  1. HL
    Huchuan Lu

    Dalian University of Technology, China

    91 publications · 16.4K citations

    52

    h-index

  2. JH
    Junwei Han

    Northwestern Polytechnical University, China

    49 publications · 8.2K citations

    35

    h-index

  3. ZL
    Zhi Liu

    Shanghai University, China

    59 publications · 4.1K citations

    33

    h-index

  4. DZ
    Dingwen Zhang

    Northwestern Polytechnical University, China

    34 publications · 5.5K citations

    30

    h-index

  5. AB
    Ali Borji

    University of Central Florida, United States

    42 publications · 7K citations

    29

    h-index

1–5 of 8K

Venues

  1. IEEE Transactions on Image Processing

    207 publications · 25.4K citations

    90

    h-index

  2. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 76 publications · 31.8K citations

    54

    h-index

  3. IEEE Transactions on Multimedia

    101 publications · 6.5K citations

    47

    h-index

  4. 44

    h-index

  5. arXiv (Cornell University)

    Repository · 139 publications · 12.8K citations

    42

    h-index

1–5