Visual Saliency Detection

Visual Saliency Detection is a computational method that identifies the most visually prominent regions or objects in an image by modeling human attention mechanisms to prioritize areas with distinctive low-level features, high-level semantics, or task-driven cues.

1.8K

Publications

171.3K

Citations

4.6K

Authors

1.1K

Institutions

Publications per year

2017–2026

1K

Authors

4.6K

  1. HL
    Huchuan Lu

    Dalian University of Technology, China

    65 publications · 12.3K citations

    40

    h-index

  2. JH
    Junwei Han

    Northwestern Polytechnical University, China

    38 publications · 6.2K citations

    30

    h-index

  3. MC
    Ming‐Ming Cheng

    Nankai University, China

    29 publications · 12.7K citations

    25

    h-index

  4. YF
    Yuming Fang

    Jiangxi University of Finance and Economics, China

    30 publications · 2.2K citations

    23

    h-index

  5. DZ
    Dingwen Zhang

    Northwestern Polytechnical University, China

    24 publications · 3.9K citations

    22

    h-index

1–5 of 4.6K

Venues

  1. IEEE Transactions on Image Processing

    141 publications · 15.9K citations

    69

    h-index

  2. 44

    h-index

  3. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 50 publications · 25.2K citations

    41

    h-index

  4. IEEE Transactions on Multimedia

    60 publications · 3.8K citations

    35

    h-index

  5. Neurocomputing

    82 publications · 2.8K citations

    28

    h-index

1–5