Saliency-based Segmentation

Saliency-Based Segmentation is a computational method in visual perception research that identifies and delineates image regions of highest perceptual prominence based on bottom-up attentional cues, distinguishing itself from other segmentation techniques by prioritizing stimulus-driven saliency over semantic or boundary-based cues.

272

Publications

19.1K

Citations

962

Authors

380

Institutions

Publications per year

2017–2026

152

Authors

962

  1. ZL
    Zhi Liu

    Shanghai University, China

    6 publications · 568 citations

    6

    h-index

  2. WW
    Wenguan Wang

    Beijing Institute of Technology, China

    5 publications · 1.6K citations

    5

    h-index

  3. KN
    King Ngi Ngan

    Chinese University of Hong Kong, Hong Kong SAR China

    5 publications · 461 citations

    5

    h-index

  4. JS
    Jianbing Shen

    Beijing Institute of Technology, China

    5 publications · 1.3K citations

    5

    h-index

  5. DM
    Dwarikanath Mahapatra

    ETH Zurich, Switzerland

    4 publications · 113 citations

    4

    h-index

1–5 of 962

Venues

  1. IEEE Transactions on Image Processing

    16 publications · 1.1K citations

    14

    h-index

  2. Neurocomputing

    9 publications · 314 citations

    9

    h-index

  3. IEEE Access

    7 publications · 287 citations

    7

    h-index

  4. IEEE Transactions on Multimedia

    7 publications · 680 citations

    7

    h-index

  5. arXiv (Cornell University)

    Repository · 6 publications · 371 citations

    6

    h-index

1–5