Semantic Boundary Detection

Semantic Boundary Detection is a computational method in image segmentation that identifies precise pixel-level contours delineating regions belonging to distinct semantic object classes, distinguished from general edge detection by its focus on meaningfully labeled categories rather than low-level intensity changes.

344

Publications

30.6K

Citations

1.3K

Authors

430

Institutions

Publications per year

2017–2026

263

Authors

1.3K

  1. LC
    Liang-Chieh Chen

    Google (United States), United States

    4 publications · 5.1K citations

    4

    h-index

  2. WD
    Wenhui Diao

    Chinese Academy of Sciences, China

    4 publications · 119 citations

    4

    h-index

  3. CP
    Chao Peng

    Megvii (China)

    4 publications · 2.7K citations

    4

    h-index

  4. AY
    Alan Yuille

    Johns Hopkins University, United States

    4 publications · 518 citations

    4

    h-index

  5. SL
    Shijian Lu

    Nanyang Technological University, Singapore

    4 publications · 307 citations

    4

    h-index

1–5 of 1.3K

Venues

  1. arXiv (Cornell University)

    Repository · 27 publications · 6.2K citations

    18

    h-index

  2. 15

    h-index

  3. Pattern Recognition

    14 publications · 517 citations

    13

    h-index

  4. IEEE Transactions on Image Processing

    10 publications · 1.4K citations

    10

    h-index

  5. Remote Sensing

    9 publications · 377 citations

    9

    h-index

1–5