Few-shot Semantic Segmentation

Few-Shot Semantic Segmentation is a specialized paradigm within image segmentation that enables the precise categorization of pixels into predefined classes using only a minimal number of annotated support examples per class, thereby addressing the challenge of generalizing segmentation models under extreme data scarcity.

107

Publications

9.2K

Citations

425

Authors

151

Institutions

Publications per year

2017–2026

107

Authors

425

  1. GL
    Guosheng Lin

    Nanyang Technological University, Singapore

    6 publications · 916 citations

    6

    h-index

  2. CS
    Chunhua Shen

    The University of Adelaide, Australia

    5 publications · 1.1K citations

    5

    h-index

  3. JJ
    Jiaya Jia

    Chinese University of Hong Kong, Hong Kong SAR China

    5 publications · 929 citations

    5

    h-index

  4. ZT
    Zhuotao Tian

    Chinese University of Hong Kong, Hong Kong SAR China

    5 publications · 929 citations

    5

    h-index

  5. RY
    Rui Yao

    China University of Mining and Technology, China

    4 publications · 750 citations

    4

    h-index

1–5 of 425

Venues

  1. arXiv (Cornell University)

    Repository · 17 publications · 725 citations

    14

    h-index

  2. IEEE Transactions on Multimedia

    6 publications · 261 citations

    6

    h-index

  3. IEEE Transactions on Image Processing

    5 publications · 228 citations

    5

    h-index

  4. 4

    h-index

  5. 4

    h-index

1–5