Unsupervised Semantic Segmentation

Unsupervised Semantic Segmentation is a method in computer vision that performs pixel-level label assignment to image regions without requiring manually annotated training data, distinguishing itself from supervised approaches by leveraging intrinsic data structures or self-generated pseudo-labels to discover semantic categories.

314

Publications

21.6K

Citations

1.2K

Authors

412

Institutions

Publications per year

2017–2026

286

Authors

1.2K

  1. LV
    Luc Van Gool

    ETH Zurich, Switzerland

    9 publications · 459 citations

    9

    h-index

  2. TF
    Tim Fingscheidt

    Technische Universität Braunschweig, Germany

    6 publications · 175 citations

    6

    h-index

  3. YY
    Yi Yang

    University of Technology Sydney, Australia

    6 publications · 1.3K citations

    6

    h-index

  4. YL
    Yawei Luo

    Huazhong University of Science and Technology, China

    5 publications · 1.2K citations

    5

    h-index

  5. JY
    Junqing Yu

    Huazhong University of Science and Technology, China

    5 publications · 1.2K citations

    5

    h-index

1–5 of 1.2K

Venues

  1. arXiv (Cornell University)

    Repository · 35 publications · 1.7K citations

    18

    h-index

  2. 18

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 10 publications · 351 citations

    9

    h-index

  4. 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

    Conference · 8 publications · 762 citations

    8

    h-index

  5. 8

    h-index

1–5