Annotation-efficient Segmentation

Annotation-Efficient Segmentation is a semantic segmentation paradigm that reduces the reliance on extensively annotated training data by leveraging techniques such as weak supervision, few-shot learning, or active labeling to achieve high segmentation performance with minimal human-labeled supervision.

54

Publications

2.6K

Citations

311

Authors

151

Institutions

Publications per year

2017–2026

53

Authors

311

  1. LV
    Luc Van Gool

    ETH Zurich, Switzerland

    4 publications · 448 citations

    4

    h-index

  2. DD
    Dengxin Dai

    ETH Zurich, Switzerland

    3 publications · 287 citations

    3

    h-index

  3. OL
    Oliver Lange

    Ludwig-Maximilians-Universität München, Germany

    2 publications · 55 citations

    2

    h-index

  4. RM
    Radek Mackowiak

    Heidelberg University, Germany

    2 publications · 55 citations

    2

    h-index

  5. GW
    Guotai Wang

    University of Electronic Science and Technology of China, China

    2 publications · 111 citations

    2

    h-index

1–5 of 311

Venues

  1. arXiv (Cornell University)

    Repository · 11 publications · 319 citations

    11

    h-index

  2. IEEE Transactions on Medical Imaging

    9 publications · 327 citations

    9

    h-index

  3. Medical Image Analysis

    2 publications · 44 citations

    2

    h-index

  4. IEEE Transactions on Artificial Intelligence

    AI · 1 publications · 16 citations

    1

    h-index

  5. Repository for Publications and Research Data (ETH Zurich)

    Repository · 1 publications · 67 citations

    1

    h-index

1–5