Multi-scale Context Modeling

Multi-Scale Context Modeling is a computational strategy in semantic segmentation that integrates contextual information across multiple spatial scales within an image, distinguishing itself by enabling the simultaneous capture of fine-grained local details and broader semantic dependencies to improve pixel-level classification accuracy.

63

Publications

4.3K

Citations

284

Authors

117

Institutions

Publications per year

2017–2026

54

Authors

284

  1. HW
    Haonan Wang

    University of Alberta, Canada

    2 publications · 1.1K citations

    2

    h-index

  2. CK
    C. Krishna Mohan

    Indian Institute of Technology Hyderabad, India

    2 publications · 109 citations

    2

    h-index

  3. CH
    Christian Heipke

    Leibniz University Hannover, Germany

    2 publications · 119 citations

    2

    h-index

  4. CZ
    Ce Zhu

    University of Electronic Science and Technology of China, China

    2 publications · 104 citations

    2

    h-index

  5. FR
    Franz Rottensteiner

    Leibniz University Hannover, Germany

    2 publications · 119 citations

    2

    h-index

1–5 of 284

Venues

  1. arXiv (Cornell University)

    Repository · 8 publications · 470 citations

    8

    h-index

  2. 3

    h-index

  3. IEEE Access

    2 publications · 50 citations

    2

    h-index

  4. IEEE Transactions on Image Processing

    2 publications · 112 citations

    2

    h-index

  5. 2

    h-index

1–5