Instance-aware Semantic Segmentation

Instance-Aware Semantic Segmentation is a semantic segmentation framework that, as a unified task, performs both semantic class prediction and instance discrimination by generating instance-sensitive pixel-level labels while preserving semantic consistency across object boundaries.

58

Publications

8.8K

Citations

233

Authors

97

Institutions

Publications per year

2017–2026

52

Authors

233

  1. JD
    Jifeng Dai

    Tsinghua University, China

    5 publications · 2.6K citations

    5

    h-index

  2. XQ
    Xiaojuan Qi

    University of Hong Kong, Hong Kong SAR China

    4 publications · 306 citations

    4

    h-index

  3. LW
    Liwei Wang

    Peking University, China

    3 publications · 237 citations

    3

    h-index

  4. YL
    Yanwei Li

    Chinese University of Hong Kong, Hong Kong SAR China

    3 publications · 237 citations

    3

    h-index

  5. JJ
    Jiaya Jia

    Chinese University of Hong Kong, Hong Kong SAR China

    3 publications · 237 citations

    3

    h-index

1–5 of 233

Venues

  1. arXiv (Cornell University)

    Repository · 12 publications · 618 citations

    11

    h-index

  2. Neurocomputing

    3 publications · 1.8K citations

    3

    h-index

  3. Remote Sensing

    3 publications · 150 citations

    3

    h-index

  4. Computers and Electronics in Agriculture

    3 publications · 143 citations

    2

    h-index

  5. IEEE Robotics and Automation Letters

    2 publications · 243 citations

    2

    h-index

1–5