Instance Segmentation Evaluation

Instance Segmentation Evaluation is a technical methodology in computer vision that quantitatively assesses the accuracy of predicted object instances by distinguishing overlapping segmented regions through pixel-level and object-level correspondence with ground truth annotations.

227

Publications

17.4K

Citations

1K

Authors

373

Institutions

Publications per year

2017–2026

218

Authors

1K

  1. XW
    Xinggang Wang

    Huazhong University of Science and Technology, China

    6 publications · 1.4K citations

    6

    h-index

  2. SL
    Shu Liu

    Chinese University of Hong Kong, Hong Kong SAR China

    4 publications · 661 citations

    4

    h-index

  3. RG
    Ross Girshick

    Meta (Israel), Israel

    4 publications · 753 citations

    4

    h-index

  4. PD
    Piotr Dollár

    Meta (Israel), Israel

    4 publications · 753 citations

    4

    h-index

  5. HC
    Hao Chen

    Chinese University of Hong Kong, Hong Kong SAR China

    4 publications · 1.2K citations

    4

    h-index

1–5 of 1K

Venues

  1. arXiv (Cornell University)

    Repository · 33 publications · 1.2K citations

    18

    h-index

  2. 7

    h-index

  3. Computers and Electronics in Agriculture

    7 publications · 476 citations

    7

    h-index

  4. Medical Image Analysis

    6 publications · 758 citations

    6

    h-index

  5. Sensors

    6 publications · 192 citations

    6

    h-index

1–5