Amodal Instance Segmentation

Amodal Instance Segmentation is a computer vision task that identifies and delineates individual object instances in an image by predicting their complete pixel-level masks, including both visible and spatially occluded regions, to infer the full extent of objects even where not directly observable.

21

Publications

1.3K

Citations

78

Authors

25

Institutions

Publications per year

2017–2026

20

Authors

78

  1. RM
    Rohit Mohan

    University of Freiburg, Germany

    2 publications · 69 citations

    2

    h-index

  2. AM
    Axiu Mao

    City University of Hong Kong, Hong Kong SAR China

    2 publications · 46 citations

    2

    h-index

  3. TD
    Thomas D. Parsons

    University of Pennsylvania, United States

    2 publications · 46 citations

    2

    h-index

  4. MC
    Maria Camila Ceballos

    University of Calgary, Canada

    2 publications · 46 citations

    2

    h-index

  5. AV
    Abhinav Valada

    University of Freiburg, Germany

    2 publications · 69 citations

    2

    h-index

1–5 of 78

Venues

  1. Computers and Electronics in Agriculture

    5 publications · 158 citations

    5

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  2. 2

    h-index

  3. arXiv (Cornell University)

    Repository · 2 publications · 38 citations

    2

    h-index

  4. 1

    h-index

  5. International Journal of Multimedia Information Retrieval

    IJMIR · 1 publications · 491 citations

    1

    h-index

1–5