Real-time Semantic Segmentation

Real-Time Semantic Segmentation is a semantic segmentation methodology distinguished by its capability to process and output pixel-level class predictions at a rate sufficient to support interactive or dynamic application demands, typically operating in lockstep with the acquisition frame rate of visual input.

265

Publications

23.1K

Citations

1K

Authors

339

Institutions

Publications per year

2017–2026

250

Authors

1K

  1. CS
    Chunhua Shen

    The University of Adelaide, Australia

    8 publications · 676 citations

    8

    h-index

  2. JL
    Jiehao Li

    Beijing Institute of Technology, China

    6 publications · 167 citations

    6

    h-index

  3. CC
    Camille Couprie

    Laboratoire d'Informatique Gaspard-Monge, France

    6 publications · 747 citations

    6

    h-index

  4. LM
    Luis M. Bergasa

    Universidad de Alcalá, Spain

    5 publications · 1.7K citations

    5

    h-index

  5. KY
    Kailun Yang

    Zhejiang University, China

    5 publications · 268 citations

    5

    h-index

1–5 of 1K

Venues

  1. arXiv (Cornell University)

    Repository · 41 publications · 5.2K citations

    27

    h-index

  2. 12

    h-index

  3. Neurocomputing

    12 publications · 1.5K citations

    11

    h-index

  4. IEEE Access

    10 publications · 655 citations

    10

    h-index

  5. IEEE Robotics and Automation Letters

    6 publications · 599 citations

    6

    h-index

1–5