Instance Segmentation For Autonomous Driving

Instance Segmentation for Autonomous Driving is a specialized computer vision framework that extends generic instance segmentation by incorporating driving-specific contextual constraints, dynamic object handling, and real-time processing requirements to enable precise pixel-level identification and localization of individual objects in complex urban traffic environments.

135

Publications

10.4K

Citations

524

Authors

177

Institutions

Publications per year

2017–2026

125

Authors

524

  1. RU
    Raquel Urtasun

    University of Toronto, Canada

    7 publications · 1.2K citations

    7

    h-index

  2. SY
    Senthil Yogamani

    Valeo (Ireland), Ireland

    7 publications · 276 citations

    7

    h-index

  3. MR
    Mengye Ren

    University of Toronto, Canada

    5 publications · 461 citations

    5

    h-index

  4. HR
    Hazem Rashed

    Valeo (Ireland), Ireland

    4 publications · 54 citations

    4

    h-index

  5. BD
    Bert De Brabandere

    KU Leuven, Belgium

    4 publications · 385 citations

    4

    h-index

1–5 of 524

Venues

  1. arXiv (Cornell University)

    Repository · 24 publications · 1.6K citations

    15

    h-index

  2. 4

    h-index

  3. IEEE Robotics and Automation Letters

    3 publications · 115 citations

    3

    h-index

  4. Sensors

    3 publications · 105 citations

    3

    h-index

  5. IEEE Access

    2 publications · 41 citations

    2

    h-index

1–5