Sim2real Transfer

Sim2Real Transfer is a methodological framework in LiDAR perception that enables the adaptation of models trained in simulated environments to perform effectively in real-world sensing conditions by bridging the domain gap between synthetic and physical sensor data.

35

Publications

2.2K

Citations

182

Authors

66

Institutions

Publications per year

2017–2026

35

Authors

182

  1. NH
    Nicolas Heess

    Google (United States), United States

    3 publications · 376 citations

    3

    h-index

  2. DB
    Dhruv Batra

    Georgia Institute of Technology, United States

    3 publications · 63 citations

    3

    h-index

  3. YZ
    Yuke Zhu

    Stanford University, United States

    3 publications · 364 citations

    3

    h-index

  4. AZ
    Andrew Zisserman

    University of Oxford, United Kingdom

    3 publications · 148 citations

    3

    h-index

  5. CD
    Carl Doersch

    Carnegie Mellon University, United States

    3 publications · 148 citations

    3

    h-index

1–5 of 182

Venues

  1. arXiv (Cornell University)

    Repository · 8 publications · 983 citations

    8

    h-index

  2. IFAC-PapersOnLine

    2 publications · 50 citations

    2

    h-index

  3. Robotics and Autonomous Systems

    1 publications · 30 citations

    1

    h-index

  4. 1

    h-index

  5. IEEE Robotics and Automation Letters

    1 publications · 60 citations

    1

    h-index

1–5