Event-based Vision

Event-Based Vision is a computational sensing paradigm in robot sensors that, unlike traditional frame-based vision, captures visual information asynchronously through a stream of sparse, time-stamped pixel-level brightness changes, enabling high temporal resolution, low latency, and reduced data redundancy.

417

Publications

27.6K

Citations

1.1K

Authors

348

Institutions

Publications per year

2017–2026

306

Variants

Event Vision

Authors

1.1K

  1. DS
    Davide Scaramuzza

    University of Zurich, Switzerland

    40 publications · 4.7K citations

    32

    h-index

  2. TD
    Tobi Delbrück

    ETH Zurich, Switzerland

    38 publications · 3.5K citations

    31

    h-index

  3. RB
    Ryad Benosman

    Institut de la Vision, France

    31 publications · 2.5K citations

    23

    h-index

  4. GG
    Guillermo Gallego

    University of Zurich, Switzerland

    18 publications · 1.8K citations

    18

    h-index

  5. SI
    Sio-Hoï Ieng

    Institut de la Vision, France

    21 publications · 1.5K citations

    16

    h-index

1–5 of 1.1K

Venues

  1. Frontiers in Neuroscience

    23 publications · 1.7K citations

    18

    h-index

  2. IEEE Robotics and Automation Letters

    19 publications · 1.4K citations

    17

    h-index

  3. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 16 publications · 1.8K citations

    16

    h-index

  4. arXiv (Cornell University)

    Repository · 17 publications · 583 citations

    14

    h-index

  5. Sensors

    11 publications · 250 citations

    11

    h-index

1–5