Multi-modal Perception

Multi-Modal Perception is a computational framework in LiDAR perception that integrates data from multiple sensory modalities, such as LiDAR, camera, and radar, to enhance environmental understanding by leveraging complementary spatial, spectral, and temporal information unattainable through a single modality alone.

280

Publications

24K

Citations

1.1K

Authors

368

Institutions

Publications per year

2017–2026

209

Authors

1.1K

  1. XZ
    Xinyu Zhang

    Tsinghua University, China

    5 publications · 354 citations

    5

    h-index

  2. JM
    Jiaqi Ma

    University of California, Los Angeles, United States

    4 publications · 741 citations

    4

    h-index

  3. KD
    Klaus Dietmayer

    Universität Ulm, Germany

    4 publications · 1.4K citations

    4

    h-index

  4. JY
    Jian Yang

    Nanjing University of Science and Technology, China

    4 publications · 208 citations

    4

    h-index

  5. BC
    Benjamin Caine

    Google (United States), United States

    3 publications · 3.3K citations

    3

    h-index

1–5 of 1.1K

Venues

  1. arXiv (Cornell University)

    Repository · 26 publications · 1K citations

    17

    h-index

  2. 11

    h-index

  3. IEEE Robotics and Automation Letters

    10 publications · 693 citations

    10

    h-index

  4. IEEE Access

    8 publications · 293 citations

    8

    h-index

  5. Sensors

    8 publications · 385 citations

    7

    h-index

1–5