3D Scene Understanding

3D Scene Understanding is a computational framework within computer vision that integrates geometric, semantic, and spatial reasoning to interpret the three-dimensional structure and content of real-world environments from sensor data, distinguishing itself from 2D approaches by explicitly modeling volumetric layout, object pose, and scene topology in three-dimensional space.

2.2K

Publications

238.9K

Citations

5.8K

Authors

1.1K

Institutions

Publications per year

2017–2026

1.2K

Variants

Three-dimensional Scene Understanding

Authors

5.8K

  1. MH
    Martial Hebert

    Carnegie Mellon University, United States

    26 publications · 6.4K citations

    23

    h-index

  2. MS
    Manolis Savva

    Stanford University, United States

    25 publications · 9.8K citations

    22

    h-index

  3. SS
    Silvio Savarese

    Stanford University, United States

    24 publications · 4.3K citations

    21

    h-index

  4. RU
    Raquel Urtasun

    University of Toronto, Canada

    20 publications · 13.4K citations

    20

    h-index

  5. LG
    Leonidas Guibas

    Stanford University, United States

    23 publications · 14.5K citations

    20

    h-index

1–5 of 5.8K

Venues

  1. arXiv (Cornell University)

    Repository · 236 publications · 14.2K citations

    51

    h-index

  2. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 76 publications · 13.1K citations

    41

    h-index

  3. ACM Transactions on Graphics

    TOG · 36 publications · 6.9K citations

    31

    h-index

  4. 28

    h-index

  5. International Journal of Computer Vision

    33 publications · 7K citations

    27

    h-index

1–5