Concepedia

Scene Understanding Optimization

Scene Understanding Optimization is a methodological framework within performance optimization for augmented reality that enhances the efficiency and accuracy of environmental interpretation by selectively refining spatial perception, object recognition, and semantic segmentation processes to meet real-time and resource-constrained deployment requirements.

23

Publications

1.5K

Citations

123

Authors

46

Institutions

Publications per year

2017–2026

16

Parents

Publications

23

Augmented Reality Meets Computer Vision: Efficient Data Generation for Urban Driving Scenes

Hassan Abu Alhaija, Siva Karthik Mustikovela, Lars Mescheder et al. · International Journal of Computer Vision · 2018 · 428 citations

, , +14

IM2CAD

Hamid Izadinia, Qi Shan, Steven M. Seitz · 2017 · 144 citations

, , +16

Collaborative Sensing in a Distributed PTZ Camera Network

Chong Ding, Song Bi, Akshay A. Morye et al. · IEEE Transactions on Image Processing · 2012 · 127 citations

, , +17

Beyond Point Clouds: Scene Understanding by Reasoning Geometry and Physics

Bo Zheng, Yibiao Zhao, Joey C. Yu et al. · 2013 · 118 citations

, , +17

Accelerating real-time embedded scene labeling with convolutional networks

Lukas Cavigelli, Michele Magno, Luca Benini · 2015 · 112 citations · Full text

, , +15

1–5 of 23

Authors

123

  1. PZ
    Pengcheng Zhang

    Hohai University, China

    1 publications · 30 citations

    1

    h-index

  2. BF
    Björn Franke

    University of Edinburgh, United Kingdom

    1 publications · 45 citations

    1

    h-index

  3. KO
    Kaoru Ota

    Muroran Institute of Technology, Japan

    1 publications · 20 citations

    1

    h-index

  4. CZ
    Cheng Zou

    Xijing Hospital, China

    1 publications · 39 citations

    1

    h-index

  5. AA
    Akshay A. Morye

    University of California, Riverside, United States

    1 publications · 127 citations

    1

    h-index

1–5 of 123

Institutions

46

  1. ETH Zurich

    Zurich, Switzerland

    2 h-index

    4 publications

    764 citations

  2. Nanjing University

    Nanjing, China

    1 h-index

    1 publications

    12 citations

  3. Imperial College London

    London, United Kingdom

    1 h-index

    3 publications

    135 citations

  4. University of Michigan

    Ann Arbor, United States

    1 h-index

    4 publications

    184 citations

  5. Sony Corporation (United States)

    New York, United States

    1 h-index

    1 publications

    127 citations

  6. University of Bologna

    Bologna, Italy

    1 h-index

    2 publications

    224 citations

  7. Lawrence Livermore National Laboratory

    Livermore, United States

    1 h-index

    1 publications

    45 citations

  8. University of Washington

    Seattle, United States

    1 h-index

    2 publications

    288 citations

1–8 of 46

Venues

  1. Automation in Construction

    2 publications · 82 citations

    2

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 46 citations

    2

    h-index

  3. PLoS ONE

    1 publications · 62 citations

    1

    h-index

  4. Virtual Reality

    1 publications · 17 citations

    1

    h-index

  5. Sensors

    1 publications · 20 citations

    1

    h-index

1–5