Image-based Augmentation

Image-Based Augmentation is an augmentation technique that modifies or enhances visual content by integrating computer-generated elements directly into real-world images, distinguishing itself from other augmentation methods through its reliance on static or dynamic image data as the primary input for rendering and alignment.

102

Publications

6K

Citations

410

Authors

180

Institutions

Publications per year

2017–2026

97

Authors

410

  1. SW
    Seunghyeon Wang

    Hanyang University, South Korea

    2 publications · 64 citations

    3

    h-index

  2. YL
    Yuanzhong Li

    Fujifilm (Japan), Japan

    2 publications · 167 citations

    2

    h-index

  3. AB
    Augustin Braun

    Stanford University, United States

    2 publications · 53 citations

    2

    h-index

  4. IO
    Ivan Oseledets

    Skolkovo Institute of Science and Technology, Russia

    2 publications · 45 citations

    2

    h-index

  5. HW
    Hayley Weir

    Stanford University, United States

    2 publications · 53 citations

    2

    h-index

1–5 of 410

Venues

  1. IEEE Access

    6 publications · 286 citations

    6

    h-index

  2. Applied Sciences

    4 publications · 179 citations

    5

    h-index

  3. Electronics

    4 publications · 92 citations

    4

    h-index

  4. Sensors

    3 publications · 75 citations

    3

    h-index

  5. Computers & Geosciences

    CAGEO · 2 publications · 129 citations

    2

    h-index

1–5