Anchor-based Detection

Anchor-Based Detection is a detection methodology in object detection that generates region proposals by evaluating predefined anchor boxes at various locations, scales, and aspect ratios across the image, distinguishing itself from anchor-free approaches by relying on these parameterized reference boxes to predict object boundaries.

384

Publications

30.7K

Citations

1.6K

Authors

398

Institutions

Publications per year

2017–2026

366

Authors

1.6K

  1. LJ
    Licheng Jiao

    Xidian University, China

    8 publications · 330 citations

    8

    h-index

  2. SZ
    Stan Z. Li

    Chinese Academy of Sciences, China

    8 publications · 3.4K citations

    8

    h-index

  3. ZL
    Zhen Lei

    Chinese Academy of Sciences, China

    7 publications · 3.4K citations

    7

    h-index

  4. XY
    Xue Yang

    Shanghai Jiao Tong University, China

    6 publications · 1.3K citations

    6

    h-index

  5. KF
    Kun Fu

    Chinese Academy of Sciences, China

    6 publications · 2K citations

    6

    h-index

1–5 of 1.6K

Venues

  1. arXiv (Cornell University)

    Repository · 56 publications · 3.7K citations

    27

    h-index

  2. 26

    h-index

  3. Remote Sensing

    31 publications · 1.8K citations

    21

    h-index

  4. IEEE Access

    17 publications · 693 citations

    13

    h-index

  5. IEEE Geoscience and Remote Sensing Letters

    GRSL · 13 publications · 288 citations

    12

    h-index

1–5