Fine-grained Image Classification

Fine-Grained Image Classification is a specialized form of image classification that distinguishes subcategories within a narrow domain by identifying subtle, discriminative visual differences among visually similar object categories, as opposed to broad-level classification that separates vastly distinct classes.

644

Publications

58K

Citations

2.3K

Authors

569

Institutions

Publications per year

2017–2026

529

Authors

2.3K

  1. SB
    Serge Belongie

    University of California San Diego, United States

    12 publications · 1.6K citations

    12

    h-index

  2. ZM
    Zhanyu Ma

    Beijing University of Posts and Telecommunications, China

    9 publications · 1.1K citations

    9

    h-index

  3. YL
    Yuanqing Lin

    University of Pennsylvania, United States

    8 publications · 973 citations

    8

    h-index

  4. XW
    Xiu-Shen Wei

    Nanjing University of Science and Technology, China

    8 publications · 1.3K citations

    8

    h-index

  5. YP
    Yuxin Peng

    Peking University, China

    8 publications · 1.6K citations

    8

    h-index

1–5 of 2.3K

Venues

  1. arXiv (Cornell University)

    Repository · 67 publications · 11.4K citations

    30

    h-index

  2. IEEE Transactions on Image Processing

    25 publications · 2.8K citations

    23

    h-index

  3. Pattern Recognition

    23 publications · 1.6K citations

    18

    h-index

  4. IEEE Access

    24 publications · 1.4K citations

    17

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 18 publications · 2K citations

    15

    h-index

1–5