Large-scale Image Retrieval

Large-Scale Image Retrieval is an image retrieval paradigm distinguished by its operational requirement to efficiently and accurately retrieve relevant images from a database containing millions or billions of images, necessitating scalable indexing, compact representation, and efficient search methodologies to manage computational and storage constraints.

873

Publications

153.7K

Citations

2.3K

Authors

657

Institutions

Publications per year

2017–2026

297

Authors

2.3K

  1. ZZ
    Zheng Zhang

    Harbin Institute of Technology, China

    14 publications · 654 citations

    14

    h-index

  2. WZ
    Wengang Zhou

    University of Science and Technology of China, China

    19 publications · 953 citations

    14

    h-index

  3. WL
    Wei Liu

    Tencent (China), China

    15 publications · 2.5K citations

    14

    h-index

  4. HL
    Houqiang Li

    University of Science and Technology of China, China

    19 publications · 975 citations

    14

    h-index

  5. FS
    Fumin Shen

    University of Electronic Science and Technology of China, China

    14 publications · 2.1K citations

    13

    h-index

1–5 of 2.3K

Venues

  1. IEEE Transactions on Image Processing

    34 publications · 2.7K citations

    27

    h-index

  2. IEEE Transactions on Multimedia

    34 publications · 1.9K citations

    23

    h-index

  3. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 26 publications · 11.9K citations

    21

    h-index

  4. arXiv (Cornell University)

    Repository · 32 publications · 1.3K citations

    20

    h-index

  5. Neurocomputing

    19 publications · 635 citations

    16

    h-index

1–5