Benchmark Datasets

Benchmark Datasets is a reference collection of data instances and associated annotations or ground truth that serves as a standardized basis for systematically evaluating, comparing, and advancing the performance of information retrieval systems across consistent experimental conditions.

19.6K

Publications

1.6M

Citations

52.9K

Authors

6.4K

Institutions

Publications per year

2017–2026

15K

Variants

Benchmark Data

Authors

52.9K

  1. DT
    Dacheng Tao

    The University of Sydney, Australia

    67 publications · 5.1K citations

    36

    h-index

  2. MY
    Ming–Hsuan Yang

    University of California, Merced, United States

    51 publications · 18.3K citations

    36

    h-index

  3. CS
    Chunhua Shen

    The University of Adelaide, Australia

    41 publications · 5.3K citations

    30

    h-index

  4. FN
    Feiping Nie

    Northwestern Polytechnical University, China

    49 publications · 4.9K citations

    30

    h-index

  5. HL
    Huchuan Lu

    Dalian University of Technology, China

    31 publications · 6K citations

    28

    h-index

1–5 of 52.9K

Venues

  1. arXiv (Cornell University)

    Repository · 2.2K publications · 171.4K citations

    172

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 524 publications · 54.8K citations

    104

    h-index

  3. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 224 publications · 54.1K citations

    87

    h-index

  4. IEEE Access

    517 publications · 27.9K citations

    78

    h-index

  5. IEEE Transactions on Image Processing

    228 publications · 22.1K citations

    76

    h-index

1–5