TasksSotADatasetsPapersMethodsSubmitAbout
Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable BenchmarksAll SotADatasetsPapersMethods

Community

Submit ResultsAbout

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/RCC

RCC

Reported on 4 benchmarks across 1 task · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision8 results

  • Object CountingonFSC147
    MAE(test)· 2022-05-20
    17.12
    best: 5.74 (CountGD)
    Learning to Count Anything: Reference-less Class-agnostic Counting with Weak SupervisionarXiv:2205.10203
  • Object CountingonFSC147
    MAE(val)· 2022-05-20
    17.49
    best: 7.1 (CountGD)
    Learning to Count Anything: Reference-less Class-agnostic Counting with Weak SupervisionarXiv:2205.10203
  • Object CountingonFSC147
    RMSE(test)· 2022-05-20
    104.53
    best: 24.09 (CountGD)
    Learning to Count Anything: Reference-less Class-agnostic Counting with Weak SupervisionarXiv:2205.10203
  • Object CountingonFSC147
    RMSE(val)· 2022-05-20
    58.81
    best: 26.08 (CountGD)
    Learning to Count Anything: Reference-less Class-agnostic Counting with Weak SupervisionarXiv:2205.10203
  • Object CountingonFSC147
    MAE(test)· 2022-05-20
    17.12
    best: 5.74 (CountGD)
    Learning to Count Anything: Reference-less Class-agnostic Counting with Weak SupervisionarXiv:2205.10203
  • Object CountingonFSC147
    MAE(val)· 2022-05-20
    17.49
    best: 7.1 (CountGD)
    Learning to Count Anything: Reference-less Class-agnostic Counting with Weak SupervisionarXiv:2205.10203
  • Object CountingonFSC147
    RMSE(test)· 2022-05-20
    104.53
    best: 24.09 (CountGD)
    Learning to Count Anything: Reference-less Class-agnostic Counting with Weak SupervisionarXiv:2205.10203
  • Object CountingonFSC147
    RMSE(val)· 2022-05-20
    58.81
    best: 26.08 (CountGD)
    Learning to Count Anything: Reference-less Class-agnostic Counting with Weak SupervisionarXiv:2205.10203