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Models/CBN+ECN

CBN+ECN

Reported on 16 benchmarks across 2 tasks · 1 paper

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

Methodology8 results

  • Domain AdaptationonMarket to Duke
    mAP· 2020-01-23
    44.9
    best: 74.8 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Domain AdaptationonMarket to Duke
    rank-1· 2020-01-23
    68
    best: 85 (CCTSE)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Domain AdaptationonMarket to Duke
    rank-10· 2020-01-23
    83.9
    best: 94.4 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Domain AdaptationonMarket to Duke
    rank-5· 2020-01-23
    80
    best: 92.4 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Domain AdaptationonDuke to Market
    mAP· 2020-01-23
    52
    best: 84.4 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Domain AdaptationonDuke to Market
    rank-1· 2020-01-23
    81.7
    best: 93.6 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Domain AdaptationonDuke to Market
    rank-10· 2020-01-23
    94.7
    best: 98.7 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Domain AdaptationonDuke to Market
    rank-5· 2020-01-23
    91.9
    best: 97.7 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680

Other8 results

  • Unsupervised Domain AdaptationonMarket to Duke
    mAP· 2020-01-23
    44.9
    best: 74.8 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Unsupervised Domain AdaptationonMarket to Duke
    rank-1· 2020-01-23
    68
    best: 85 (CCTSE)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Unsupervised Domain AdaptationonMarket to Duke
    rank-10· 2020-01-23
    83.9
    best: 94.4 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Unsupervised Domain AdaptationonMarket to Duke
    rank-5· 2020-01-23
    80
    best: 92.4 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Unsupervised Domain AdaptationonDuke to Market
    mAP· 2020-01-23
    52
    best: 84.4 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Unsupervised Domain AdaptationonDuke to Market
    rank-1· 2020-01-23
    81.7
    best: 93.6 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Unsupervised Domain AdaptationonDuke to Market
    rank-10· 2020-01-23
    94.7
    best: 98.7 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680
  • Unsupervised Domain AdaptationonDuke to Market
    rank-5· 2020-01-23
    91.9
    best: 97.7 (CORE-ReID)
    Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch NormalizationarXiv:2001.08680