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Models/HPGN

HPGN

Reported on 8 benchmarks across 2 tasks · 1 paper · 4 SOTA

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

Computer Vision8 results

  • Intelligent SurveillanceonVehicleID Small
    Rank1· 2020-05-29
    83.91
    best: 87.9 (ANet)
    SOTA
    Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identificationarXiv:2005.14684
  • Intelligent SurveillanceonVehicleID Small
    mAP· 2020-05-29
    89.6
    best: 92.5 (MBR-4B (without RK))
    SOTA
    Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identificationarXiv:2005.14684
  • Vehicle Re-IdentificationonVehicleID Small
    Rank1· 2020-05-29
    83.91
    best: 87.9 (ANet)
    SOTA
    Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identificationarXiv:2005.14684
  • Vehicle Re-IdentificationonVehicleID Small
    mAP· 2020-05-29
    89.6
    best: 92.5 (MBR-4B (without RK))
    SOTA
    Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identificationarXiv:2005.14684
  • Intelligent SurveillanceonVeRi-776
    Rank1· 2020-05-29
    96.72
    best: 97.3 (RPTM)
    Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identificationarXiv:2005.14684
  • Intelligent SurveillanceonVeRi-776
    mAP· 2020-05-29
    80.18
    best: 92.1 (MBR4B-LAI (w/ RK))
    Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identificationarXiv:2005.14684
  • Vehicle Re-IdentificationonVeRi-776
    Rank1· 2020-05-29
    96.72
    best: 97.3 (RPTM)
    Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identificationarXiv:2005.14684
  • Vehicle Re-IdentificationonVeRi-776
    mAP· 2020-05-29
    80.18
    best: 92.1 (MBR4B-LAI (w/ RK))
    Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identificationarXiv:2005.14684