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Models/DualCoOp

DualCoOp

Reported on 6 benchmarks across 3 tasks · 1 paper · 6 SOTA

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

Computer Vision4 results

  • Multi-Label Image ClassificationonMS-COCO-2014
    Average mAP· 2022-06-20
    81.9
    best: 83.6 (DualCoOp+TaI-DPT)
    SOTA
    DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited AnnotationsarXiv:2206.09541
  • Multi-Label Image ClassificationonPASCAL VOC 2007
    Average mAP· 2022-06-20
    93.2
    best: 94.8 (DualCoOp+TaI-DPT)
    SOTA
    DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited AnnotationsarXiv:2206.09541
  • Image ClassificationonMS-COCO-2014
    Average mAP· 2022-06-20
    81.9
    best: 83.6 (DualCoOp+TaI-DPT)
    SOTA
    DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited AnnotationsarXiv:2206.09541
  • Image ClassificationonPASCAL VOC 2007
    Average mAP· 2022-06-20
    93.2
    best: 94.8 (DualCoOp+TaI-DPT)
    SOTA
    DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited AnnotationsarXiv:2206.09541

Methodology2 results

  • 2D ClassificationonMS-COCO-2014
    Average mAP· 2022-06-20
    81.9
    best: 83.6 (DualCoOp+TaI-DPT)
    SOTA
    DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited AnnotationsarXiv:2206.09541
  • 2D ClassificationonPASCAL VOC 2007
    Average mAP· 2022-06-20
    93.2
    best: 94.8 (DualCoOp+TaI-DPT)
    SOTA
    DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited AnnotationsarXiv:2206.09541