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Models/Dual-path CNN

Dual-path CNN

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.

Miscellaneous4 results

  • Image Retrieval with Multi-Modal QueryonMSCOCO-1k
    Image-to-text R@1· 2017-11-15
    41.2
    best: 81.9 (NAPReg)
    SOTA
    Dual-Path Convolutional Image-Text Embeddings with Instance LossarXiv:1711.05535
  • Image Retrieval with Multi-Modal QueryonMSCOCO-1k
    Text-to-image R@1· 2017-11-15
    25.3
    best: 66.9 (NAPReg)
    SOTA
    Dual-Path Convolutional Image-Text Embeddings with Instance LossarXiv:1711.05535
  • Cross-Modal Information RetrievalonMSCOCO-1k
    Image-to-text R@1· 2017-11-15
    41.2
    best: 81.9 (NAPReg)
    SOTA
    Dual-Path Convolutional Image-Text Embeddings with Instance LossarXiv:1711.05535
  • Cross-Modal Information RetrievalonMSCOCO-1k
    Text-to-image R@1· 2017-11-15
    25.3
    best: 66.9 (NAPReg)
    SOTA
    Dual-Path Convolutional Image-Text Embeddings with Instance LossarXiv:1711.05535

Natural Language Processing2 results

  • Cross-Modal RetrievalonMSCOCO-1k
    Image-to-text R@1· 2017-11-15
    41.2
    best: 81.9 (NAPReg)
    SOTA
    Dual-Path Convolutional Image-Text Embeddings with Instance LossarXiv:1711.05535
  • Cross-Modal RetrievalonMSCOCO-1k
    Text-to-image R@1· 2017-11-15
    25.3
    best: 66.9 (NAPReg)
    SOTA
    Dual-Path Convolutional Image-Text Embeddings with Instance LossarXiv:1711.05535