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Models/NIMA

NIMA

Reported on 21 benchmarks across 4 tasks · 1 paper · 12 SOTA

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

Computer Vision15 results

  • Video UnderstandingonMSU NR VQA Database
    KLCC· 2017-09-15
    0.6745
    best: 0.7883 (MDTVSFA)
    SOTA
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • Video UnderstandingonMSU NR VQA Database
    PLCC· 2017-09-15
    0.8784
    best: 0.9431 (MDTVSFA)
    SOTA
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • Video UnderstandingonMSU NR VQA Database
    SRCC· 2017-09-15
    0.8494
    best: 0.9289 (MDTVSFA)
    SOTA
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • Image Quality AssessmentonMSU NR VQA Database
    KLCC· 2017-09-15
    0.6745
    best: 0.7648 (UNIQUE)
    SOTA
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • Image Quality AssessmentonMSU NR VQA Database
    PLCC· 2017-09-15
    0.8784
    best: 0.9238 (UNIQUE)
    SOTA
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • Image Quality AssessmentonMSU NR VQA Database
    SRCC· 2017-09-15
    0.8494
    best: 0.9148 (UNIQUE)
    SOTA
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • VideoonMSU NR VQA Database
    KLCC· 2017-09-15
    0.6745
    best: 0.7883 (MDTVSFA)
    SOTA
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • VideoonMSU NR VQA Database
    PLCC· 2017-09-15
    0.8784
    best: 0.9431 (MDTVSFA)
    SOTA
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • VideoonMSU NR VQA Database
    SRCC· 2017-09-15
    0.8494
    best: 0.9289 (MDTVSFA)
    SOTA
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • Video UnderstandingonMSU SR-QA Dataset
    KLCC· 2017-09-15
    0.20377
    best: 0.69774 (ClipIQA+)
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • Video UnderstandingonMSU SR-QA Dataset
    PLCC· 2017-09-15
    0.2655
    best: 0.75743 (PieAPP)
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • Video UnderstandingonMSU SR-QA Dataset
    SROCC· 2017-09-15
    0.25887
    best: 0.75215 (PieAPP)
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • VideoonMSU SR-QA Dataset
    KLCC· 2017-09-15
    0.20377
    best: 0.69774 (ClipIQA+)
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • VideoonMSU SR-QA Dataset
    PLCC· 2017-09-15
    0.2655
    best: 0.75743 (PieAPP)
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • VideoonMSU SR-QA Dataset
    SROCC· 2017-09-15
    0.25887
    best: 0.75215 (PieAPP)
    NIMA: Neural Image AssessmentarXiv:1709.05424

Time Series6 results

  • Video Quality AssessmentonMSU NR VQA Database
    KLCC· 2017-09-15
    0.6745
    best: 0.7883 (MDTVSFA)
    SOTA
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • Video Quality AssessmentonMSU NR VQA Database
    PLCC· 2017-09-15
    0.8784
    best: 0.9431 (MDTVSFA)
    SOTA
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • Video Quality AssessmentonMSU NR VQA Database
    SRCC· 2017-09-15
    0.8494
    best: 0.9289 (MDTVSFA)
    SOTA
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • Video Quality AssessmentonMSU SR-QA Dataset
    KLCC· 2017-09-15
    0.20377
    best: 0.69774 (ClipIQA+)
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • Video Quality AssessmentonMSU SR-QA Dataset
    PLCC· 2017-09-15
    0.2655
    best: 0.75743 (PieAPP)
    NIMA: Neural Image AssessmentarXiv:1709.05424
  • Video Quality AssessmentonMSU SR-QA Dataset
    SROCC· 2017-09-15
    0.25887
    best: 0.75215 (PieAPP)
    NIMA: Neural Image AssessmentarXiv:1709.05424