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Models/VGG-16 BN

VGG-16 BN

Reported on 6 benchmarks across 2 tasks · 1 paper · 6 SOTA

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

Methodology3 results

  • Domain AdaptationonVizWiz-Classification
    Accuracy - All Images· 2014-09-04
    36.7
    best: 57.2 (VOLO-D5)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • Domain AdaptationonVizWiz-Classification
    Accuracy - Clean Images· 2014-09-04
    41.1
    best: 450 (ViT-8/B-224)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • Domain AdaptationonVizWiz-Classification
    Accuracy - Corrupted Images· 2014-09-04
    31.1
    best: 51.8 (VOLO-D5)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556

Computer Vision3 results

  • Domain GeneralizationonVizWiz-Classification
    Accuracy - All Images· 2014-09-04
    36.7
    best: 57.2 (VOLO-D5)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • Domain GeneralizationonVizWiz-Classification
    Accuracy - Clean Images· 2014-09-04
    41.1
    best: 450 (ViT-8/B-224)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556
  • Domain GeneralizationonVizWiz-Classification
    Accuracy - Corrupted Images· 2014-09-04
    31.1
    best: 51.8 (VOLO-D5)
    SOTA
    Very Deep Convolutional Networks for Large-Scale Image RecognitionarXiv:1409.1556