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Models/MANO-tiny

MANO-tiny

Reported on 8 benchmarks across 2 tasks · 1 paper

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

Computer Vision8 results

  • Image ClassificationonTiny ImageNet Classification
    Validation Acc· uses extra data· 2025-07-03
    87.52
    best: 92.98 (Astroformer)
    Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and PhysicsarXiv:2507.02748
  • Image ClassificationonFlowers-102
    Accuracy· uses extra data· 2025-07-03
    89
    best: 99.76 (CCT-14/7x2)
    Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and PhysicsarXiv:2507.02748
  • Image ClassificationonCIFAR-100
    Percentage correct· uses extra data· 2025-07-03
    85.08
    best: 96.08 (EffNet-L2 (SAM))
    Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and PhysicsarXiv:2507.02748
  • Image ClassificationonFood-101
    Accuracy (%)· uses extra data· 2025-07-03
    82.48
    best: 92.9 (Bamboo (ViTB/16))
    Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and PhysicsarXiv:2507.02748
  • Image ClassificationonOxford-IIIT Pet Dataset
    Accuracy· uses extra data· 2025-07-03
    88.31
    best: 99.6 (OmniVec2)
    Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and PhysicsarXiv:2507.02748
  • Image ClassificationonStanford Cars
    Accuracy· uses extra data· 2025-07-03
    65.68
    best: 96.868 (efficient adaptive ensembling)
    Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and PhysicsarXiv:2507.02748
  • Fine-Grained Image ClassificationonOxford-IIIT Pet Dataset
    Accuracy· uses extra data· 2025-07-03
    88.31
    best: 99.6 (OmniVec2)
    Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and PhysicsarXiv:2507.02748
  • Fine-Grained Image ClassificationonStanford Cars
    Accuracy· uses extra data· 2025-07-03
    65.68
    best: 96.1 (SR-GNN)
    Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and PhysicsarXiv:2507.02748