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Models/E3D-L

E3D-L

Reported on 6 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.

Robots3 results

  • Activity RecognitiononSomething-Something V2
    GFLOPs· 2023-03-05
    18.3
    best: 13321 (InternVideo2-6B)
    Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video RecognitionarXiv:2303.02693
  • Activity RecognitiononSomething-Something V2
    Top-1 Accuracy· 2023-03-05
    65.7
    best: 77.3 (MVD (Kinetics400 pretrain, ViT-H, 16 frame))
    Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video RecognitionarXiv:2303.02693
  • Activity RecognitiononSomething-Something V2
    Top-5 Accuracy· 2023-03-05
    89.8
    best: 96.3 (DejaVid)
    Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video RecognitionarXiv:2303.02693

Time Series3 results

  • Action RecognitiononSomething-Something V2
    GFLOPs· 2023-03-05
    18.3
    best: 13321 (InternVideo2-6B)
    Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video RecognitionarXiv:2303.02693
  • Action RecognitiononSomething-Something V2
    Top-1 Accuracy· 2023-03-05
    65.7
    best: 77.3 (MVD (Kinetics400 pretrain, ViT-H, 16 frame))
    Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video RecognitionarXiv:2303.02693
  • Action RecognitiononSomething-Something V2
    Top-5 Accuracy· 2023-03-05
    89.8
    best: 96.3 (DejaVid)
    Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video RecognitionarXiv:2303.02693