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Models/MTUT

MTUT

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.

Computer Vision6 results

  • HandonNVGesture
    Accuracy· 2018-12-14
    86.93
    best: 91.7 (De+Recouple)
    SOTA
    Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal TrainingarXiv:1812.06145
  • HandonEgoGesture
    Accuracy· 2018-12-14
    93.87
    best: 94.03 (ResNeXt-101)
    SOTA
    Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal TrainingarXiv:1812.06145
  • HandonVIVA Hand Gestures Dataset
    Accuracy· 2018-12-14
    86.08
    SOTA
    Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal TrainingarXiv:1812.06145
  • Gesture RecognitiononNVGesture
    Accuracy· 2018-12-14
    86.93
    best: 91.7 (De+Recouple)
    SOTA
    Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal TrainingarXiv:1812.06145
  • Gesture RecognitiononEgoGesture
    Accuracy· 2018-12-14
    93.87
    best: 94.03 (ResNeXt-101)
    SOTA
    Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal TrainingarXiv:1812.06145
  • Gesture RecognitiononVIVA Hand Gestures Dataset
    Accuracy· 2018-12-14
    86.08
    SOTA
    Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal TrainingarXiv:1812.06145