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Models/3DV-PointNet++

3DV-PointNet++

Reported on 14 benchmarks across 7 tasks · 1 paper · 14 SOTA

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

Computer Vision6 results

  • VideoonNTU RGB+D
    Cross Subject Accuracy· 2021-12-01
    88.8
    best: 92.3 (Kinet)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202
  • VideoonNTU RGB+D
    Cross View Accuracy· 2021-12-01
    96.3
    best: 96.7 (PSTNet++)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202
  • Temporal Action LocalizationonNTU RGB+D
    Cross Subject Accuracy· 2021-12-01
    88.8
    best: 92.3 (Kinet)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202
  • Temporal Action LocalizationonNTU RGB+D
    Cross View Accuracy· 2021-12-01
    96.3
    best: 96.7 (PSTNet++)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202
  • Action LocalizationonNTU RGB+D
    Cross Subject Accuracy· 2021-12-01
    88.8
    best: 92.3 (Kinet)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202
  • Action LocalizationonNTU RGB+D
    Cross View Accuracy· 2021-12-01
    96.3
    best: 96.7 (PSTNet++)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202

Methodology2 results

  • Zero-Shot LearningonNTU RGB+D
    Cross Subject Accuracy· 2021-12-01
    88.8
    best: 92.3 (Kinet)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202
  • Zero-Shot LearningonNTU RGB+D
    Cross View Accuracy· 2021-12-01
    96.3
    best: 96.7 (PSTNet++)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202

Robots2 results

  • Activity RecognitiononNTU RGB+D
    Cross Subject Accuracy· 2021-12-01
    88.8
    best: 92.3 (Kinet)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202
  • Activity RecognitiononNTU RGB+D
    Cross View Accuracy· 2021-12-01
    96.3
    best: 96.7 (PSTNet++)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202

Natural Language Processing2 results

  • 3D Action RecognitiononNTU RGB+D
    Cross Subject Accuracy· 2021-12-01
    88.8
    best: 92.3 (Kinet)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202
  • 3D Action RecognitiononNTU RGB+D
    Cross View Accuracy· 2021-12-01
    96.3
    best: 96.7 (PSTNet++)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202

Time Series2 results

  • Action RecognitiononNTU RGB+D
    Cross Subject Accuracy· 2021-12-01
    88.8
    best: 92.3 (Kinet)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202
  • Action RecognitiononNTU RGB+D
    Cross View Accuracy· 2021-12-01
    96.3
    best: 96.7 (PSTNet++)
    SOTA
    3DVNet: Multi-View Depth Prediction and Volumetric RefinementarXiv:2112.00202