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Models/Radar-PointGNN: Graph convolutions

Radar-PointGNN: Graph convolutions

Reported on 42 benchmarks across 6 tasks

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

Methodology28 results

  • 3DonnuScenes
    NDS
    0.03
    best: 55.3 (LabelDistill)
  • 3DonnuScenes
    mAAE
    0.93
    best: 1 (BirdNet+ (multisweep))
  • 3DonnuScenes
    mAOE
    0.93
    best: 1.6 (PointNet)
  • 3DonnuScenes
    mAP
    0.01
    best: 45.1 (LabelDistill)
  • 3DonnuScenes
    mASE
    0.92
    best: 1 (qww)
  • 3DonnuScenes
    mATE
    0.97
    best: 1.06 (3D-GCK)
  • 3DonnuScenes
    mAVE
    0.99
    best: 2.21 (PointNet)
  • 2D ClassificationonnuScenes
    NDS
    0.03
    best: 55.3 (LabelDistill)
  • 2D ClassificationonnuScenes
    mAAE
    0.93
    best: 1 (BirdNet+ (multisweep))
  • 2D ClassificationonnuScenes
    mAOE
    0.93
    best: 1.6 (PointNet)
  • 2D ClassificationonnuScenes
    mAP
    0.01
    best: 45.1 (LabelDistill)
  • 2D ClassificationonnuScenes
    mASE
    0.92
    best: 1 (qww)
  • 2D ClassificationonnuScenes
    mATE
    0.97
    best: 1.06 (3D-GCK)
  • 2D ClassificationonnuScenes
    mAVE
    0.99
    best: 2.21 (PointNet)
  • 2D Object DetectiononnuScenes
    NDS
    0.03
    best: 55.3 (LabelDistill)
  • 2D Object DetectiononnuScenes
    mAAE
    0.93
    best: 1 (BirdNet+ (multisweep))
  • 2D Object DetectiononnuScenes
    mAOE
    0.93
    best: 1.6 (PointNet)
  • 2D Object DetectiononnuScenes
    mAP
    0.01
    best: 45.1 (LabelDistill)
  • 2D Object DetectiononnuScenes
    mASE
    0.92
    best: 1 (qww)
  • 2D Object DetectiononnuScenes
    mATE
    0.97
    best: 1.06 (3D-GCK)
  • 2D Object DetectiononnuScenes
    mAVE
    0.99
    best: 2.21 (PointNet)
  • 16konnuScenes
    NDS
    0.03
    best: 55.3 (LabelDistill)
  • 16konnuScenes
    mAAE
    0.93
    best: 1 (BirdNet+ (multisweep))
  • 16konnuScenes
    mAOE
    0.93
    best: 1.6 (PointNet)
  • 16konnuScenes
    mAP
    0.01
    best: 45.1 (LabelDistill)
  • 16konnuScenes
    mASE
    0.92
    best: 1 (qww)
  • 16konnuScenes
    mATE
    0.97
    best: 1.06 (3D-GCK)
  • 16konnuScenes
    mAVE
    0.99
    best: 2.21 (PointNet)

Computer Vision14 results

  • Object DetectiononnuScenes
    NDS
    0.03
    best: 55.3 (LabelDistill)
  • Object DetectiononnuScenes
    mAAE
    0.93
    best: 1 (BirdNet+ (multisweep))
  • Object DetectiononnuScenes
    mAOE
    0.93
    best: 1.6 (PointNet)
  • Object DetectiononnuScenes
    mAP
    0.01
    best: 45.1 (LabelDistill)
  • Object DetectiononnuScenes
    mASE
    0.92
    best: 1 (qww)
  • Object DetectiononnuScenes
    mATE
    0.97
    best: 1.06 (3D-GCK)
  • Object DetectiononnuScenes
    mAVE
    0.99
    best: 2.21 (PointNet)
  • 3D Object DetectiononnuScenes
    NDS
    0.03
    best: 55.3 (LabelDistill)
  • 3D Object DetectiononnuScenes
    mAAE
    0.93
    best: 1 (BirdNet+ (multisweep))
  • 3D Object DetectiononnuScenes
    mAOE
    0.93
    best: 1.6 (PointNet)
  • 3D Object DetectiononnuScenes
    mAP
    0.01
    best: 45.1 (LabelDistill)
  • 3D Object DetectiononnuScenes
    mASE
    0.92
    best: 1 (qww)
  • 3D Object DetectiononnuScenes
    mATE
    0.97
    best: 1.06 (3D-GCK)
  • 3D Object DetectiononnuScenes
    mAVE
    0.99
    best: 2.21 (PointNet)