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Models/BEVDet4D

BEVDet4D

Reported on 48 benchmarks across 6 tasks · 1 paper · 6 SOTA

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

Methodology60 results

  • 3DonnuScenes Camera Only
    NDS· 2022-03-31
    56.9
    best: 68.7 (Far3D)
    SOTA
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D ClassificationonnuScenes Camera Only
    NDS· 2022-03-31
    56.9
    best: 68.7 (Far3D)
    SOTA
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D Object DetectiononnuScenes Camera Only
    NDS· 2022-03-31
    56.9
    best: 68.7 (Far3D)
    SOTA
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 16konnuScenes Camera Only
    NDS· 2022-03-31
    56.9
    best: 68.7 (Far3D)
    SOTA
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3DonnuScenes
    NDS· 2022-03-31
    0.569
    best: 55.3 (LabelDistill)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3DonnuScenes
    mAAE· 2022-03-31
    0.121
    best: 1 (BirdNet+ (multisweep))
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3DonnuScenes
    mAOE· 2022-03-31
    0.386
    best: 1.6 (PointNet)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3DonnuScenes
    mAP· 2022-03-31
    0.451
    best: 45.1 (LabelDistill)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3DonnuScenes
    mASE· 2022-03-31
    0.241
    best: 1 (qww)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3DonnuScenes
    mATE· 2022-03-31
    0.511
    best: 1.06 (3D-GCK)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3DonnuScenes
    mAVE· 2022-03-31
    0.301
    best: 2.21 (PointNet)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D ClassificationonnuScenes
    NDS· 2022-03-31
    0.569
    best: 55.3 (LabelDistill)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D ClassificationonnuScenes
    mAAE· 2022-03-31
    0.121
    best: 1 (BirdNet+ (multisweep))
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D ClassificationonnuScenes
    mAOE· 2022-03-31
    0.386
    best: 1.6 (PointNet)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D ClassificationonnuScenes
    mAP· 2022-03-31
    0.451
    best: 45.1 (LabelDistill)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D ClassificationonnuScenes
    mASE· 2022-03-31
    0.241
    best: 1 (qww)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D ClassificationonnuScenes
    mATE· 2022-03-31
    0.511
    best: 1.06 (3D-GCK)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D ClassificationonnuScenes
    mAVE· 2022-03-31
    0.301
    best: 2.21 (PointNet)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D Object DetectiononnuScenes
    NDS· 2022-03-31
    0.569
    best: 55.3 (LabelDistill)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D Object DetectiononnuScenes
    mAAE· 2022-03-31
    0.121
    best: 1 (BirdNet+ (multisweep))
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D Object DetectiononnuScenes
    mAOE· 2022-03-31
    0.386
    best: 1.6 (PointNet)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D Object DetectiononnuScenes
    mAP· 2022-03-31
    0.451
    best: 45.1 (LabelDistill)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D Object DetectiononnuScenes
    mASE· 2022-03-31
    0.241
    best: 1 (qww)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D Object DetectiononnuScenes
    mATE· 2022-03-31
    0.511
    best: 1.06 (3D-GCK)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 2D Object DetectiononnuScenes
    mAVE· 2022-03-31
    0.301
    best: 2.21 (PointNet)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 16konnuScenes
    NDS· 2022-03-31
    0.569
    best: 55.3 (LabelDistill)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 16konnuScenes
    mAAE· 2022-03-31
    0.121
    best: 1 (BirdNet+ (multisweep))
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 16konnuScenes
    mAOE· 2022-03-31
    0.386
    best: 1.6 (PointNet)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 16konnuScenes
    mAP· 2022-03-31
    0.451
    best: 45.1 (LabelDistill)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 16konnuScenes
    mASE· 2022-03-31
    0.241
    best: 1 (qww)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 16konnuScenes
    mATE· 2022-03-31
    0.511
    best: 1.06 (3D-GCK)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 16konnuScenes
    mAVE· 2022-03-31
    0.301
    best: 2.21 (PointNet)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3DonnuScenes
    NDS
    0.57
    best: 55.3 (LabelDistill)
  • 3DonnuScenes
    mAAE
    0.12
    best: 1 (BirdNet+ (multisweep))
  • 3DonnuScenes
    mAOE
    0.39
    best: 1.6 (PointNet)
  • 3DonnuScenes
    mAP
    0.45
    best: 45.1 (LabelDistill)
  • 3DonnuScenes
    mASE
    0.24
    best: 1 (qww)
  • 3DonnuScenes
    mATE
    0.51
    best: 1.06 (3D-GCK)
  • 3DonnuScenes
    mAVE
    0.3
    best: 2.21 (PointNet)
  • 2D ClassificationonnuScenes
    NDS
    0.57
    best: 55.3 (LabelDistill)
  • 2D ClassificationonnuScenes
    mAAE
    0.12
    best: 1 (BirdNet+ (multisweep))
  • 2D ClassificationonnuScenes
    mAOE
    0.39
    best: 1.6 (PointNet)
  • 2D ClassificationonnuScenes
    mAP
    0.45
    best: 45.1 (LabelDistill)
  • 2D ClassificationonnuScenes
    mASE
    0.24
    best: 1 (qww)
  • 2D ClassificationonnuScenes
    mATE
    0.51
    best: 1.06 (3D-GCK)
  • 2D ClassificationonnuScenes
    mAVE
    0.3
    best: 2.21 (PointNet)
  • 2D Object DetectiononnuScenes
    NDS
    0.57
    best: 55.3 (LabelDistill)
  • 2D Object DetectiononnuScenes
    mAAE
    0.12
    best: 1 (BirdNet+ (multisweep))
  • 2D Object DetectiononnuScenes
    mAOE
    0.39
    best: 1.6 (PointNet)
  • 2D Object DetectiononnuScenes
    mAP
    0.45
    best: 45.1 (LabelDistill)
  • 2D Object DetectiononnuScenes
    mASE
    0.24
    best: 1 (qww)
  • 2D Object DetectiononnuScenes
    mATE
    0.51
    best: 1.06 (3D-GCK)
  • 2D Object DetectiononnuScenes
    mAVE
    0.3
    best: 2.21 (PointNet)
  • 16konnuScenes
    NDS
    0.57
    best: 55.3 (LabelDistill)
  • 16konnuScenes
    mAAE
    0.12
    best: 1 (BirdNet+ (multisweep))
  • 16konnuScenes
    mAOE
    0.39
    best: 1.6 (PointNet)
  • 16konnuScenes
    mAP
    0.45
    best: 45.1 (LabelDistill)
  • 16konnuScenes
    mASE
    0.24
    best: 1 (qww)
  • 16konnuScenes
    mATE
    0.51
    best: 1.06 (3D-GCK)
  • 16konnuScenes
    mAVE
    0.3
    best: 2.21 (PointNet)

Computer Vision30 results

  • Object DetectiononnuScenes Camera Only
    NDS· 2022-03-31
    56.9
    best: 68.7 (Far3D)
    SOTA
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3D Object DetectiononnuScenes Camera Only
    NDS· 2022-03-31
    56.9
    best: 68.7 (Far3D)
    SOTA
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • Object DetectiononnuScenes
    NDS· 2022-03-31
    0.569
    best: 55.3 (LabelDistill)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • Object DetectiononnuScenes
    mAAE· 2022-03-31
    0.121
    best: 1 (BirdNet+ (multisweep))
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • Object DetectiononnuScenes
    mAOE· 2022-03-31
    0.386
    best: 1.6 (PointNet)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • Object DetectiononnuScenes
    mAP· 2022-03-31
    0.451
    best: 45.1 (LabelDistill)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • Object DetectiononnuScenes
    mASE· 2022-03-31
    0.241
    best: 1 (qww)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • Object DetectiononnuScenes
    mATE· 2022-03-31
    0.511
    best: 1.06 (3D-GCK)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • Object DetectiononnuScenes
    mAVE· 2022-03-31
    0.301
    best: 2.21 (PointNet)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3D Object DetectiononnuScenes
    NDS· 2022-03-31
    0.569
    best: 55.3 (LabelDistill)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3D Object DetectiononnuScenes
    mAAE· 2022-03-31
    0.121
    best: 1 (BirdNet+ (multisweep))
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3D Object DetectiononnuScenes
    mAOE· 2022-03-31
    0.386
    best: 1.6 (PointNet)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3D Object DetectiononnuScenes
    mAP· 2022-03-31
    0.451
    best: 45.1 (LabelDistill)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3D Object DetectiononnuScenes
    mASE· 2022-03-31
    0.241
    best: 1 (qww)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3D Object DetectiononnuScenes
    mATE· 2022-03-31
    0.511
    best: 1.06 (3D-GCK)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • 3D Object DetectiononnuScenes
    mAVE· 2022-03-31
    0.301
    best: 2.21 (PointNet)
    BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object DetectionarXiv:2203.17054
  • Object DetectiononnuScenes
    NDS
    0.57
    best: 55.3 (LabelDistill)
  • Object DetectiononnuScenes
    mAAE
    0.12
    best: 1 (BirdNet+ (multisweep))
  • Object DetectiononnuScenes
    mAOE
    0.39
    best: 1.6 (PointNet)
  • Object DetectiononnuScenes
    mAP
    0.45
    best: 45.1 (LabelDistill)
  • Object DetectiononnuScenes
    mASE
    0.24
    best: 1 (qww)
  • Object DetectiononnuScenes
    mATE
    0.51
    best: 1.06 (3D-GCK)
  • Object DetectiononnuScenes
    mAVE
    0.3
    best: 2.21 (PointNet)
  • 3D Object DetectiononnuScenes
    NDS
    0.57
    best: 55.3 (LabelDistill)
  • 3D Object DetectiononnuScenes
    mAAE
    0.12
    best: 1 (BirdNet+ (multisweep))
  • 3D Object DetectiononnuScenes
    mAOE
    0.39
    best: 1.6 (PointNet)
  • 3D Object DetectiononnuScenes
    mAP
    0.45
    best: 45.1 (LabelDistill)
  • 3D Object DetectiononnuScenes
    mASE
    0.24
    best: 1 (qww)
  • 3D Object DetectiononnuScenes
    mATE
    0.51
    best: 1.06 (3D-GCK)
  • 3D Object DetectiononnuScenes
    mAVE
    0.3
    best: 2.21 (PointNet)