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Models/V2VNet (PointPillar backbone)

V2VNet (PointPillar backbone)

Reported on 12 benchmarks across 6 tasks · 1 paper · 12 SOTA

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

Methodology8 results

3DonOPV2V
AP@0.7@CulverCity· 2020-08-17
0.734
best: 0.735 (Attentive Fusion (PointPillar backbone))
SOTA
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction arXiv:2008.07519
3DonOPV2V
AP@0.7@Default· 2020-08-17
0.822
SOTA
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction arXiv:2008.07519
2D ClassificationonOPV2V
AP@0.7@CulverCity· 2020-08-17
0.734
best: 0.735 (Attentive Fusion (PointPillar backbone))
SOTA
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction arXiv:2008.07519
2D ClassificationonOPV2V
AP@0.7@Default· 2020-08-17
0.822
SOTA
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction arXiv:2008.07519
2D Object DetectiononOPV2V
AP@0.7@CulverCity· 2020-08-17
0.734
best: 0.735 (Attentive Fusion (PointPillar backbone))
SOTA
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction arXiv:2008.07519
2D Object DetectiononOPV2V
AP@0.7@Default· 2020-08-17
0.822
SOTA
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction arXiv:2008.07519
16konOPV2V
AP@0.7@CulverCity· 2020-08-17
0.734
best: 0.735 (Attentive Fusion (PointPillar backbone))
SOTA
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction arXiv:2008.07519
16konOPV2V
AP@0.7@Default· 2020-08-17
0.822
SOTA
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction arXiv:2008.07519

Computer Vision4 results

Object DetectiononOPV2V
AP@0.7@CulverCity· 2020-08-17
0.734
best: 0.735 (Attentive Fusion (PointPillar backbone))
SOTA
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction arXiv:2008.07519
Object DetectiononOPV2V
AP@0.7@Default· 2020-08-17
0.822
SOTA
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction arXiv:2008.07519
3D Object DetectiononOPV2V
AP@0.7@CulverCity· 2020-08-17
0.734
best: 0.735 (Attentive Fusion (PointPillar backbone))
SOTA
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction arXiv:2008.07519
3D Object DetectiononOPV2V
AP@0.7@Default· 2020-08-17
0.822
SOTA
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction arXiv:2008.07519