3D Object Detection On Opv2V
Metrics
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Results
Performance results of various models on this benchmark
Model Name | [email protected]@CulverCity | [email protected]@Default | Paper Title | Repository |
|---|---|---|---|---|
| Late Fusion (PointPillar backbone) | 0.669 | 0.781 | OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication | - |
| Attentive Fusion (PointPillar backbone) | 0.735 | 0.815 | OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication | - |
| Cooper (PointPillar backbone) | 0.696 | 0.800 | Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds | - |
| F-Cooper (PointPillar backbone) | 0.728 | 0.790 | F-Cooper: Feature based Cooperative Perception for Autonomous Vehicle Edge Computing System Using 3D Point Clouds | - |
| V2VNet (PointPillar backbone) | 0.734 | 0.822 | V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction | - |
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