Benchmark: 3D LiDAR Detection
Results on OPV2V dataset (AP@0.7 for no-compression/ compression)
| | Backbone | Fusion Strategy | Bandwidth (Megabit),
before/after compression| Default Towns |Culver City| Download |
|——————–| ——– | ————— | ————— | ————- |———–| ——– |
| Naive Late | PointPillar | Late | 0.024/0.024 | 0.781/0.781 | 0.668/0.668 | url |
| Cooper | PointPillar | Early | 7.68/7.68 | 0.800/x | 0.696/x | url |
| Attentive Fusion | PointPillar | Intermediate | 126.8/1.98 | 0.815/0.810 | 0.735/0.731 | url |
| F-Cooper | PointPillar | Intermediate | 72.08/1.12 | 0.790/0.788 | 0.728/0.726 | url |
| Naive Late | VoxelNet | Late | 0.024/0.024 | 0.738/0.738 | 0.588/0.588 | url |
| Cooper | VoxelNet | Early | 7.68/7.68 | 0.758/x | 0.677/x | url |
| Attentive Fusion | VoxelNet | Intermediate | 576.71/1.12 | 0.864/0.852 | 0.775/0.746 | url |
| Naive Late | SECOND | Late | 0.024/0.024 | 0.775/0.775 |0.682/0.682 | url |
| Cooper | SECOND | Early | 7.68/7.68 | 0.813/x | 0.738/x | url |
| Attentive | SECOND | Intermediate | 63.4/0.99 | 0.826/0.783 | 0.760/0.760 | url |
| Naive Late | PIXOR | Late | 0.024/0.024 | 0.578/0.578 | 0.360/0.360 | url |
| Cooper | PIXOR | Early | 7.68/7.68 | 0.678/x | 0.558/x | url |
| Attentive | PIXOR | Intermediate | 313.75/1.22 | 0.687/0.612 | 0.546/0.492 | url |
Note:
We suggest using PointPillar as the backbone when you are creating your method and try to compare with our benchmark, as we implement most of the SOTA methods with this backbone only.
We assume the transimssion rate is 27Mbp/s. Considering the frequency of LiDAR is 10Hz, the bandwidth requirement should be less than 2.7Mbp to avoid severe delay.
A ‘x’ in the benchmark table represents the bandwidth requirement is too large, which can not be considered to employ in practice.