Research Article
An Anchor-Free 3D Object Detection Approach Based on Hierarchical Pillars
Table 3
Detection performance comparison among several methods on KITTI validation set (car class).
| Methods | Modality | Anchor free | Stage | Speed (Hz) | 3D detection AP () | BEV detection AP () | Easy | Moderate | Hard | Easy | Moderate | Hard |
| F-PointNet [20] | L+C | N | Two | 5.9 | 83.76 | 70.92 | 63.65 | 88.16 | 84.02 | 76.44 | PointRCNN [21] | L | N | Two | 10 | 89.19 | 78.85 | 77.91 | 90.21 | 87.89 | 85.51 | Fast-PointRCNN [22] | L | N | Two | 15.4 | 89.12 | 79 | 77.48 | 90.12 | 88.1 | 86.24 | VoxelNet [12] | L | N | One | 4.4 | 81.97 | 65.46 | 62.85 | 89.6 | 84.81 | 78.57 | SECOND [13] | L | N | One | 20 | 87.43 | 76.48 | 69.1 | 89.96 | 87.07 | 79.66 | PointPillars [14] | L | N | One | 42 | 87.44 | 77.67 | 75.76 | 89.88 | 87.43 | 85.01 | AFDet [17] | L | Y | One | 35 | 85.68 | 75.57 | 69.31 | 89.42 | 85.45 | 80.56 | Ours | L | Y | One | 35.7 | 88.65 | 78.20 | 76.17 | 90.04 | 87.80 | 84.14 |
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