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. 2022 Feb 2;22(3):1139. doi: 10.3390/s22031139

Table 6.

Results of SemanticKITTI validation split. Section 1 shows relevant state-of-the-art methods and their results. Section 2 shows our single projections. The fusion approaches are shown in Section 3 and Section 4. Note that the values differ from the published values. This is because the validation data has been used, and there is no post-processing. For the fusion approach, the NN calculation is included within the inference time, and the architectures are not optimized.

Method Inline graphic Car Inline graphic Bicycle Inline graphic Motorcycle Inline graphic Truck Inline graphic Other Vehicle Inline graphic Person Inline graphic Bicyclist Inline graphic Motorcyclist Inline graphic Road Inline graphic Parking Inline graphic Sidewalk Inline graphic Other Ground Inline graphic Building Inline graphic Fence Inline graphic Vegetation Inline graphic Trunk Inline graphic Terrain Inline graphic Pole Inline graphic Traffic Sign mIoU Mean Time
RangeNet21 0.84 0.24 0.34 0.3 0.2 0.35 0.45 0.0 0.93 0.43 0.8 0.01 0.79 0.47 0.81 0.48 0.71 0.39 0.35 0.47 76
SalsaNext 0.86 0.39 0.42 0.78 0.42 0.62 0.68 0.0 0.94 0.42 0.8 0.04 0.80 0.48 0.80 0.58 0.64 0.47 0.44 0.55 52
PolarNet (cart) 0.93 0.27 0.50 0.47 0.27 0.53 0.72 0.0 0.89 0.36 0.72 0.95 0.89 0.46 0.86 0.6 0.74 0.53 0.43 0.53 39
Bird’s-eye 0.8 0.04 0.11 0.06 0.12 0.17 0.36 0.0 0.83 0.22 0.62 0.92 0.85 0.17 0.62 0.37 0.65 0.22 0.19 0.34 33
3D bird’s-eye 0.92 0.11 0.25 0.64 0.3 0.32 0.69 0.0 0.88 0.34 0.69 0.0 0.86 0.35 0.82 0.52 0.7 0.47 0.26 0.48 49
3D bird’s-eye 0.9 0.2 0.68 0.53 0.18 0.45 0.72 0.0 0.89 0.41 0.71 0.0 0.89 0.47 0.86 0.58 0.74 0.51 0.4 0.5 114
3D cylindrical 0.84 0.1 0.1 0.1 0.26 0.25 0.25 0.0 0.84 0.17 0.63 0.0 0.77 0.32 0.79 0.45 0.66 0.39 0.23 0.37 47
SalsaNext [3 × 64 × 512] 0.89 0.34 0.52 0.76 0.46 0.47 0.5 0.0 0.93 0.45 0.78 0.0 0.77 0.5 0.8 0.5 0.67 0.34 0.4 0.53 11
Baseline 0.91 0.32 0.45 0.81 0.38 0.42 0.64 0.0 0.91 0.41 0.75 0.0 0.88 0.51 0.85 0.55 0.71 0.46 0.34 0.54 240
KPFusion 0.93 0.35 0.26 0.62 0.4 0.38 0.65 0.0 0.89 0.37 0.72 0.0 0.88 0.51 0.86 0.59 0.72 0.55 0.46 0.53 386
PointNetFusion 0.91 0.06 0.17 0.66 0.36 0.2 0.09 0.0 0.89 0.34 0.71 0.0 0.86 0.41 0.83 0.36 0.7 0.32 0.35 0.43 291
NN k=8 0.92 0.32 0.47 0.8 0.4 0.44 0.66 0.0 0.91 0.42 0.75 0.0 0.88 0.5 0.85 0.56 0.71 0.49 0.35 0.55 327
KPFusion 0.94 0.4 0.42 0.73 0.42 0.67 0.8 0.0 0.94 0.43 0.8 0.0 0.9 0.59 0.89 0.7 0.78 0.59 0.49 0.61 445
PointNetFusion 0.9 0.19 0.08 0.3 0.22 0.51 0.7 0.0 0.91 0.36 0.76 0.2 0.88 0.5 0.87 0.61 0.76 0.57 0.45 0.5 342