基于边界点估计与稀疏卷积神经网络的三维点云语义分割

杨军,张琛

Semantic segmentation of 3D point cloud based on boundary point estimation and sparse convolution neural network

Jun YANG,Chen ZHANG

表 2 不同方法在SemanticKITTI数据集上的分割精度对比

Tab.2 Comparison of segmentation accuracy of different methods on SemanticKITTI dataset

方法 mIoU/% IoU/% road side- walk par- king other-ground buil- ding car truck bicy- cle motor- cycle other-vehicle vegeta- tion trunk terrain per- son bicy- clist motor- cyclist fence pole traffic-sign PointNet [5] 14.6 61.6 35.7 15.8 1.4 41.4 46.3 0.1 1.3 0.3 0.8 31.0 4.6 17.6 0.2 0.2 0.0 12.9 2.4 3.7 SPG [30] 17.4 45.0 28.5 1.6 0.6 64.3 49.3 0.1 0.2 0.2 0.8 48.9 27.2 24.6 0.3 2.7 0.1 20.8 15.9 0.8 PointNet++ [6] 20.1 72.0 41.8 18.7 5.6 62.3 53.7 0.9 1.9 0.2 0.2 46.5 13.8 30.0 0.9 1.0 0.0 16.9 6.0 8.9 TangentConv [28] 40.9 83.9 63.9 33.4 15.4 83.4 90.8 15.2 2.7 16.5 12.1 79.5 49.3 58.1 23.0 28.4 8.1 49.0 35.8 28.5 SpSequenceNet [38] 43.1 90.1 73.9 57.6 27.1 91.2 88.5 29.2 24.0 0.0 22.7 84.0 66.0 65.7 6.3 0.0 0.0 67.7 50.8 48.7 HPGCNN [39] 50.5 89.5 73.6 58.8 34.6 91.2 93.1 21.0 6.5 17.6 23.3 84.4 65.9 70.0 32.1 30.0 14.7 65.5 45.5 41.5 RangeNet++ [40] 52.2 91.8 75.2 65.0 27.8 87.4 91.4 25.7 25.7 34.4 23.0 80.5 55.1 64.6 38.3 38.8 4.8 58.6 47.9 55.9 RandLA-Net [18] 53.9 90.7 73.7 60.3 20.4 86.9 94.2 40.1 26.0 25.8 38.9 81.4 61.3 66.8 49.2 48.2 7.2 56.3 49.2 47.7 PolarNet [41] 54.3 90.8 74.4 61.7 21.7 90.0 93.8 22.9 40.3 30.1 28.5 84.0 65.5 67.8 43.2 40.2 5.6 61.3 51.8 57.5 3D-MiniNet [42] 55.8 91.6 74.5 64.2 25.4 89.4 90.5 28.5 42.3 42.1 29.4 82.8 60.8 66.7 47.8 44.1 14.5 60.8 48.0 56.6 SAFFGCNN [43] 56.6 89.9 73.9 63.5 35.1 91.5 95.0 38.3 33.2 35.1 28.7 84.4 67.1 69.5 45.3 43.5 7.3 66.1 54.3 53.7 KPConv [36] 58.8 88.8 72.7 61.3 31.6 90.5 96.0 33.4 30.2 42.5 31.6 84.8 69.2 69.1 61.5 61.6 11.8 64.2 56.4 48.4 BAAF-Net [35] 59.9 90.9 74.4 62.2 23.6 89.8 95.4 48.7 31.8 35.5 46.7 82.7 63.4 67.9 49.5 55.7 53.0 60.8 53.7 52.0 TORNADONet [44] 61.1 90.8 75.3 65.3 27.5 89.6 93.1 43.1 53.0 44.4 39.4 84.1 64.3 69.6 61.6 56.7 20.2 62.9 55.0 64.2 FusionNet [20] 61.3 91.8 77.1 68.8 30.8 92.5 95.3 41.8 47.5 37.7 34.5 84.5 69.8 68.5 59.5 56.8 11.9 69.4 60.0 66.5 本研究方法 62.7 92.7 78.5 71.6 31.5 91.4 95.5 40.9 46.1 48.0 42.2 85.2 68.4 70.2 63.9 54.3 23.8 68.6 56.7 62.8