基于多模态知识对齐的双分支点云语义分割算法
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杨军,卯恒睿,党吉圣
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Dual-branch point cloud semantic segmentation algorithm based on multimodal knowledge alignment
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Jun YANG,Hengrui MAO,Jisheng DANG
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| 表 1 SemanticKITTI数据集上不同算法的语义分割性能对比 |
| Tab.1 Comparison of semantic segmentation performance of different algorithms on SemanticKITTI dataset |
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| 模型 | mIoU/% | IoU/% | | 道路 | 人行道 | 停车场 | 其他地面 | 建筑物 | 小汽车 | 卡车 | 坐车 | 摩托车 | | PointNet++[17] | 20.1 | 72.0 | 41.8 | 18.7 | 5.6 | 62.3 | 53.7 | 0.9 | 1.9 | 0.2 | | Cylinder3D[18] | 66.9 | 94.5 | 81.2 | 44.8 | 1.0 | 90.5 | 97.1 | 85.1 | 70.3 | 54.5 | | TFNet[19] | 66.1 | 90.6 | 75.3 | 68.5 | 29.0 | 91.6 | 94.3 | 38.4 | 60.7 | 58.5 | | WaffleIron[20] | 68.0 | 95.5 | 83.6 | 50.2 | 6.4 | 92.1 | 96.1 | 77.4 | 58.1 | 79.7 | | SalsaNext+[21] | 59.5 | 93.3 | 78.8 | 55.8 | 7.7 | 90.2 | 93.5 | 50.4 | 40.2 | 43.3 | | RViT-FLARES[22] | 66.1 | 91.6 | 77.3 | 71.1 | 32.7 | 91.4 | 95.6 | 52.4 | 56.3 | 60.5 | | PC-BEV[23] | 67.2 | 93.0 | 79.8 | 73.5 | 32.1 | 92.1 | 96.5 | 37.6 | 66.5 | 57.7 | | 2DPASS[24] | 68.3 | 94.0 | 81.3 | 49.1 | 4.2 | 91.7 | 96.6 | 92.4 | 52.7 | 76.9 | | 本文模型 | 69.1 | 94.4 | 82.0 | 52.3 | 3.6 | 91.7 | 97.2 | 92.5 | 56.4 | 77.3 | | | 模型 | IoU/% | | 其他车辆 | 植被 | 树干 | 地形 | 行人 | 骑自行车的人 | 骑摩托车的人 | 围栏 | 立杆 | 交通标志 | | PointNet++[17] | 0.2 | 46.5 | 13.8 | 30.0 | 0.9 | 1.0 | 0.0 | 16.9 | 6.0 | 8.9 | | Cylinder3D[18] | 80.9 | 76.5 | 92.2 | 0.0 | 86.6 | 70.8 | 70.4 | 58.7 | 64.2 | 51.8 | | TFNet[19] | 48.4 | 83.8 | 71.1 | 67.0 | 74.3 | 72.2 | 35.5 | 67.3 | 60.8 | 68.7 | | WaffleIron[20] | 59.0 | 87.8 | 73.8 | 73.0 | 81.1 | 92.2 | 1.2 | 67.5 | 65.7 | 52.2 | | SalsaNext+[21] | 41.1 | 81.8 | 63.6 | 70.9 | 49.3 | 76.6 | 9.6 | 56.9 | 54.3 | 48.9 | | RViT-FLARES[22] | 57.1 | 83.1 | 68.0 | 68.1 | 72.0 | 69.7 | 16.0 | 67.4 | 58.0 | 67.5 | | PC-BEV[23] | 48.2 | 85.4 | 70.0 | 70.0 | 62.5 | 68.0 | 49.1 | 69.2 | 62.4 | 63.0 | | 2DPASS[24] | 66.1 | 89.2 | 71.9 | 76.4 | 78.3 | 92.8 | 2.7 | 66.3 | 62.5 | 54.0 | | 本文模型 | 74.8 | 89.4 | 73.2 | 76.6 | 78.6 | 91.0 | 0.2 | 65.3 | 62.6 | 53.0 |
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