Semantic Segmentation On Semantic3D
평가 지표
mIoU
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | mIoU |
|---|---|
| large-scale-point-cloud-semantic-segmentation | 73.2% |
| segcloud-semantic-segmentation-of-3d-point | 61.3% |
| semantic-segmentation-for-real-point-cloud | 75.4% |
| fast-semantic-segmentation-of-3d-point-clouds | 54.2% |
| unstructured-point-cloud-semantic | 59.1% |
| 191111236 | 77.4% |
| shellnet-efficient-point-cloud-convolutional | 69.3% |
| graph-attention-convolution-for-point-cloud | 70.8% |
| segcloud-semantic-segmentation-of-3d-point | 58.2% |
| omni-supervised-point-cloud-segmentation-via | 77.8% |
| scf-net-learning-spatial-contextual-features | 77.6% |
| semantic-classification-of-3d-point-clouds | 62.7% |
| deep-projective-3d-semantic-segmentation | 58.5% |
| kpconv-flexible-and-deformable-convolution | 74.6% |
| fg-net-fast-large-scale-lidar-point | 78.2% |
| classification-of-point-cloud-scenes-with | 65.3% |
| large-scale-point-cloud-semantic-segmentation | 76.2% |