Lidar Semantic Segmentation On Paris Lille 3D
Metrics
mIOU
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | mIOU |
|---|---|
| generalizing-discrete-convolutions-for | 0.759 |
| exploiting-local-geometry-for-feature-and | 0.785 |
| fg-net-fast-large-scale-lidar-point | 0.819 |
| paris-lille-3d-a-large-and-high-quality | 0.31 |
| generalizing-discrete-convolutions-for | 0.720 |
| lightconvpoint-convolution-for-points | 0.827 |
| cloudspam-contrastive-learning-on-unlabeled | 0.638 |
| kpconv-flexible-and-deformable-convolution | 0.759 |
| cloudspam-contrastive-learning-on-unlabeled | 0.738 |