Semantic Segmentation On Scannetv2
평가 지표
Mean IoU
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | Mean IoU |
|---|---|
| pyramid-scene-parsing-network | 47.5% |
| cmx-cross-modal-fusion-for-rgb-x-semantic | 61.3% |
| self-supervised-model-adaptation-for | 50.3 |
| enet-a-deep-neural-network-architecture-for | 37.6% |
| scannet-richly-annotated-3d-reconstructions | 33.0% |
| self-supervised-model-adaptation-for | 57.7 |
| floors-are-flat-leveraging-semantics-for-real | - |
| rfbnet-deep-multimodal-networks-with-residual | 59.2% |
| efficient-multi-task-scene-analysis-with-rgb | 56.4% |
| panopticndt-efficient-and-robust-panoptic | 60.0% |
| 3dmv-joint-3d-multi-view-prediction-for-3d | 49.8% |
| mseg-a-composite-dataset-for-multi-domain-1 | 48.5% |