Multi-Entity Segmentation on Human3D (val)
85.59mIoUPIC++
Evaluation results
| Method | Links | |
|---|---|---|
| PIC++variant=-Sep, training_protocol=full fine-tuning2024.04 | 85.59 | |
| ACTTraining Strategy=Multi-Dataset Joint Training2024.04 | 84.69 | |
| PointMLPTraining Strategy=Multi-Dataset Joint Training2024.04 | 84.64 | |
| PointNeXtTraining Strategy=Multi-Dataset Joint Training2024.04 | 84.52 | |
| PointNetTraining Strategy=Single Dataset Supervised Training2024.04 | 83.91 | |
| PCMambaTraining Strategy=Multi-Dataset Joint Training2024.04 | 83.74 | |
| PIC++variant=-Cat, training_protocol=full fine-tuning2024.04 | 83.34 | |
| PCTTraining Strategy=Single Dataset Supervised Training2024.04 | 83.16 | |
| PTv3Training Strategy=Multi-Dataset Joint Training2024.04 | 83.13 | |
| PointDiffTraining Strategy=Multi-Dataset Joint Training2024.04 | 83.04 | |
| MAMBA3DTraining Strategy=Multi-Dataset Joint Training2024.04 | 82.36 | |
| PIC++variant=-Sep, training_protocol=scratch2024.04 | 82.36 | |
| PTv2Training Strategy=Multi-Dataset Joint Training2024.04 | 82.15 | |
| PTv1Training Strategy=Multi-Dataset Joint Training2024.04 | 81.11 | |
| PCTTraining Strategy=Multi-Dataset Joint Training2024.04 | 80.75 | |
| PointNetTraining Strategy=Multi-Dataset Joint Training2024.04 | 79.33 | |
| PIC++variant=-Cat, training_protocol=scratch2024.04 | 79.13 | |
| PointLoRATraining Strategy=Multi-Dataset Joint Training2024.04 | 79.02 | |
| I2P-MAETraining Strategy=Multi-Dataset Joint Training2024.04 | 78.57 | |
| PointM2AETraining Strategy=Multi-Dataset Joint Training2024.04 | 78.36 | |
| PICvariant=-Sep2024.04 | 77.93 | |
| DGCNNTraining Strategy=Single Dataset Supervised Training2024.04 | 76.28 | |
| PICvariant=-Cat2024.04 | 75.28 | |
| DGCNNTraining Strategy=Multi-Dataset Joint Training2024.04 | 74.55 | |
| Copy2024.04 | 9.12 |