Point Cloud Quality Assessment on SJTU WPC (cross-dataset)
0.8173SRCCUPDA
Evaluation results
| Method | Links | ||
|---|---|---|---|
| UPDABackbone=MM-PCQA, Train/Test Method=UPDA2026.02 | 0.8173 | 0.8283 | |
| UPDABackbone=GMS-3DQA, Train/Test Method=UPDA2026.02 | 0.8167 | 0.8354 | |
| MM-PCQABackbone=MM-PCQA, Train/Test Method=DirAdapt2026.02 | 0.7856 | 0.8094 | |
| MM-PCQABackbone=MM-PCQA, Train/Test Method=NoAdapt2026.02 | 0.7851 | 0.8238 | |
| 3DTABackbone=3DTA, Train/Test Method=DirAdapt2026.02 | 0.7839 | 0.8114 | |
| UPDABackbone=3DTA, Train/Test Method=UPDA2026.02 | 0.7819 | 0.8189 | |
| 3DTABackbone=3DTA, Train/Test Method=NoAdapt2026.02 | 0.763 | 0.8046 | |
| GMS-3DQABackbone=GMS-3DQA, Train/Test Method=DirAdapt2026.02 | 0.7621 | 0.7592 | |
| GMS-3DQABackbone=GMS-3DQA, Train/Test Method=NoAdapt2026.02 | 0.7592 | 0.7942 | |
| PQA-NetBackbone=PQA-Net, Train/Test Method=NoAdapt2026.02 | 0.6267 | 0.661 | |
| UPDABackbone=GMS-3DQA, Train/Test Method=UPDA2026.02 | 0.5397 | 0.5542 | |
| IT-PCQABackbone=IT-PCQA, Train/Test Method=UDA2026.02 | 0.4923 | 0.4875 | |
| UPDABackbone=3DTA, Train/Test Method=UPDA2026.02 | 0.4814 | 0.5483 | |
| GMS-3DQABackbone=GMS-3DQA, Train/Test Method=NoAdapt2026.02 | 0.4602 | 0.4951 | |
| GMS-3DQABackbone=GMS-3DQA, Train/Test Method=DirAdapt2026.02 | 0.4435 | 0.4327 | |
| IT-PCQABackbone=IT-PCQA, Train/Test Method=UDA2026.02 | 0.4219 | 0.4233 | |
| 3DTABackbone=3DTA, Train/Test Method=DirAdapt2026.02 | 0.3564 | 0.4543 | |
| PQA-NetBackbone=PQA-Net, Train/Test Method=NoAdapt2026.02 | 0.3518 | 0.3588 | |
| 3DTABackbone=3DTA, Train/Test Method=NoAdapt2026.02 | 0.3372 | 0.4409 | |
| UPDABackbone=MM-PCQA, Train/Test Method=UPDA2026.02 | 0.2381 | 0.4659 | |
| MM-PCQABackbone=MM-PCQA, Train/Test Method=DirAdapt2026.02 | 0.1852 | 0.4231 | |
| MM-PCQABackbone=MM-PCQA, Train/Test Method=NoAdapt2026.02 | 0.1752 | 0.458 |