Image Quality Assessment On Msu Nr Vqa
Metriken
KLCC
PLCC
SRCC
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | KLCC | PLCC | SRCC |
|---|---|---|---|
| norm-in-norm-loss-with-faster-convergence-and | 0.7589 | 0.9106 | 0.9104 |
| perceptual-quality-assessment-of-smartphone | 0.7106 | 0.8855 | 0.8799 |
| from-patches-to-pictures-paq-2-piq-mapping | 0.7079 | 0.8549 | 0.8705 |
| koniq-10k-towards-an-ecologically-valid-and | 0.6608 | 0.8464 | 0.8360 |
| nima-neural-image-assessment | 0.6745 | 0.8784 | 0.8494 |
| unique-unsupervised-image-quality-estimation | 0.7648 | 0.9238 | 0.9148 |
| perceptual-quality-assessment-of-smartphone | 0.7148 | 0.8824 | 0.8794 |
| Modell 8 | 0.3755 | 0.2898 | 0.5066 |
| musiq-multi-scale-image-quality-transformer | 0.7433 | 0.9068 | 0.9004 |
| perceptual-quality-assessment-of-smartphone | 0.7186 | 0.8814 | 0.8822 |