Video Frame Interpolation On Snu Film Medium
Métriques
PSNR
SSIM
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | PSNR | SSIM |
|---|---|---|
| learning-cross-video-neural-representations | 35.94 | 0.9797 |
| spatio-temporal-multi-flow-network-for-video | 37.111 | - |
| enhanced-bi-directional-motion-estimation-for | 36.07 | 0.980 |
| video-frame-interpolation-with-densely | 36.25 | 0.9799 |
| extracting-motion-and-appearance-via-inter | 36.09 | 0.9801 |
| a-unified-pyramid-recurrent-network-for-video | 36.29 | 0.9801 |
| deep-bayesian-video-frame-interpolation | 36.95 | 0.985 |
| vfimamba-video-frame-interpolation-with-state | 36.40 | 0.9805 |