Video Frame Interpolation On Ucf101 1
Metrics
PSNR
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | PSNR |
|---|---|
| spatio-temporal-multi-flow-network-for-video | 33.384 |
| asymmetric-bilateral-motion-estimation-for | 35.38 |
| enhanced-bi-directional-motion-estimation-for | 35.41 |
| softmax-splatting-for-video-frame | 35.39 |
| video-frame-interpolation-with-densely | 35.44 |
| extracting-motion-and-appearance-via-inter | 35.48 |
| ifrnet-intermediate-feature-refine-network | 35.42 |
| exploring-motion-ambiguity-and-alignment-for | 35.43 |
| cdfi-compression-driven-network-design-for | 35.21 |
| unsupervised-video-interpolation-using-cycle | - |
| learning-cross-video-neural-representations | 35.36 |
| bmbc-bilateral-motion-estimation-with | 35.15 |
| video-frame-interpolation-via-residue | 34.93 |
| depth-aware-video-frame-interpolation | 34.99 |
| neighbor-correspondence-matching-for-flow | 35.36 |
| vfimamba-video-frame-interpolation-with-state | 35.45 |
| film-frame-interpolation-for-large-motion | 35.32 |
| a-unified-pyramid-recurrent-network-for-video | 35.47 |
| many-to-many-splatting-for-efficient-video | 35.17 |