Video Super Resolution On Vid4 4X Upscaling
Metrics
PSNR
SSIM
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | PSNR | SSIM |
|---|---|---|
| video-super-resolution-transformer-with | 28.20 | 0.8507 |
| videogigagan-towards-detail-rich-video-super | 27.04 | - |
| basicvsr-the-search-for-essential-components | 27.39 | 0.8279 |
| evtexture-event-driven-texture-enhancement | 29.78 | 0.8983 |
| basicvsr-the-search-for-essential-components | 27.24 | 0.8251 |
| bidirectional-recurrent-convolutional | 24.43 | 0.662 |
| recurrent-video-restoration-transformer-with | 27.99 | 0.8462 |
| learning-spatial-adaptation-and-temporal | 27.44 | 0.8420 |
| real-time-single-image-and-video-super | 25.06 | 0.7394 |
| deep-back-projection-networks-for-super | 25.37 | 0.737 |
| detail-revealing-deep-video-super-resolution | 25.88 | 0.774 |
| recurrent-back-projection-network-for-video | 27.12 | 0.8180 |
| collaborative-feedback-discriminative | 28.18 | 0.8503 |
| an-implicit-alignment-for-video-super | 28.26 | 0.8517 |
| real-time-video-super-resolution-with-spatio | 25.35 | 0.7557 |
| basicvsr-improving-video-super-resolution | 27.79 | 0.8400 |
| rethinking-alignment-in-video-super | 28.07 | 0.8485 |
| vrt-a-video-restoration-transformer | 27.93 | 0.8425 |
| temporally-coherent-gans-for-video-super | 25.89 | - |
| learning-for-video-super-resolution-through | 26.01 | 0.771 |
| image-super-resolution-using-deep | 24.68 | 0.7158 |
| deep-video-super-resolution-network-using | 27.33 | 0.8319 |
| edvr-video-restoration-with-enhanced | 27.35 | 0.8264 |
| temporally-coherent-gans-for-video-super | 25.57 | - |
| real-time-video-super-resolution-with-spatio | 23.82 | 0.6548 |
| evtexture-event-driven-texture-enhancement | 29.51 | 0.8909 |
| deep-video-super-resolution-using-hr-optical | 26 | 0.772 |