Name
Abstract | ||
|---|---|---|
Video super-resolution (SR) aims at estimating a high-resolution video sequence from a low-resolution (LR) one. Given that the deep learning has been successfully applied to the task of single image SR, which demonstrates the strong capability of neural networks for modeling spatial relation within one single image, the key challenge to conduct video SR is how to efficiently and effectively exploi... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TIP.2018.2820807 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
Neural networks,Adaptive systems,Motion compensation,Machine learning,Optical imaging,Image resolution,Adaptation models | Spatial relation,Pattern recognition,Adaptive system,Motion compensation,Robustness (computer science),Artificial intelligence,Deep learning,Artificial neural network,Image resolution,Optical flow,Mathematics | Journal |
Volume | Issue | ISSN |
27 | 7 | 1057-7149 |
Citations | PageRank | References |
5 | 0.41 | 17 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ding Liu | 1 | 611 | 32.97 |
| Zhaowen Wang | 2 | 1063 | 40.64 |
| Yuchen Fan | 3 | 332 | 17.14 |
| Xianming Liu | 4 | 216 | 19.73 |
| Zhangyang Wang | 5 | 437 | 75.27 |
| Shiyu Chang | 6 | 770 | 51.07 |
| Xinchao Wang | 7 | 474 | 43.70 |
| Thomas S. Huang | 8 | 27815 | 2618.42 |