Name
Abstract | ||
|---|---|---|
•We develop a lightweight deep learning model for photo-realistic super-resolution.•It requires 25% fewer operations than others while achieving better performance.•Our method can handle multiple scale factors with a single network.•We provide various analyses such as initialization schemes or efficiency trade-off. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.patcog.2022.108649 | Pattern Recognition |
Keywords | DocType | Volume |
Super-resolution,Photo-realistic,Convolutional neural network,Efficient model,Adversarial learning,Multi-scale approach | Journal | 127 |
ISSN | Citations | PageRank |
0031-3203 | 0 | 0.34 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Namhyuk Ahn | 1 | 6 | 3.13 |
| Kang, Byungkon | 2 | 21 | 3.77 |
| Kyung-Ah Sohn | 3 | 38 | 13.32 |