Name
Title | ||
|---|---|---|
FilterNet: Adaptive Information Filtering Network for Accurate and Fast Image Super-Resolution |
Abstract | ||
|---|---|---|
Deep convolutional neural network (CNN) approaches have achieved impressive performance for image super-resolution (SR). The main issue of image SR is to effectively recover the high-frequency detail of low-resolution (LR) input. However, existing CNN methods often inevitably exhibit a large amount of memory consumption and computational cost. In addition, in most SR networks, the low-frequency an... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TCSVT.2019.2906428 | IEEE Transactions on Circuits and Systems for Video Technology |
Keywords | DocType | Volume |
Image reconstruction,Image resolution,Convolution,Information filters,Convolutional neural networks,Training | Journal | 30 |
Issue | ISSN | Citations |
6 | 1051-8215 | 6 |
PageRank | References | Authors |
0.44 | 24 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Feng Li | 1 | 8 | 2.97 |
| Bai Huihui | 2 | 243 | 41.01 |
| Yao Zhao | 3 | 1926 | 219.11 |