Name
Abstract | ||
|---|---|---|
Recently, convolutional neural network (CNN)-based methods have achieved remarkable progress in image and video super-resolution, which inspires research on down-/up-sampling-based image and video coding using CNN. Instead of hand-crafted filters for up-sampling, trained CNN models are believed to be more capable of improving image quality, thus leading to coding gain. However, previous studies ei... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TCSVT.2018.2884203 | IEEE Transactions on Circuits and Systems for Video Technology |
Keywords | Field | DocType |
Encoding,Image reconstruction,Image coding,Spatial resolution,High efficiency video coding | Reference frame,Computer vision,Coding gain,Pattern recognition,Convolutional neural network,Computer science,Image quality,Coding (social sciences),Artificial intelligence,Upsampling,Reference software,Video compression picture types | Journal |
Volume | Issue | ISSN |
29 | 12 | 1051-8215 |
Citations | PageRank | References |
8 | 0.47 | 22 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianping Lin | 1 | 12 | 1.89 |
| Dong Liu | 2 | 721 | 74.92 |
| Haitao Yang | 3 | 34 | 5.41 |
| Houqiang Li | 4 | 2090 | 172.30 |
| Feng Wu | 5 | 3635 | 295.09 |