Name
Abstract | ||
|---|---|---|
Most face super-resolution methods assume that low- and high-resolution manifolds have similar local geometrical structure; hence, learn local models on the low-resolution manifold (e.g., sparse or locally linear embedding models), which are then applied on the high-resolution manifold. However, the low-resolution manifold is distorted by the one-to-many relationship between low- and high-resoluti... |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TIP.2017.2717181 | IEEE Transactions on Image Processing |
Keywords | DocType | Volume |
Face,Image resolution,Manifolds,Face recognition,Dictionaries,Image reconstruction,Probes | Journal | 26 |
Issue | ISSN | Citations |
9 | 1057-7149 | 13 |
PageRank | References | Authors |
0.53 | 64 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Reuben A. Farrugia | 1 | 111 | 18.26 |
| Christine Guillemot | 2 | 1286 | 104.25 |