Name
Abstract | ||
|---|---|---|
In real-world image enhancement, it is often challenging (if not impossible) to acquire ground-truth data, preventing the adoption of distance metrics for objective quality assessment. As a result, one often resorts to subjective quality assessment, the most straightforward and reliable means of evaluating image enhancement. Conventional subjective testing requires manually pre-selecting a small s... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/CVPR46437.2021.00077 | 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) |
Keywords | DocType | ISSN |
Photography,Measurement,Visualization,Machine vision,Superresolution,Quality assessment,Pattern recognition | Conference | 1063-6919 |
ISBN | Citations | PageRank |
978-1-6654-4509-2 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peibei Cao | 1 | 0 | 0.34 |
| Zhangyang Wang | 2 | 437 | 75.27 |
| Kede Ma | 3 | 773 | 27.93 |