Name
Title | ||
|---|---|---|
Low-Complexity Deep No-Reference Light Field Image Quality Assessment with Discriminative EPI Patches Focused |
Abstract | ||
|---|---|---|
Light field image quality assessment (LF-IQA) has attracted increasing research interests due to the fast-growing demands for immersive media experience. In this paper, we propose a low-complexity deep residual convolutional neural network (CNN) based no-reference (NR) LF-IQA approach for potential applications of light field images on consumer electronic devices. For efficient and accurate LF-IQA... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICCE50685.2021.9427654 | 2021 IEEE International Conference on Consumer Electronics (ICCE) |
Keywords | DocType | ISBN |
Light field,image quality assessment,convolutional neural network,Epipolar Plane Image | Conference | 978-1-7281-9766-1 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ping Zhao | 1 | 0 | 0.34 |
| Xiaoming Chen | 2 | 50 | 4.50 |
| Yuk Ying Chung | 3 | 211 | 25.47 |
| Haisheng Li | 4 | 10 | 10.14 |