Name
Title | ||
|---|---|---|
A Deep Spatial Contextual Long-term Recurrent Convolutional Network for Saliency Detection. |
Abstract | ||
|---|---|---|
Traditional saliency models usually adopt hand-crafted image features and human-designed mechanisms to calculate local or global contrast. In this paper, we propose a novel computational saliency model, i.e., deep spatial contextual long-term recurrent convolutional network (DSCLRCN), to predict where people look in natural scenes. DSCLRCN first automatically learns saliency related local features... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TIP.2018.2817047 | IEEE Transactions on Image Processing |
Keywords | DocType | Volume |
Feature extraction,Visualization,Context modeling,Computational modeling,Saliency detection,Task analysis,Modulation | Journal | 27 |
Issue | ISSN | Citations |
7 | 1057-7149 | 26 |
PageRank | References | Authors |
0.85 | 36 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nian Liu | 1 | 318 | 12.08 |
| Junwei Han | 2 | 3501 | 194.57 |