Name
Title | ||
|---|---|---|
ConnNet: A Long-Range Relation-Aware Pixel-Connectivity Network for Salient Segmentation. |
Abstract | ||
|---|---|---|
Salient segmentation aims to segment out attention-grabbing regions, a critical yet challenging task and the foundation of many high-level computer vision applications. It requires semantic-aware grouping of pixels into salient regions and benefits from the utilization of global multi-scale contexts to achieve good local reasoning. Previous works often address it as two-class segmentation problems... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TIP.2018.2886997 | IEEE Transactions on Image Processing |
Keywords | DocType | Volume |
Task analysis,Image segmentation,Object segmentation,Computer architecture,Semantics,Feature extraction,Convolutional neural networks | Journal | 28 |
Issue | ISSN | Citations |
5 | 1057-7149 | 4 |
PageRank | References | Authors |
0.38 | 29 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Kampffmeyer | 1 | 43 | 6.00 |
| Nanqing Dong | 2 | 26 | 3.53 |
| Xiaodan Liang | 3 | 37 | 9.73 |
| Yujia Zhang | 4 | 31 | 9.22 |
| Eric P. Xing | 5 | 87 | 11.44 |