Name
Abstract | ||
|---|---|---|
Co-salient object detection (CoSOD) aims to detect common salient objects sharing the same attributes in an image group. The key issue of CoSOD is how to model the inter-saliency relations within an image group. The major limitation of previous methods is that they pre-define the group-to-one relations within an image group. In this paper, we propose a new concept of structural inter-saliency relations and solve the CoSOD with deep reinforcement learning framework. Firstly, we design a semantic relation graph (SRG) to model the structural inter-saliency relations. Then the feature selecting agent (FS-agent) aims to select the informative features, which can help the SRG effectively model structural inter-saliency relations. Finally, relation updating agent (RU-agent) progressively updates the SRG to focus on the co-salient relations like human decision-making process. Extensive experiments on co-saliency datasets show that because of well modeling inter-saliency relations in image group, our proposed method achieves superior performance compared to the state-of-the-art methods. We hope that this paper can motivate future research for visual co-analysis tasks. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TCSVT.2022.3150923 | IEEE Transactions on Circuits and Systems for Video Technology |
Keywords | DocType | Volume |
Co-saliency detection,deep reinforcement learning,graph convolutional network | Journal | 32 |
Issue | ISSN | Citations |
8 | 1051-8215 | 0 |
PageRank | References | Authors |
0.34 | 41 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lv Tang | 1 | 5 | 2.05 |
| Bo Li | 2 | 8 | 8.65 |
| Senyun Kuang | 3 | 0 | 1.01 |
| Mofei Song | 4 | 0 | 0.34 |
| Shouhong Ding | 5 | 0 | 1.69 |