sism
ICNet: Intra-saliencyCorrelationNetworkfor Co-SaliencyDetection
Specifically, we adopt normalized masked average pooling (NMAP) to extract latent intra-saliency categories from the SISMs and semantic features as intra cues. Then we employ a correlation fusion module (CFM) to obtain inter cues by exploiting correlations between the intra cues and single-image features. To improve Co-SOD performance, we propose a category-independent rearranged self-correlation feature(RSCF)strategy.
Country:
- Asia > China > Tianjin Province > Tianjin (0.04)
- North America > Canada > British Columbia > Metro Vancouver Regional District > Vancouver (0.04)
Technology:
Country:
- Asia > China > Tianjin Province > Tianjin (0.05)
- North America > Canada > British Columbia > Metro Vancouver Regional District > Vancouver (0.04)
Technology:
- Information Technology > Sensing and Signal Processing > Image Processing (1.00)
- Information Technology > Artificial Intelligence > Vision (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.93)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.68)