CAGNet: Content-Aware Guidance for Salient Object Detection

Sina Mohammadi, Mehrdad Noori, Ali Bahri, Sina Ghofrani Majelan, Mohammad Havaei. Pattern Recognition 2020;103:107303.

Beneficial from Fully Convolutional Neural Networks (FCNs), saliency detection methods have achieved promising results. However, it is still challenging to learn effective features for detecting salient objects in complicated scenarios, in which i) non-salient regions may have “salient-like” appearance; ii) the salient objects may have different-looking regions. To handle these complex scenarios, we propose a Feature Guide Network which exploits the nature of low-level and high-level features to i) make foreground and background regions more distinct and suppress the non-salient regions which have “salient-like” appearance; ii) assign foreground label to different-looking salient regions. Furthermore, we utilize a Multi-scale Feature Extraction Module (MFEM) for each level of abstraction to obtain multi-scale contextual information. Finally, we design a loss function which outperforms the widely used Cross-entropy loss. By adopting four different pre-trained models as the backbone, we prove that our method is very general with respect to the choice of the backbone model. Experiments on six challenging datasets demonstrate that our method achieves the state-of-the-art performance in terms of different evaluation metrics. Additionally, our approach contains fewer parameters than the existing ones, does not need any post-processing, and runs fast at a real-time speed of 28 FPS when processing a 480 × 480 image.

Related posts

Digital Technology Supercluster Announces Investment to Increase the Effectiveness of Precision Oncology

Digital Technology Supercluster Announces Investment to Increase the Effectiveness of Precision Oncology

Harnessing artificial intelligence to take the guesswork out of diagnosing cancer recurrence for millions of cancer survivors

Read more
How to Bring Biomarker Testing In-House for Cancer Targeted Treatment Selection

How to Bring Biomarker Testing In-House for Cancer Targeted Treatment Selection

Personalized cancer treatment via targeted therapies is two-to-three times more effective than standard chemotherapy for patients with advan

...
Read more
Imagia Cybernetics & Canexia Health Merge to Supercharge Precision Oncology Accessibility

Imagia Cybernetics & Canexia Health Merge to Supercharge Precision Oncology Accessibility

Imagia Cybernetics, an AI-healthcare company that accelerates oncology solutions generated from real world data, today announced its merger

...
Read more