Stacked Cross Refinement Network for Edge-Aware Salient Object Detection
University of Chinese Academy of Sciences · Beijing Institute of Big Data Research · +1 more institution
Abstract
Salient object detection is a fundamental computer vision task. The majority of existing algorithms focus on aggregating multi-level features of pre-trained convolutional neural networks. Moreover, some researchers attempt to utilize edge information for auxiliary training. However, existing edge-aware models design unidirectional frameworks which only use edge features to improve the segmentation features. Motivated by the logical interrelations between binary segmentation and edge maps, we propose a novel Stacked Cross Refinement Network (SCRN) for salient object detection in this paper. Our framework aims to simultaneously refine multi-level features of salient object detection and edge detection by…
Citation impact
- FWCI
- 25.72
- Percentile
- 100%
- References
- 54
Authors
3- ZWZhe WuCorresponding
University of Chinese Academy of Sciences, Beijing Institute of Big Data Research
- LSLi Su
Beijing Institute of Big Data Research, University of Chinese Academy of Sciences
- QHQingming Huang
Beijing Institute of Big Data Research, University of Chinese Academy of Sciences, Peng Cheng Laboratory
Topics & keywords
- Computer science
- Benchmark (surveying)
- Enhanced Data Rates for GSM Evolution
- Artificial intelligence
- Salient
- Convolutional neural network
- Segmentation
- Object detection