Multi-Scale Interactive Network for Salient Object Detection
Dalian University of Technology · Peng Cheng Laboratory
Abstract
Deep-learning based salient object detection methods achieve great progress. However, the variable scale and unknown category of salient objects are great challenges all the time. These are closely related to the utilization of multi-level and multi-scale features. In this paper, we propose the aggregate interaction modules to integrate the features from adjacent levels, in which less noise is introduced because of only using small up-/down-sampling rates. To obtain more efficient multi-scale features from the integrated features, the self-interaction modules are embedded in each decoder unit. Besides, the class imbalance issue caused by the scale variation weakens the effect of the binary cross entropy loss…
Citation impact
- FWCI
- 49.63
- Percentile
- 100%
- References
- 65
Authors
4Topics & keywords
- Computer science
- Exploit
- Salient
- Benchmark (surveying)
- Consistency (knowledge bases)
- Artificial intelligence
- Scale (ratio)
- Aggregate (composite)