Camouflaged Object Detection with Feature Decomposition and Edge Reconstruction
University Town of Shenzhen · Tsinghua University · +1 more institution
Abstract
Camouflaged object detection (COD) aims to address the tough issue of identifying camouflaged objects visually blended into the surrounding backgrounds. COD is a challenging task due to the intrinsic similarity of camouflaged objects with the background, as well as their ambiguous boundaries. Existing approaches to this problem have developed various techniques to mimic the human visual system. Albeit effective in many cases, these methods still struggle when camouflaged objects are so deceptive to the vision system. In this paper, we propose the FEature Decomposition and Edge Reconstruction (FEDER) model for COD. The FEDER model addresses the intrinsic similarity of foreground and background by decomposing…
Citation impact
- FWCI
- 36.48
- Percentile
- 100%
- References
- 58
Authors
7Topics & keywords
- Computer science
- Artificial intelligence
- Feature (linguistics)
- Task (project management)
- Enhanced Data Rates for GSM Evolution
- Object (grammar)
- Similarity (geometry)
- Computer vision