计算机工程与应用2025，Vol.61Issue(10)：228-237,10.DOI:10.3778/j.issn.1002-8331.2401-0200
融合多尺度交叉注意力和边缘感知的伪装目标检测
Camouflaged Object Detection Based on Multi-Scale Cross Attention and Edge Perception
摘要
Abstract
Aiming at the problem that current camouflaged object detection algorithms being unable accurately and com-pletely detect target objects and their edges,a camouflaged object detection network integrating multi-scale cross attention and edge perception(MAEP-Net)is proposed.Use Res2Net-50 to extract the original features of the image,use a feature pyramid structure that integrates multi-scale cross attention to mine target position information and highlight disguised target area features from both channel and spatial dimensions.Use a positioning module to accurately locate the approximate position of the target.The edge perception module suppresses background noise in low-level features and fuses edge features to obtain more edge detail information.The final refining module concentrates on target clues from both foreground and background directions through attention mechanisms,and further refines the target structure and edge contours by using edge prior,semantic prior,domain prior,and region prior knowledge.Experimental results on 3 public datasets have shown that the proposed algorithm outperforms 12 mainstream algorithms in all 4 objective evaluation metrics,especially on the COD10K dataset where the weighted average F-measure and mean absolute error(MAE)of the proposed algorithm reach 0.797 and 0.031 respectively.It follows that the proposed algorithm has good detection performance in COD tasks.关键词
多尺度交叉注意力/边缘感知/伪装目标检测/特征金字塔结构Key words
multi-scale cross attention/edge perception/camouflaged object detection/feature pyramid structure分类
信息技术与安全科学引用本文复制引用
郝子强,张庆宝,赵世豪,王焯豪,詹伟达..融合多尺度交叉注意力和边缘感知的伪装目标检测[J].计算机工程与应用,2025,61(10):228-237,10.基金项目
吉林省科技发展计划项目(20210204118YY). （20210204118YY）
