文献类型： 会议论文

第一作者： Junjie Cui

作者： Junjie Cui ¹ ; Zhengyu Liu ¹ ; Shuting Yang ² ; Xuejian Zhang ² ; Xia Yuan ¹ ;

作者机构： 1.School of Computer Science and Engineering, Nanjing University of Science and Technology

2.Institute of Agricultural Economy and Information Technology, Ningxia Academy of Agriculture and Forestry Sciences

关键词： Camouflaged object detection;Fractional edge;Interactive task learning

会议名称： Chinese Conference on Pattern Recognition and Computer Vision

主办单位：

页码： 16-28

摘要： Camouflaged object detection is a challenging task because of intrinsic similarity between background and foreground. In the existing models, many confusing edge features eventually lead to bad predictions. In this paper, we propose an Interactive Task Learning Network, in which an improved fractional-order differential operator is used to calculate the gradient intensity of the image. By calculating average gradient and spatial frequency of image, it can adaptively learn the fractional-order v and extract features from different directions. Experiments on three camouflaged datasets indicate that the proposed method is effective and progressiveness.

分类号： tp391.4-53