液晶与显示2025，Vol.40Issue(4)：607-616,10.DOI:10.37188/CJLCD.2024-0230
RGB深度图像显著性目标检测方法设计
Design of salience target detection method for RGB depth images
摘要
Abstract
In order to efficiently use depth feature information to assist salient object detection,the fusion of different scale feature information is realized.In this paper,an improved salient object detection algorithm for RGB-D image saliency based on CDINet algorithm is proposed.Firstly,a multi-scale feature fusion module is added to enhance the transmission of feature information between encoder and decoder,so as to effectively reduce shallow feature loss,and obtain more feature information of salient objects through the jump connection of auxiliary decoder.Next,a circular attention module is connected at the tail of the CDINet's network structure,which gradually optimizes local details by using memory-oriented scene understanding.Finally,the loss function is adjusted,and the consistency enhanced loss(CEL)is used to deal with the spatial consistency caused by the fusion of different scale features,and the salient areas are uniformly highlighted without increasing parameters.The experimental results show that compared with the original CDINet algorithm model,the improved model has an F-measure increase of 0.6%and a MAE decrease of 0.4%on LFSD data set,and an F-measure increase of 0.4%and a S-measure decrease of 0.5%on STERE data set.Compared with other algorithm models,this model basically meets the requirements of better detection performance and higher adaptability.关键词
显著性目标检测/计算机视觉/边缘检测/深度学习Key words
significance target detection/computer vision/edge detection/deep learning分类
计算机与自动化引用本文复制引用
王雨夕,徐杨,袁旭祥..RGB深度图像显著性目标检测方法设计[J].液晶与显示,2025,40(4):607-616,10.基金项目
国家自然科学基金(No.61775169) （No.61775169）
辽宁省教育厅科研项目(No.LJKZ0310)Supported by National Natural Science Foundation of China(No.61775169) （No.LJKZ0310）
Research Project of Education Department of Liaoning Province(No.LJKZ0310) （No.LJKZ0310）
