中南民族大学学报（自然科学版）2024，Vol.43Issue(3)：415-423,9.DOI:10.20056/j.cnki.ZNMDZK.20240317
集间两级语义互补的小样本语义分割
Few-shot semantic segmentation based on inter-set semantic complementarity of two levels
摘要
Abstract
Existing few-shot semantic segmentation models typically rely on single level semantic feature,but due to the small sample data of less sample size and different attributes of semantic features at each level,it is difficult for the network model to extract semantic features at a single level to ensure the segmentation ability and generalization.To solve this problem,a few-shot semantic segmentation based on inter-set semantic complementarity of two levels is proposed.In this method,the high-level semantic features of the support set with strong category are used to weight the generalization middle-level semantic features of the query set,and the generalization capability of the query set semantic features is preserved while the features of the query set target categories are enhanced.In addition,the model enhances the interaction between the two sets of information by optimizing support middle-level semantic feature and constructing non-parametric learning prior information for the query set,so as to obtain richer discriminant information.Experimental results based on PASCAL-5i data set show that the proposed method is effective in solving the problem of few-shot semantic segmentation.The mIoU value of the network can reach 44.6%and 48.8%in 1-shot and 5-shot settings,respectively,and its results surpass some state-of-the-art method.and the number of parameters in the network model is controlled within the acceptable range.关键词
小样本语义分割/原型学习/集间两级语义特征/多尺度Key words
few-shot semantic segmentation/prototype learning/inter-set semantic features of two levels/multi-scale分类
信息技术与安全科学引用本文复制引用
文婧,陈少波..集间两级语义互补的小样本语义分割[J].中南民族大学学报（自然科学版）,2024,43(3):415-423,9.基金项目
中央高校基本科研业务费专项资金资助项目(CZY22012) （CZY22012）
