红外技术2025，Vol.47Issue(6)：722-728,7.
结合上下文信息的红外-可见光行人重识别
Infrared-Visible Person Re-Identification Based on Context Information
摘要
Abstract
The purpose of an infrared-visible person re-identification task is to match RGB and infrared images of the same identity.Because of the different imaging principles of the two modalities,it is difficult to efficiently extract discriminative modality-shared features.To address this issue,this study proposes a Modality-shared feature enhancement module and a global feature enhancement module that jointly extract enhanced discriminative global features.First,a modality-shared feature enhancement module is added to the backbone network to alleviate modality information and enhance modality-shared features with contextual information.Second,the global feature enhanced module encodes global features and jointly optimizes the loss function to further enhance the discriminative power of the global features while mining pattern features.Finally,the mutual mean learning method was used to reduce modality differences and constrain the feature representation.Experiments on mainstream datasets show that the proposed method achieves higher accuracy than existing methods.关键词
行人重识别/红外/上下文信息/互均值学习Key words
person re-identification/infrared/context information/mutual mean learning分类
计算机与自动化引用本文复制引用
葛斌,郑海君,石怀忠,夏晨星,邬成..结合上下文信息的红外-可见光行人重识别[J].红外技术,2025,47(6):722-728,7.基金项目
国家自然科学基金(6210071479,62102003) （6210071479,62102003）
国家重大专项(2020YFB1314103) （2020YFB1314103）
安徽省自然科学基金(2108085QF258) （2108085QF258）
安徽省博士后基金(2022B623) （2022B623）
安徽省高等学校自然科学研究项目(KJ2020A0299). （KJ2020A0299）
