EHAFF-NET: Enhanced Hybrid Attention and Feature Fusion for Pedestrian ReID

EHAFF-NET: Enhanced Hybrid Attention and Feature Fusion for Pedestrian ReID

This study addresses the cross-scenario challenges in pedestrian re-identification for public safety, including perspective differences, lighting variations, occlusions, and vague feature expressions. We propose a pedestrian re-identification method called EHAFF-NET, which integrates an enhanced hyb...

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Bibliographic Details
Main Authors: Jun Yang, Yan Wang, Haizhen Xie, Jiayue Chen, Shulong Sun, Xiaolan Zhang
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Mathematics
Subjects:
attention mechanisms
deep learning
feature extraction
multi-branch feature fusion
pedestrian re-identification
Online Access:https://www.mdpi.com/2227-7390/13/4/660
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