BiFFN: Bi-Frequency Guided Feature Fusion Network for Visible–Infrared Person Re-Identification
Visible–infrared person re-identification (VI-ReID) aims to minimize the modality gaps of pedestrian images across different modalities. Existing methods primarily focus on extracting cross-modality features from the spatial domain, which often limits the comprehensive extraction of useful informati...
Saved in:
| Main Authors: | Xingyu Cao, Pengxin Ding, Jie Li, Mei Chen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/5/1298 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multi-granularity feature intersection learning for visible-infrared person re-identification
by: Sixian Chan, et al.
Published: (2025-05-01) -
Nystromformer based cross-modality transformer for visible-infrared person re-identification
by: Ranjit Kumar Mishra, et al.
Published: (2025-05-01) -
Practical Evaluation Framework for Real-Time Multi-Object Tracking: Achieving Optimal and Realistic Performance
by: Jumabek Alikhanov, et al.
Published: (2025-01-01) -
A Video SAR Multi-Target Tracking Algorithm Based on Re-Identification Features and Multi-Stage Data Association
by: Anxi Yu, et al.
Published: (2025-03-01) -
Multi-Scale Contrastive Learning with Hierarchical Knowledge Synergy for Visible-Infrared Person Re-Identification
by: Yongheng Qian, et al.
Published: (2025-01-01)