DMFFNet: Dual-Mode Multiscale Feature Fusion-Based Pedestrian Detection Method
Most contemporary pedestrian detection algorithms are based on visible light image detection. However, in environments with dim light, small targets, and easily occluded and cluttered backgrounds, single-mode visible light images relying on color, texture, and other features cannot adequately repres...
Saved in:
| Main Authors: | Ruizhe Hu, Ting Rui, Yan Ouyang, Jinkang Wang, Qunyan Jiang, Yinan Du |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9805743/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multi-scale cross-layer fusion and center position network for pedestrian detection
by: Qian Liu, et al.
Published: (2024-01-01) -
Multiscale Feature Fusion for Salient Object Detection of Strip Steel Surface Defects
by: Li Zhang, et al.
Published: (2025-01-01) -
Multispectral Target Detection Based on Deep Feature Fusion of Visible and Infrared Modalities
by: Yongsheng Zhao, et al.
Published: (2025-05-01) -
EHAFF-NET: Enhanced Hybrid Attention and Feature Fusion for Pedestrian ReID
by: Jun Yang, et al.
Published: (2025-02-01) -
Multimodal fusion transformer network for multispectral pedestrian detection in low-light condition
by: Gong Li, et al.
Published: (2025-05-01)