Attention-Guided Sample-Based Feature Enhancement Network for Crowded Pedestrian Detection Using Vision Sensors
Occlusion presents a major obstacle in the development of pedestrian detection technologies utilizing computer vision. This challenge includes both inter-class occlusion caused by environmental objects obscuring pedestrians, and intra-class occlusion resulting from interactions between pedestrians....
Saved in:
| Main Authors: | Shuyuan Tang, Yiqing Zhou, Jintao Li, Chang Liu, Jinglin Shi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-09-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/24/19/6350 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Pedestrian Trajectory Prediction Based on Dual Social Graph Attention Network
by: Xinhai Li, et al.
Published: (2025-04-01) -
Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection
by: ZHENG Kaikui, et al.
Published: (2025-01-01) -
Pedestrian Trajectory Prediction via Window Attention and Spatial Graph Interaction Network
by: Xiang Gu, et al.
Published: (2025-01-01) -
Pedestrian Crossing Direction Prediction at Intersections for Pedestrian Safety
by: Younggun Kim, et al.
Published: (2025-01-01) -
EHAFF-NET: Enhanced Hybrid Attention and Feature Fusion for Pedestrian ReID
by: Jun Yang, et al.
Published: (2025-02-01)