Multi‐scale pedestrian detection based on self‐attention and adaptively spatial feature fusion
Abstract Pedestrian detection is a classic problem in computer vision, which has an essential impact on the safety of urban autonomous driving. Although significant improvement has been made in pedestrian detection recently, small‐scale pedestrian detection is still challenging. To effectively tackl...
Main Authors: | Minjun Wang, Houjin Chen, Yanfeng Li, Yuhao You, Jinlei Zhu |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-06-01
|
Series: | IET Intelligent Transport Systems |
Online Access: | https://doi.org/10.1049/itr2.12066 |
Similar Items
-
Adaptive Fusion of Multi-Scale YOLO for Pedestrian Detection
by: Wei-Yen Hsu, et al.
Published: (2021-01-01) -
Adaptive Weighted Multi-Level Fusion of Multi-Scale Features: A New Approach to Pedestrian Detection
by: Yao Xu, et al.
Published: (2021-02-01) -
Deep Feature Fusion by Competitive Attention for Pedestrian Detection
by: Zhichang Chen, et al.
Published: (2019-01-01) -
Spatially Attentive Visual Tracking Using Multi-Model Adaptive Response Fusion
by: Jianming Zhang, et al.
Published: (2019-01-01) -
Attention Based Multi-Layer Fusion of Multispectral Images for Pedestrian Detection
by: Yongtao Zhang, et al.
Published: (2020-01-01)