INSANet: INtra-INter Spectral Attention Network for Effective Feature Fusion of Multispectral Pedestrian Detection
Pedestrian detection is a critical task for safety-critical systems, but detecting pedestrians is challenging in low-light and adverse weather conditions. Thermal images can be used to improve robustness by providing complementary information to RGB images. Previous studies have shown that multi-mod...
Main Authors: | Sangin Lee, Taejoo Kim, Jeongmin Shin, Namil Kim, Yukyung Choi |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-02-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/24/4/1168 |
Similar Items
-
HAFNet: Hierarchical Attentive Fusion Network for Multispectral Pedestrian Detection
by: Peiran Peng, et al.
Published: (2023-04-01) -
Multispectral Benchmark Dataset and Baseline for Forklift Collision Avoidance
by: Hyeongjun Kim, et al.
Published: (2022-10-01) -
Attention Fusion for One-Stage Multispectral Pedestrian Detection
by: Zhiwei Cao, et al.
Published: (2021-06-01) -
All-Weather Pedestrian Detection Based on Double-Stream Multispectral Network
by: Chih-Hsien Hsia, et al.
Published: (2023-05-01) -
Attention-Based Cross-Modality Feature Complementation for Multispectral Pedestrian Detection
by: Qunyan Jiang, et al.
Published: (2022-01-01)