TF-YOLO: A Transformer–Fusion-Based YOLO Detector for Multimodal Pedestrian Detection in Autonomous Driving Scenes

• Published in: World electric vehicle journal Vol. 14; no. 12; p. 352
• Main Authors: Chen, Yunfan, Ye, Jinxing, Wan, Xiangkui
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2023
• Subjects: Computer networks; convolutional neural network; Datasets; deep learning; Detectors; Illumination; Infrared imagery; Light; Lighting; Methods; multimodal images; Neural networks; pedestrian detection; Pedestrians; Performance enhancement; Sensors; Smog; Transformers

Recent research demonstrates that the fusion of multimodal images can improve the performance of pedestrian detectors under low-illumination environments. However, existing multimodal pedestrian detectors cannot adapt to the variability of environmental illumination. When the lighting conditions of...