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Fully convolutional neural networks for LIDAR–camera fusion for pedestrian detection in autonomous vehicle
Pedestrian detection appears to be an integral part of a vast array of vision-based technologies, ranging from item recognition and monitoring via...
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Fusion-attention network using dense scale-invariant feature transform flow image and point cloud for 3D pedestrian detection
In this paper, we introduce a fusion-attention network for three-dimensional (3D) pedestrian detection using the fusion of dense scale-invariant...
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Pedestrian detection based on channel feature fusion and enhanced semantic segmentation
AbstractAt present, pedestrian detection is widely applied to autonomous driving and intelligent transportation and robots, etc. But the balance...
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HF-YOLO: Advanced Pedestrian Detection Model with Feature Fusion and Imbalance Resolution
Pedestrian detection is crucial for various applications, including intelligent transportation and video surveillance systems. Although recent...
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Transformer fusion and histogram layer multispectral pedestrian detection network
Due to the complementarity of multispectral data, the performance of pedestrian detection can be significantly improved, so multispectral pedestrian...
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Cross-modality complementary information fusion for multispectral pedestrian detection
Multispectral pedestrian detection has received increasing attention in recent years as color and thermal modalities can provide complementary visual...
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MLFFCSP: a new anti-occlusion pedestrian detection network with multi-level feature fusion for small targets
Pedestrian detection relying on deep convolution neural networks has achieved significant progress. However, the performance of current pedestrian...
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Context feature fusion and enhanced non-maximum suppression for pedestrian detection in crowded scenes
Pedestrian detection has a wide range of applications in the field of multimedia, and significant progress has been made. However, in densely...
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Multi-window Transformer parallel fusion feature pyramid network for pedestrian orientation detection
In complex traffic scenes, the orientation and location of pedestrians are important criteria for judging their intentions. We note that pedestrians...
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RCSLFNet: a novel real-time pedestrian detection network based on re-parameterized convolution and channel-spatial location fusion attention for low-resolution infrared image
A novel real-time infrared pedestrian detection algorithm is introduced in this study. The proposed approach leverages re-parameterized convolution...
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Efficient feature fusion network based on center and scale prediction for pedestrian detection
Center and scale prediction (CSP) is an anchor-free pedestrian detector with good performance. However, there are lots of parameters in the detector,...
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A feature aggregation network for multispectral pedestrian detection
Pedestrian detection is an important task in many computer vision applications. Since multispectral pedestrian detection can alleviate the...
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Cross-Modal Attentive Recalibration and Dynamic Fusion for Multispectral Pedestrian Detection
Multispectral pedestrian detection can provide accurate and reliable results from color-thermal modalities and has drawn much attention. However, how...
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Pedestrian reidentification based on multiscale convolution feature fusion
The current pedestrian reidentification method based on convolutional neural networks still cannot solve the problems of pedestrian posture change,...
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Cross-Modality Attention and Multimodal Fusion Transformer for Pedestrian Detection
Pedestrian detection is an important challenge in computer vision due to its various applications. To achieve more accurate results, thermal images...
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Detailed Analysis of Pedestrian Activity Recognition in Pedestrian Zones Using 3D Skeleton Joints Using LSTM
As autonomous driving technology is develo** rapidly, demands for pedestrian safety, intelligence, and stability are increasing. In this situation,...
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STIGCN: spatial–temporal interaction-aware graph convolution network for pedestrian trajectory prediction
Accurately predicting the future trajectory of pedestrians is critical for tasks such as autonomous driving and robot navigation. Previous methods...
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Local and Global Contextual Features Fusion for Pedestrian Intention Prediction
Autonomous vehicles (AVs) are becoming an indispensable part of future transportation. However, safety challenges and lack of reliability limit their...
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High-density pedestrian detection algorithm based on deep information fusion
In order to improve the accuracy of high-density population detection, a high density pedestrian detection algorithm (YOLOv4-HDPD) is proposed based...
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AFC-Net: adjacent feature complementary for crowded pedestrian detection
In recent years, despite the significant performance improvement for pedestrian detection algorithms in crowded scenes, an imbalance between...
