Pedestrian detection methods have been significantly improved with the development of
deep convolutional neural networks. Nevertheless, detecting ismall-scaled pedestrians and …

In this paper, we address the challenging problem of detecting pedestrians, which are
heavily occluded and/or far from cameras. Unlike most existing pedestrian detection …

Pedestrian detection in the wild remains a challenging problem especially for scenes
containing serious occlusion. In this paper, we propose a novel feature learning method in …

Pedestrian detection is a crucial task in intelligent transportation systems, which can be
applied in autonomous vehicles and traffic scene video surveillance systems. The past few …

As a basic component in the field of computer vision, the pedestrian detection plays an
essential role in several real‐world applications such as video surveillance. The promising …

Pedestrian detection is a canonical problem in computer vision. Motivated by the
observation that the major bottleneck of pedestrian detection lies on the different scales of …

The research in pedestrian detection has made remarkable progress in recent years.
However, robust pedestrian detection in crowded scenes remains a considerable challenge …

Pedestrian detection uses computer vision technology to detect and locate pedestrians in an
image or video sequence. Many traditional and deep learning methods have been …

In recent years, the performance of the convolutional neural network-based pedestrian
detection method has improved significantly. However, an imbalance remains between …

Abstract Although the Region-based Convolutional Neural Network (R-CNN) families have
shown promising results for object detection, they still face great challenges for task-specific …