Pedestrian detection is a challenging research task, and it is widely applied in automatic
driving and intelligent surveillance fields. Although many approaches based on deep …

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

Pedestrian detection, as a research hotspot in the field of computer vision, is widely used in
many fields, such as automatic driving, video surveillance, robots and so on. In recent years …

Pedestrian detection is a crucial task in many vision-based applications, such as video
surveillance, human activity analysis and autonomous driving. Recently, most of the existing …

Pedestrian detection is a specific application of object detection. Compared with general
object detection, it shows similarities and unique characteristics. In addition, it has important …

With the development of pedestrian detection technologies, existing methods can not
simultaneously satisfy high quality detection and fast calculation for practical applications …

We propose a guiding network to assist with training a deep convolutional neural network
(DCNN) to improve the accuracy of pedestrian detection. The guiding network is adaptively …

This paper proposes boosting-like deep learning (BDL) framework for pedestrian detection.
Due to overtraining on the limited training samples, overfitting is a major problem of deep …

Pedestrian detection is an important computer vision algorithm in advanced driver
assistance systems (ADAS). In this paper, we propose a deep learning-based pedestrian …

The application of pedestrian detection is extremely extensive, such as in the field of
intelligent surveillance, unmanned vehicle, and pedestrian analysis. With the development …