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

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 …

With pedestrian detection algorithms, balancing the trade-off between accuracy and speed
remains challenging. Following the central point-based one-stage object detection …

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 …

Pedestrian detection has made breakthroughs after the rise of convolutional neural
networks. However, it faces some challenging problems, including dataset difference, small …

Despite rapid development in anchor-free pedestrian detection algorithms, an optimistic
trade-off between detection accuracy and efficiency is still far from being achieved. In this …

Pedestrian detection methods have been significantly improved with the development of
deep convolutional neural networks. Nevertheless, it remains a challenging problem how to …

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 …

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 …

Trade-off or appropriate balance between high accuracy on object identification and fast
speed of identification process is one of the most challenging problems in the study of …