With the rapid development of driverless cars, pedestrian detection has been a canonical
instance of object detection. Although recent deep learning detectors such as RPN+ BF and …

With the big success of deep convolutional neural networks (CNN) in image classification
task, many proposal based networks are proposed to detect given objects in an image …

This paper presents a pedestrian detection approach that uses neural features from a fully
convolutional network (FCN) instead of features manually designed. We train an AdaBoost …

The problem of pedestrian detection receives increasing attention due to the rapid
development of artificial intelligence technologies. In this paper, we propose a deep neural …

As a special task beyond general object detection, pedestrian detection has attracted much
attention in recent years. Despite the significant improvements, detecting pedestrians is still …

Pedestrian detection methods based on deep learning can automatically learn features in
unsupervised or supervised fashions and are capable to learn qualified high level feature …

This paper proposes a boosting-like deep learning (BDL) framework for pedestrian
detection. The fusion of handcrafted and deep learned features is considered to extract more …

Almost all existing state-of-the-art pedestrian detection methods use combination of hand-
crafted features, which cannot well handle the particular challenges in real-world situation …

The problem of pedestrian detection in image and video frames has been extensively
investigated in the past decade. However, the low performance in complex scenes shows …

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 …