Occlusions, scale variation and numerous false positives still represent fundamental
challenges in pedestrian detection. Intuitively, different sizes of receptive fields and more …

Pedestrian detection has attracted more attention in the fields of computer vision and
artificial intelligence. A variety of real-world applications involving pedestrian detection have …

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 is an important but challenging problem in computer vision, especially
in human-centric tasks. Over the past decade, significant improvement has been witnessed …

Although pedestrian detection has achieved promising performance with the development of
deep learning techniques, it remains a great challenge to detect heavily occluded …

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 …

Pedestrian detection is used in many vision based applications ranging from video
surveillance to autonomous driving. Despite achieving high performance, it is still largely …

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 is a very important task in intelligent transportation system. State-of-the-
art detectors work well on non-occluded pedestrians, but they are still far from satisfactory for …

Some factors such as low resolution of small targets, limited target features, and noise
interference affect the effect of pedestrian detection. Therefore, a pedestrian detection …