There are still many pressing problems in pedestrian detection, such as difficulty in detection
due to severe pedestrian occlusion, difficulty in detecting small objects and low detection …

Despite promising performance achieved by deep con-volutional neural networks for non-
occluded pedestrian de-tection, it remains a great challenge to detect partially oc-cluded …

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 an important branch of computer vision, and has important
applications in the fields of autonomous driving, artificial intelligence and video surveillance …

Recent advances in pedestrian detection, a fundamental problem in computer vision, have
been attained by transferring the learned features of convolutional neural networks (CNN) to …

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

State-of-the-art pedestrian detectors have achieved significant progress on non-occluded
pedestrians, yet they are still struggling under heavy occlusions. The recent occlusion …

Occluded pedestrian detection is very challenging in computer vision, because the
pedestrians are frequently occluded by various obstacles or persons, especially in crowded …

Pedestrian detection is the use of computer vision techniques to determine whether there
are pedestrians in an image or video sequence and give their precise positioning, but the …

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 …