Pedestrian detection is a key problem in computer vision, with several applications that have
the potential to positively impact quality of life. In recent years, the number of approaches to …

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 …

Effective multi-object tracking (MOT) methods have been developed in recent years for a
wide range of applications including visual surveillance and behavior understanding …

Big data has had a great share in the success of deep learning in computer vision. Recent
works suggest that there is significant further potential to increase object detection …

Pedestrian detection has achieved significant progress with the availability of existing
benchmark datasets. However, there is a gap in the diversity and density between real world …

For autonomous driving, perception is a primary and essential element that fundamentally
deals with the insight into the ego vehicle's environment through sensors. Perception is …

In this work we propose a new architecture for person re-identification. As the task of re-
identification is inherently associated with embedding learning and non-rigid appearance …

Pedestrian detection in crowded scenes is a challenging problem, because occlusion
happens frequently among different pedestrians. In this paper, we propose an effective and …

In many surveillance systems there is a requirement to determine whether a given person of
interest has already been observed over a network of cameras. This is the person re …

In many surveillance systems there is a requirement to determine whether a given person of
interest has already been observed over a network of cameras. This paper presents two …