Object detection and tracking is one of the most important and challenging branches in
computer vision, and have been widely applied in various fields, such as health-care …

When overpopulated cities face frequent crowded events like strikes, demonstrations,
parades or other sorts of people gatherings, they are confronted to multiple security issues …

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 …

In this paper, we address the problem of forest fires' early detection and segmentation in
order to predict their spread and help with fire fighting. Techniques based on Convolutional …

Pedestrian detection is widely applied in surveillance, autonomous robotic navigation, and
automotive safety. However, there are many occlusion problems in real life. This paper …

Pedestrian detection is a challenging and hot research topic in the field of computer vision,
especially for the crowded scenes where occlusion happens frequently. In this paper, we …

Autonomous Vehicles (AVs) have the potential to solve many traffic problems, such as
accidents, congestion and pollution. However, there are still challenges to overcome, for …

The significant power of deep learning networks has led to enormous development in object
detection. Over the last few years, object detector frameworks have achieved tremendous …

Images of heavily occluded objects in cluttered scenes, such as fruit clusters in trees, are
hard to segment. To further retrieve the 3D size and 6D pose of each individual object in …

Multiview detection incorporates multiple camera views to deal with occlusions, and its
central problem is multiview aggregation. Given feature map projections from multiple views …