With growing numbers of intelligent autonomous systems in human environments, the ability
of such systems to perceive, understand, and anticipate human behavior becomes …

Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …

State-of-the-art computer vision systems are trained to predict a fixed set of predetermined
object categories. This restricted form of supervision limits their generality and usability since …

Over the years, datasets and benchmarks have proven their fundamental importance in
computer vision research, enabling targeted progress and objective comparisons in many …

Computer vision has a great potential to help our daily lives by searching for lost keys,
watering flowers or reminding us to take a pill. To succeed with such tasks, computer vision …

Predicting the future trajectories of multiple interacting pedestrians in a scene has become
an increasingly important problem for many different applications ranging from control of …

The main challenge of Multi-Object Tracking (MOT) lies in maintaining a continuous
trajectory for each target. Existing methods often learn reliable motion patterns to match the …

Recent works have shown that convolutional networks have substantially improved the
performance of multiple object tracking by simultaneously learning detection and …

Deep learning-based object detection solutions emerged from computer vision has
captivated full attention in recent years. The growing UAV market trends and interest in …

Deciphering human behaviors to predict their future paths/trajectories and what they would
do from videos is important in many applications. Motivated by this idea, this paper studies …