Robotic mapping provides spatial information for autonomous agents. Depending on the
tasks they seek to enable, the maps created range from simple 2D representations of the …

Gathering a large number of people in a shared physical area is very common in urban
culture. Although there are limitless examples of mega crowds, the Islamic religious ritual …

This paper introduces a video representation based on dense trajectories and motion
boundary descriptors. Trajectories capture the local motion information of the video. A dense …

We present a novel end-to-end partially supervised deep learning approach for video
anomaly detection and localization using only normal samples. The insight that motivates …

Anomaly detection in surveillance videos has been recently gaining attention. A challenging
aspect of high-dimensional applications such as video surveillance is continual learning …

Anomaly detection in surveillance videos is attracting an increasing amount of attention.
Despite the competitive performance of recent methods, they lack theoretical performance …

Abnormal event detection in video surveillance is extremely important, especially for
crowded scenes. In recent years, many algorithms have been proposed based on hand …

How to learn discriminative video representation from unlabeled videos is challenging but
crucial for video analysis. The latest attempts seek to learn a representation model by …

Abnormal behavior detection in crowd scenes is continuously a challenge in the field of
computer vision. For tackling this problem, this paper starts from a novel structure modeling …

Classification of data is difficult if the data is imbalanced and classes are overlapping. In
recent years, more research has started to focus on classification of imbalanced data since …