Although widely used in many applications, accurate and efficient human action recognition
remains a challenging area of research in the field of computer vision. Most recent surveys …

Recognizing human activities from video sequences or still images is a challenging task due
to problems, such as background clutter, partial occlusion, changes in scale, viewpoint …

Riding on the waves of deep neural networks, deep metric learning has achieved promising
results in various tasks by using triplet network or Siamese network. Though the basic goal …

Higher dimensional data such as video and 3D are the leading edge of multimedia retrieval
and computer vision research. In this survey, we give a comprehensive overview and key …

Over the past two decades, human action recognition from video has been an important
area of research in computer vision. Its applications include surveillance systems, human …

Classification of human actions is an ongoing research problem in computer vision. This
review is aimed to scope current literature on data fusion and action recognition techniques …

This paper presents an approach for detecting suspicious events in videos by using only the
video itself as the training samples for valid behaviors. These salient events are obtained in …

In this paper, we revive the use of old-fashioned handcrafted video representations for
action recognition and put new life into these techniques via a CNN-based hallucination …

In this paper, we build on a concept of self-supervision by taking RGB frames as input to
learn to predict both action concepts and auxiliary descriptors eg, object descriptors. So …

Human action recognition in the surveillance video is currently one of the challenging
research topics. Most of the works in this area are based on either building classifiers on …