Few-shot action recognition has attracted increasing attention in recent years, but it remains
challenging due to the intrinsic difficulty in learning transferable knowledge to generalize to …

Single-stage detectors have gained great attention due to their high detection accuracy and
real-time speed. To detect multi-scale objects, single-stage detectors make scale-aware …

Humans are able to simultaneously identify a person and recognize his or her action based
on biological motions. Previous work usually treats action recognition and person …

Making human poses serve high-level computer vision tasks such as action recognition,
recognizing the quality of estimated poses is of critical importance. Conventionally, the mean …

In the recent past, human action recognition is inviting increased attention in the automated
video surveillance systems. An efficient human action classification technique in an …

In the research field of few-shot learning, the main difference between image-based and
video-based is the additional temporal dimension. In recent years, some works have used …

Transfer learning aims to learn an effective classifier for unlabeled target data by borrowing
knowledge from well-labeled source data. However, most existing work has emphasized on …

The aim of this study is to improve the classification efficiency of advanced methods using a
multilayered dictionary learning framework. This paper presents the new idea of …

Detecting human fight behavior from videos is important in social signal processing,
especially in the context of surveillance. However, the uncommon occurrence of real human …

Recent studies have shown that video action recognition models are also vulnerable to
fooling by adversarial samples. However, currently existing video attack methods usually …