Abstract Human Action Recognition (HAR) is a challenging task used in sports such as
volleyball, basketball, soccer, and tennis to detect players and recognize their actions and …

Recent developments in video analysis of sports and computer vision techniques have
achieved significant improvements to enable a variety of critical operations. To provide …

Human action recognition is an important task in computer vision. Extracting discriminative
spatial and temporal features to model the spatial and temporal evolutions of different …

Anomalous events detection in real-world video scenes is a challenging problem due to the
complexity of" anomaly" as well as the cluttered backgrounds, objects and motions in the …

Modeling relation between actors is important for recognizing group activity in a multi-person
scene. This paper aims at learning discriminative relation between actors efficiently using …

In group activity recognition, the temporal dynamics of the whole activity can be inferred
based on the dynamics of the individual people representing the activity. We build a deep …

Human motion prediction aims to generate future motions based on the observed human
motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling …

Objective assessment of an athlete's performance is of importance in elite sports to facilitate
detailed analysis. The implementation of automated detection and recognition of sport …

Group activity recognition (GAR) is a challenging task aimed at recognizing the behavior of a
group of people. It is a complex inference process in which visual cues collected from …

Graph embedding methods represent nodes in a continuous vector space, preserving
different types of relational information from the graph. There are many hyper-parameters to …