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 …

To understand human behaviors, action recognition based on videos is a common
approach. Compared with image-based action recognition, videos provide much more …

The rapid and impromptu interest in the coupling of machine learning (ML) algorithms with
wearable and contactless sensors aimed at tackling real‐world problems warrants a …

Human Pose Estimation (HPE) has received considerable attention during the past years,
improving its performance thanks to the use of Deep Learning, and introducing new …

Imposing consistency through proxy tasks has been shown to enhance data-driven learning
and enable self-supervision in various tasks. This paper introduces novel and effective …

Automated techniques for evaluating sports activities inside dynamic frames are highly
dependent on advanced sports analysis by smart machines. The monitoring of individuals …

Understanding human behavior and activity facilitates advancement of numerous real-world
applications, and is critical for video analysis. Despite the progress of action recognition …

In video understanding, action spotting consists in temporally localizing human-induced
events annotated with single timestamps. In this paper, we propose a novel loss function that …

We present a neural network TTNet aimed at real-time processing of high-resolution table
tennis videos, providing both temporal (events spotting) and spatial (ball detection and …