Sports involve commonly players and equipment of high dynamics. Their location and
motion data are essential for sports digitalization-related applications, such as from …

Standardized benchmarks are crucial for the majority of computer vision applications.
Although leaderboards and ranking tables should not be over-claimed, benchmarks often …

This paper revisits the classical multiple hypotheses tracking (MHT) algorithm in a tracking-
by-detection framework. The success of MHT largely depends on the ability to maintain a …

In the recent past, the computer vision community has developed centralized benchmarks
for the performance evaluation of a variety of tasks, including generic object and pedestrian …

Sports data analysis is becoming increasingly large scale, diversified, and shared, but
difficulty persists in rapidly accessing the most crucial information. Previous surveys have …

The rapid progress in artificial intelligence (AI) and machine learning has opened
unprecedented analytics possibilities in various team and individual sports, including …

Group activity recognition plays a fundamental role in a variety of applications, eg sports
video analysis and intelligent surveillance. How to model the spatio-temporal contextual …

Identity switches caused by inter-object interactions remain a critical problem for multi-player
tracking in real-world sports video analysis. Existing approaches utilizing the appearance …

The task of tracking multiple targets is often addressed with the so-called tracking-by-
detection paradigm, where the first step is to obtain a set of target hypotheses for each frame …

In real life, group activity recognition plays a significant and fundamental role in a variety of
applications, eg sports video analysis, abnormal behavior detection, and intelligent …