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With the recent development of Deep Learning applied to Computer Vision, sport video understanding has gained a lot of attention, providing much richer information for both sport consumers and leagues. This paper introduces DeepSportradar-v1, a suite of ...

Sports analytics has been an up-and-coming field of research among professional sporting organizations and academic institutions alike. With the insurgence and collection of athlete data, the primary goal of such analysis is to improve athletes' ...

Timely detection of runner exertion is crucial for preventing overuse injuries and conditioning training. Similarly, maintaining high levels of wellbeing while running can improve retention rates for onboarders to the sport, with the associated benefits ...

Video-based analysis of cycling races can provide a lot of information that can be used to keep cycling interesting for the fans and improve cyclists' safety. In this paper, we propose a solution to collect and process the metadata of cycling races. The ...

Data analysis in sports is becoming increasingly important, and one of the sports in which sports analysts play an active role is volleyball. Volleyball analysts have the task of annotating match videos, a time-consuming and technically challenging task ...

This paper introduces BadmintonDB, a new badminton dataset for training models for player-specific match analysis and prediction tasks, which are interesting challenges. The dataset features rally, strokes, and outcome annotations of 9 real-world ...

Due to the increasing capabilities of computer vision methods, it is now possible to apply them even to the most difficult scenarios, such as for vision-based analysis of a jiu-jitsu match. One of the biggest challenges of such scenarios are heavily ...

Much of modern sports analytics is based on player and ball tracking data. Such data are mostly collected using wearable devices or an array of carefully located cameras and detectors. Many teams do not have such a luxury, especially in undervalued ...

The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team. In 2022, the challenges were composed of 6 vision-based tasks: (1) action spotting, focusing on retrieving action timestamps in long ...

The task of spotting events in videos has gained high attention recently, as it helps in better video understanding, and it is a key step in automating the highlights generation. In this work, we tackle the problem of action spotting in soccer videos by ...

Action spotting in soccer videos is the task of identifying the specific time when a certain key action of the game occurs. Lately, it has received a large amount of attention and powerful methods have been introduced. Action spotting involves ...

Action Spotting in the broadcast soccer game is important to understand salient actions and video summary applications. In this paper, we propose an efficient transformer-based system for action spotting in soccer videos. We first use the multi-scale ...

Tracking the players and the ball in team sports is key to analyse the performance or to enhance the game watching experience with augmented reality. When the only sources for this data are broadcast videos, sports-field registration systems are ...

Instance segmentation is applied widely in image editing, image analysis and autonomous driving, etc. However, insufficient data and occlusion are common problems in practical application. DeepSportRadar Instance Segmentation challenge has focused on ...

Person re-identification (Re-ID) aims to re-identify people across multiple video frames captured at various time instants. With the advancement of deep neural networks and increasing demand of intelligent video surveillance, recent works have proposed ...

Sports analytics benefits from recent advances in machine learning providing a competitive advantage for teams or individuals. One important task in this context is the performance measurement of individual players to provide reports and log files for ...

With the development of deep learning technologies, the performance of person re-identification (ReID) has been greatly improved. However, as a subdomain of person ReID, the research for player ReID is important for the sports field yet lacks sufficient ...