activity
20182026
most citedSoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videos

133 citations · 533 across the 40 of their papers we have counts for

collaborators
Showing 2024 · cs.CVShow all

13 papers · 2 filters

cs.CV2024★ 1 cited

The Tile: A 2D Map of Ranking Scores for Two-Class Classification

Sébastien Piérard, Anaïs Halin, Anthony Cioppa +2

In the computer vision and machine learning communities, as well as in many other research domains, rigorous evaluation of any new method, including classifiers, is essential. One…

cs.CV2024★ 1 cited

A Hitchhiker's Guide to Understanding Performances of Two-Class Classifiers

Anaïs Halin, Sébastien Piérard, Anthony Cioppa +1

Properly understanding the performances of classifiers is essential in various scenarios. However, the literature often relies only on one or two standard scores to compare classif…

cs.CV2024★ 1 cited

Physically Interpretable Probabilistic Domain Characterization

Anaïs Halin, Sébastien Piérard, Renaud Vandeghen +10

Characterizing domains is essential for models analyzing dynamic environments, as it allows them to adapt to evolving conditions or to hand the task over to backup systems when fac…

cs.CV2024

3D Convex Splatting: Radiance Field Rendering with 3D Smooth Convexes

Jan Held, Renaud Vandeghen, Abdullah Hamdi +6

Recent advances in radiance field reconstruction, such as 3D Gaussian Splatting (3DGS), have achieved high-quality novel view synthesis and fast rendering by representing scenes wi…

cs.CV2024★ 4 cited

Deep learning for action spotting in association football videos

Silvio Giancola, Anthony Cioppa, Bernard Ghanem +1

The task of action spotting consists in both identifying actions and precisely localizing them in time with a single timestamp in long, untrimmed video streams. Automatically extra…

cs.CV2024★ 1 cited

SoccerNet 2024 Challenges Results

Anthony Cioppa, Silvio Giancola, Vladimir Somers +81

The SoccerNet 2024 challenges represent the fourth annual video understanding challenges organized by the SoccerNet team. These challenges aim to advance research across multiple t…

cs.CV2024★ 2 cited

Towards AI-Powered Video Assistant Referee System (VARS) for Association Football

Jan Held, Anthony Cioppa, Silvio Giancola +4

Over the past decade, the technology used by referees in football has improved substantially, enhancing the fairness and accuracy of decisions. This progress has culminated in the…

cs.CV2024

Investigating Event-Based Cameras for Video Frame Interpolation in Sports

Antoine Deckyvere, Anthony Cioppa, Silvio Giancola +2

Slow-motion replays provide a thrilling perspective on pivotal moments within sports games, offering a fresh and captivating visual experience. However, capturing slow-motion foota…

cs.CV2024

OSL-ActionSpotting: A Unified Library for Action Spotting in Sports Videos

Yassine Benzakour, Bruno Cabado, Silvio Giancola +3

Action spotting is crucial in sports analytics as it enables the precise identification and categorization of pivotal moments in sports matches, providing insights that are essenti…

cs.CV2024★ 6 cited

Multi-Stream Cellular Test-Time Adaptation of Real-Time Models Evolving in Dynamic Environments

Benoît Gérin, Anaïs Halin, Anthony Cioppa +5

In the era of the Internet of Things (IoT), objects connect through a dynamic network, empowered by technologies like 5G, enabling real-time data sharing. However, smart objects, n…

cs.CV2024★ 2 cited

SoccerNet Game State Reconstruction: End-to-End Athlete Tracking and Identification on a Minimap

Vladimir Somers, Victor Joos, Anthony Cioppa +11

Tracking and identifying athletes on the pitch holds a central role in collecting essential insights from the game, such as estimating the total distance covered by players or unde…

cs.CV2024★ 28 cited

X-VARS: Introducing Explainability in Football Refereeing with Multi-Modal Large Language Model

Jan Held, Hani Itani, Anthony Cioppa +3

The rapid advancement of artificial intelligence has led to significant improvements in automated decision-making. However, the increased performance of models often comes at the c…

cs.CV2024★ 7 cited

Efficient Image Pre-Training with Siamese Cropped Masked Autoencoders

Alexandre Eymaël, Renaud Vandeghen, Anthony Cioppa +3

Self-supervised pre-training of image encoders is omnipresent in the literature, particularly following the introduction of Masked autoencoders (MAE). Current efforts attempt to le…