activity
20182020
most citedSingle-Camera Basketball Tracker through Pose and Semantic Feature Fusion

7 citations · 7 across the 1 of their papers we have counts for

collaborators

7 papers

cs.CV2020

Using Player's Body-Orientation to Model Pass Feasibility in Soccer

Adrià Arbués-Sangüesa, Adrián Martín, Javier Fernández +2

Given a monocular video of a soccer match, this paper presents a computational model to estimate the most feasible pass at any given time. The method leverages offensive player's o…

cs.CV2020

Always Look on the Bright Side of the Field: Merging Pose and Contextual Data to Estimate Orientation of Soccer Players

Adrià Arbués-Sangüesa, Adrián Martín, Javier Fernández +3

Although orientation has proven to be a key skill of soccer players in order to succeed in a broad spectrum of plays, body orientation is a yet-little-explored area in sports analy…

cs.CV2019

History-based Anomaly Detector: an Adversarial Approach to Anomaly Detection

Pierrick Chatillon, Coloma Ballester

Anomaly detection is a difficult problem in many areas and has recently been subject to a lot of attention. Classifying unseen data as anomalous is a challenging matter. Latest pro…

cs.CV2019

Multi-Person tracking by multi-scale detection in Basketball scenarios

Adrià Arbués-Sangüesa, Gloria Haro, Coloma Ballester

Tracking data is a powerful tool for basketball teams in order to extract advanced semantic information and statistics that might lead to a performance boost. However, multi-person…

cs.CV20197 cited

Single-Camera Basketball Tracker through Pose and Semantic Feature Fusion

Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper pr…

cs.CV2019

ChromaGAN: Adversarial Picture Colorization with Semantic Class Distribution

Patricia Vitoria, Lara Raad, Coloma Ballester

The colorization of grayscale images is an ill-posed problem, with multiple correct solutions. In this paper, we propose an adversarial learning colorization approach coupled with…