Sports Analytics
24 papers with code • 0 benchmarks • 2 datasets
Benchmarks
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Libraries
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Most implemented papers
Sports Camera Calibration via Synthetic Data
Here we propose a highly automatic method for calibrating sports cameras from a single image using synthetic data.
ShuttleSet: A Human-Annotated Stroke-Level Singles Dataset for Badminton Tactical Analysis
With the recent progress in sports analytics, deep learning approaches have demonstrated the effectiveness of mining insights into players' tactics for improving performance quality and fan engagement.
Applying Deep Learning to Basketball Trajectories
Using a dataset of over 20, 000 three pointers from NBA SportVu data, the models based simply on sequential positional data outperform a static feature rich machine learning model in predicting whether a three-point shot is successful.
Cracking the Black Box: Distilling Deep Sports Analytics
This paper addresses the trade-off between Accuracy and Transparency for deep learning applied to sports analytics.
From Motor Control to Team Play in Simulated Humanoid Football
In a sequence of stages, players first learn to control a fully articulated body to perform realistic, human-like movements such as running and turning; they then acquire mid-level football skills such as dribbling and shooting; finally, they develop awareness of others and play as a team, bridging the gap between low-level motor control at a timescale of milliseconds, and coordinated goal-directed behaviour as a team at the timescale of tens of seconds.
Unsupervised Learning of Neurosymbolic Encoders
We present a framework for the unsupervised learning of neurosymbolic encoders, which are encoders obtained by composing neural networks with symbolic programs from a domain-specific language.
DeepSportLab: a Unified Framework for Ball Detection, Player Instance Segmentation and Pose Estimation in Team Sports Scenes
In addition to the increased complexity resulting from the multiplication of single-task models, the use of the off-the-shelf models also impedes the performance due to the complexity and specificity of the team sports scenes, such as strong occlusion and motion blur.
LTC-GIF: Attracting More Clicks on Feature-length Sports Videos
This paper proposes a lightweight method to attract users and increase views of the video by presenting personalized artistic media -- i. e, static thumbnails and animated GIFs.
SkeleVision: Towards Adversarial Resiliency of Person Tracking with Multi-Task Learning
Person tracking using computer vision techniques has wide ranging applications such as autonomous driving, home security and sports analytics.
A Survey on Video Action Recognition in Sports: Datasets, Methods and Applications
Finally, we discuss the challenges and unsolved problems in this area and to facilitate sports analytics, we develop a toolbox using PaddlePaddle, which supports football, basketball, table tennis and figure skating action recognition.