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Showing 26–50 of 97 papers

TitleStatusHype
Expected Possession Value of Control and Duel Actions for Soccer Player's Skills Estimation—0
FACTS: Fine-Grained Action Classification for Tactical Sports—0
FinePseudo: Improving Pseudo-Labelling through Temporal-Alignablity for Semi-Supervised Fine-Grained Action Recognition—0
Who You Play Affects How You Play: Predicting Sports Performance Using Graph Attention Networks With Temporal Convolution—0
Action Spotting and Precise Event Detection in Sports: Datasets, Methods, and Challenges—0
Action Valuation in Sports: A Survey—0
Adaptive Feature Processing for Robust Human Activity Recognition on a Novel Multi-Modal Dataset—0
A Framework for Spatio-Temporal Graph Analytics In Field Sports—0
A Hybrid Graph Network for Complex Activity Detection in Video—0
Always Look on the Bright Side of the Field: Merging Pose and Contextual Data to Estimate Orientation of Soccer Players—0
A Multi-stage deep architecture for summary generation of soccer videos—0
Analysing Long Short Term Memory Models for Cricket Match Outcome Prediction—0
A Survey on the application of Data Science And Analytics in the field of Organised Sports—0
A Universal Protocol to Benchmark Camera Calibration for Sports—0
Bayesian taut splines for estimating the number of modes—0
Bump hunting through density curvature features—0
Multi-Stage Generative Upscaler: Reconstructing Football Broadcast Images via Diffusion Models—0
On-field player workload exposure and knee injury risk monitoring via deep learning—0
OSL-ActionSpotting: A Unified Library for Action Spotting in Sports Videos—0
PassNet: Learning pass probability surfaces from single-location labels. An architecture for visually-interpretable soccer analytics—0
PLayerTV: Advanced Player Tracking and Identification for Automatic Soccer Highlight Clips—0
Pose2Trajectory: Using Transformers on Body Pose to Predict Tennis Player's Trajectory—0
Predicting Team Performance with Spatial Temporal Graph Convolutional Networks—0
Presenting Multiagent Challenges in Team Sports Analytics—0
Random forest model identifies serve strength as a key predictor of tennis match outcome—0
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