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Found 14 papers, 8 papers with code
TrackID3x3: A Dataset and Algorithm for Multi-Player Tracking with Identification and Pose Estimation in 3x3 Basketball Full-court Videos
In this paper, we propose the TrackID3x3 dataset, the first publicly available comprehensive dataset specifically designed for multi-player tracking, player identification, and pose estimation in 3x3 basketball scenarios.
AthletePose3D: A Benchmark Dataset for 3D Human Pose Estimation and Kinematic Validation in Athletic Movements
Human pose estimation is a critical task in computer vision and sports biomechanics, with applications spanning sports science, rehabilitation, and biomechanical research.
OpenSTARLab: Open Approach for Spatio-Temporal Agent Data Analysis in Soccer
OpenSTARLab includes the Pre-processing Package that standardizes event and tracking data through Unified and Integrated Event Data and State-Action-Reward formats, the Event Modeling Package that implements deep learning-based event prediction, alongside the RLearn Package for reinforcement learning tasks.
A Zero-Shot LLM Framework for Automatic Assignment Grading in Higher Education
Automated grading has become an essential tool in education technology due to its ability to efficiently assess large volumes of student work, provide consistent and unbiased evaluations, and deliver immediate feedback to enhance learning.
SoccerSynth-Detection: A Synthetic Dataset for Soccer Player Detection
Our work demonstrates the potential of synthetic datasets to replace real datasets for algorithm training in the field of soccer video analysis.
Enhanced Multi-Object Tracking Using Pose-based Virtual Markers in 3x3 Basketball
While pedestrian tracking has advanced with Tracking-by-Detection MOT, team sports like basketball pose unique challenges.
SoccerNet 2024 Challenges Results
The SoccerNet 2024 challenges represent the fourth annual video understanding challenges organized by the SoccerNet team.
Basketball-SORT: An Association Method for Complex Multi-object Occlusion Problems in Basketball Multi-object Tracking
Recent deep learning-based object detection approaches have led to significant progress in multi-object tracking (MOT) algorithms.
AutoSoccerPose: Automated 3D posture Analysis of Soccer Shot Movements
The dataset, code, and models are available at: https://github. com/calvinyeungck/3D-Shot-Posture-Dataset.
Generalized Holographic Reduced Representations
In this work, we introduce the GHRR framework, prove its theoretical properties and its adherence to HDC properties, explore its kernel and binding characteristics, and perform empirical experiments showcasing its flexible non-commutativity, enhanced decoding accuracy for compositional structures, and improved memorization capacity compared to FHRR.
Self-Attention Based Semantic Decomposition in Vector Symbolic Architectures
In this work, we introduce a new variant of the resonator network, based on self-attention based update rules in the iterative search problem.
Machine Learning for Soccer Match Result Prediction
The aim of this chapter is to give a broad overview of the current state and potential future developments in machine learning for soccer match results prediction, as a resource for those interested in conducting future studies in the area.
Foul prediction with estimated poses from soccer broadcast video
Recent advances in computer vision have made significant progress in tracking and pose estimation of sports players.
Evaluating Soccer Match Prediction Models: A Deep Learning Approach and Feature Optimization for Gradient-Boosted Trees
The original training set of matches and features, which was provided for the competition, was augmented with additional matches that were played between 4 April and 13 April 2023, representing the period after which the training set ended, but prior to the first matches that were to be predicted (upon which the performance was evaluated).
