5 citations · 16 across the 15 of their papers we have counts for
17 papers
AI Soccer Analyst: Stage-Aware and Verifiable Human-AI Collaboration for Soccer Data Analysis
Calvin Yeung, Keisuke Fujii
Sports data analysts translate domain questions into insights by combining computation with sport-specific domain expertise. Large language models ease programming, but prompt-to-r…
Right Move, Right Time: Multi-Sport Space Evaluation Platform for Ultimate Frisbee, Basketball, and Soccer
Shunsuke Iwashita, Titouan Jeannot, Braden Eberhard +4
We present an open, sport-agnostic platform that turns tracking into comparable spatial measures across professional Ultimate, basketball, and soccer. Coaches in all three sports a…
KASportsFormer: Kinematic Anatomy Enhanced Transformer for 3D Human Pose Estimation on Short Sports Scene Video
Zhuoer Yin, Calvin Yeung, Tomohiro Suzuki +2
Recent transformer based approaches have demonstrated impressive performance in solving real-world 3D human pose estimation problems. Albeit these approaches achieve fruitful resul…
AthleticsPose: Authentic Sports Motion Dataset on Athletic Field and Evaluation of Monocular 3D Pose Estimation Ability
Tomohiro Suzuki, Ryota Tanaka, Calvin Yeung +1
Monocular 3D pose estimation is a promising, flexible alternative to costly motion capture systems for sports analysis. However, its practical application is hindered by two factor…
TrackID3x3: A Dataset and Algorithm for Multi-Player Tracking with Identification and Pose Estimation in 3x3 Basketball Full-court Videos
Kazuhiro Yamada, Li Yin, Qingrui Hu +6
Multi-object tracking, player identification, and pose estimation are fundamental components of sports analytics, essential for analyzing player movements, performance, and tactica…
AthletePose3D: A Benchmark Dataset for 3D Human Pose Estimation and Kinematic Validation in Athletic Movements
Calvin Yeung, Tomohiro Suzuki, Ryota Tanaka +2
Human pose estimation is a critical task in computer vision and sports biomechanics, with applications spanning sports science, rehabilitation, and biomechanical research. While si…
OpenSTARLab: Open Approach for Spatio-Temporal Agent Data Analysis in Soccer
Calvin Yeung, Kenjiro Ide, Taiga Someya +1
Sports analytics has become both more professional and sophisticated, driven by the growing availability of detailed performance data. This progress enables applications such as ma…
A Zero-Shot LLM Framework for Automatic Assignment Grading in Higher Education
Calvin Yeung, Jeff Yu, King Chau Cheung +4
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 evalu…
SoccerSynth-Detection: A Synthetic Dataset for Soccer Player Detection
Haobin Qin, Calvin Yeung, Rikuhei Umemoto +1
In soccer video analysis, player detection is essential for identifying key events and reconstructing tactical positions. The presence of numerous players and frequent occlusions,…
Enhanced Multi-Object Tracking Using Pose-based Virtual Markers in 3x3 Basketball
Li Yin, Calvin Yeung, Qingrui Hu +4
Multi-object tracking (MOT) is crucial for various multi-agent analyses such as evaluating team sports tactics and player movements and performance. While pedestrian tracking has a…
Basketball-SORT: An Association Method for Complex Multi-object Occlusion Problems in Basketball Multi-object Tracking
Qingrui Hu, Atom Scott, Calvin Yeung +1
Recent deep learning-based object detection approaches have led to significant progress in multi-object tracking (MOT) algorithms. The current MOT methods mainly focus on pedestria…
AutoSoccerPose: Automated 3D posture Analysis of Soccer Shot Movements
Calvin Yeung, Kenjiro Ide, Keisuke Fujii
Image understanding is a foundational task in computer vision, with recent applications emerging in soccer posture analysis. However, existing publicly available datasets lack comp…
Machine Learning for Soccer Match Result Prediction
Rory Bunker, Calvin Yeung, Keisuke Fujii
Machine learning has become a common approach to predicting the outcomes of soccer matches, and the body of literature in this domain has grown substantially in the past decade and…
Foul prediction with estimated poses from soccer broadcast video
Jiale Fang, Calvin Yeung, Keisuke Fujii
Recent advances in computer vision have made significant progress in tracking and pose estimation of sports players. However, there have been fewer studies on behavior prediction w…
Evaluating Soccer Match Prediction Models: A Deep Learning Approach and Feature Optimization for Gradient-Boosted Trees
Calvin Yeung, Rory Bunker, Rikuhei Umemoto +1
Machine learning models have become increasingly popular for predicting the results of soccer matches, however, the lack of publicly-available benchmark datasets has made model eva…
A Strategic Framework for Optimal Decisions in Football 1-vs-1 Shot-Taking Situations: An Integrated Approach of Machine Learning, Theory-Based Modeling, and Game Theory
Calvin C. K. Yeung, Keisuke Fujii
Complex interactions between two opposing agents frequently occur in domains of machine learning, game theory, and other application domains. Quantitatively analyzing the strategie…
Transformer-Based Neural Marked Spatio Temporal Point Process Model for Football Match Events Analysis
Calvin C. K. Yeung, Tony Sit, Keisuke Fujii
With recently available football match event data that record the details of football matches, analysts and researchers have a great opportunity to develop new performance metrics,…