Open-source Monocular Python HawkEye for Tennis

Applying Deep Learning Approaches to Volleyball Data

Implementation of paper - TrackNetV3: Enhancing ShuttleCock Tracking with Augmentations and Trajectory Rectification

Tracking a table tennis ball in 3d using two cameras, and analyzing the result.

Apply computer vision to table tennis for match / training analysis

Official implementation of TrackNetV5

[KDD 2023] Ball Trajectory Inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTM

"Predicting Ball Location From Optical Tracking Data" - contains data analysis, model development and testing

Balance a ping pong ball with a Webcam and Arduino

Cricket Ball Trajectory Detection And Prediction

Tracks trajectory of a ball using OpenCV and Kalman Filters

Hawkeye official app repository. It contains the source code of the AI (developed with OpenCV) and the app itself (developed with t3-stack).

Tracking and Detection of the Soccer Ball

Python implementation of Ball tracking using OpenCV and CvBridge in ROS

Intelligent Snooker Video Analyzer turns ordinary snooker footage into professional-grade insights. It automatically detects every shot, tracks cue ball path, and generates cinematic highlights in seconds. Built for clubs, academies, and passionate players, it delivers instant real-time playback and highlights share

🔗 Bridging Modal Isolation in Interleaved Thinking: Supervising Modality Transitions via Stepwise Reinforcement

Example

Player and ball tracking map for Tennis.

Tool for multi-view camera calibration - Ball detection and tracking.

A tested control, planning, perception, bimanual, and learning platform for the Enactic OpenArm v2 (7-DOF x2) in MuJoCo: IK / Cartesian / compliant control, RRT-Connect planning, dynamic catching and throwing, articulated / cloth manipulation, language-commanded skills, a learned ACT vision policy, RL insertion, and OpenArm-Bench.