Implementation of paper - TrackNetV3: Enhancing ShuttleCock Tracking with Augmentations and Trajectory Rectification
TrackNetV3 : Beyond TrackNetV2 ,and "First" TrackNet using Attention
全自动的乒乓球剪辑工具。
🔦 Pytorch implementation of TrackNet
羽毛球比赛视频智能分析 | Badminton match video analytics: TrackNet shuttle detection + YOLOv8s-pose player tracking + court homography + bullet-time FX. Runs end-to-end on Apple Silicon. 完整文档与 AI agent 任务包见 HANDOVER.md
Volleyball tracking - VballNet is a specialized deep learning framework designed for volleyball tracking, built upon the foundation of TrackNetV4. This repository includes two primary models, VballNetV1 and VballNetFastV1
Single-camera tennis analysis pipeline using YOLO and TrackNet for court, player, and ball detection with geometric reconstruction.
Shuttlecock hitting event detection and rally analysis in badminton using computer vision (TrackNet/YOLO) and machine learning (F0/F1 feature sets) for match winner prediction.
On-device tennis ball tracking: a TrackNet-style CNN in PyTorch, evaluated leakage-free and deployed to Apple Neural Engine via Core ML (52 FPS).
스마트폰 2대 기반 야구 ABS — 공 검출→2-view 삼각측량 3D 복원→KBO 2-plane Strike/Ball 판정 재현 파이프라인 (영상부터 표·그림 재생성)
Windows app for white table-tennis ball tracking and subtle trajectory rendering with TrackNetV3.
🖥️ Unify multiple GPUs into a single logical accelerator to boost compute efficiency and simplify multi-GPU execution and scheduling.
Scalable Flask API powering the Badminton AI Analyser. Orchestrates a concurrent multi-model pipeline (YOLO, StrongSORT, TrackNet, SlowFast) on Google Cloud Platform to process high-speed match footage.
An AI pipeline to detect and track the tennis ball with combination of YOLO and Tracknet architecture.
python computer-vision opencv machine-learning deep-learning yolov3 sort tracknet object-tracking ball-tracking sports-analytics video-analytics real-time tennis
Core ML port of TrackNetV3 ball tracking for Apple Silicon: converter, inference
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