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Papers

MediaPipe Hands: On-device Real-time Hand Tracking

2020-06-18 · Fan Zhang, Valentin Bazarevsky, Andrey Vakunov, Andrei Tkachenka, George Sung, Chuo-Ling Chang, Matthias Grundmann

We present a real-time on-device hand tracking pipeline that predicts hand skeleton from single RGB camera for AR/VR applications. The pipeline consists of two models: 1) a palm detector, 2) a hand landmark model. It's implemented via MediaPipe, a framework for building cross-platform ML solutions. The proposed model and pipeline architecture demonstrates real-time inference speed on mobile GPUs and high prediction quality. MediaPipe Hands is open sourced at https://mediapipe.dev.

📄 PDF Abstract BibTeX arXiv:2006.10214

Code (4)

Matheus-Vyctor/Gesture_Hand_Controller-1
lizhu1126/CNN-for-PD-Action tf
luizhss/Gesture_Hand_Controller
vidursatija/BlazePalm pytorch

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