  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.
