MediaPipe Hands: On-device Real-time Hand Tracking

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

Datasets


Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods