Attention Mesh: High-fidelity Face Mesh Prediction in Real-time

2020-06-19 · Ivan Grishchenko, Artsiom Ablavatski, Yury Kartynnik, Karthik Raveendran, Matthias Grundmann

We present Attention Mesh, a lightweight architecture for 3D face mesh prediction that uses attention to semantically meaningful regions. Our neural network is designed for real-time on-device inference and runs at over 50 FPS on a Pixel 2 phone. Our solution enables applications like AR makeup, eye tracking and AR puppeteering that rely on highly accurate landmarks for eye and lips regions. Our main contribution is a unified network architecture that achieves the same accuracy on facial landmarks as a multi-stage cascaded approach, while being 30 percent faster.

📄 PDF Abstract BibTeX arXiv:2006.10962

Code (1)

google/mediapipe 공식 구현 tf

Tasks

Vocal Bursts Intensity Prediction

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