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Towards Fast, Accurate and Stable 3D Dense Face Alignment

Jianzhu Guo, Xiangyu Zhu, Yang Yang, Zhen Lei, Yang Fan, Stan Z. Li

ECCV 2020

arxiv / paper / supp / video1 / video2 / code /

We propose a novel regression framework, named 3DDFA_V2, to make a balance among speed, accuracy and stability. Our model runs at over 50fps on a single CPU core (>200fps with ONNX acceleration) and outperforms other state-of-the-art heavy models simultaneously. Code and models are available at https://github.com/cleardusk/3DDFA_V2.