Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network

ECCV 2018 Yao FengFan WuXiaohu ShaoYanfeng WangXi Zhou

We propose a straightforward method that simultaneously reconstructs the 3D facial structure and provides dense alignment. To achieve this, we design a 2D representation called UV position map which records the 3D shape of a complete face in UV space, then train a simple Convolutional Neural Network to regress it from a single 2D image... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Face Alignment AFLW2000-3D PRN Mean NME 3.62% # 2
3D Face Reconstruction AFLW2000-3D PRN Mean NME 3.9625% # 1
Face Alignment AFLW-LFPA FPN Mean NME 2.93% # 1
3D Face Reconstruction Florence PRN Mean NME 3.7551% # 1