muyouhang / Led3D

This project is an implementation for "Led3D: A Lightweight and Efficient Deep Approach to Recognizing Low-quality 3D Faces".

Led3D

This project is an implementation for "Led3D: An lightweight and efficent deep approach to recognizing low-quality 3d faces" [ Download ], which is accepted by CVPR2019.

Dataset: Lock3DFace

Lable: Lock3DFace Label File

Function

• 3D Face Preprocessing (Done.)
• 3D Face Augmentation (Done.)
• Python Inference Code (Done.)

Citation

@InProceedings{Mu_2019_CVPR,
author = {Mu, Guodong and Huang, Di and Hu, Guosheng and Sun, Jia and Wang, Yunhong},
title = {Led3D: A Lightweight and Efficient Deep Approach to Recognizing Low-Quality 3D Faces},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}