A PyTorch Toolbox for Face Recognition
Real-Time Semantic Segmentation in Mobile device
center loss for face recognition
Deep Face Recognition in PyTorch
Official repository for MixFaceNets: Extremely Efficient Face Recognition Networks
Face Recognition in real-world images [ICASSP 2017]
A PyTorch Implementation of ShuffleFaceNet.
Some handy scripts for processing face datasets
This project uses the Labeled Faces in the Wild (LFW) dataset, and the goal is to train variants of deep architectures to learn when a pair of images of faces is the same person or not. It is a pytorch implementation of Siamese network with 19 layers.
Repo for our Paper: Cross Quality LFW: A database for Analyzing Cross-Resolution Image Face Recognition in Unconstrained Environments
Low-Resolution Face Recognition Based on Identity-Preserved Face Hallucination (2019, ICIP)
This is the Python version of evaluation.m for <SphereFace: Deep Hypersphere Embedding for Face Recognition> in CVPR'17
Face recognition
Deep Siamese network for low-resolution face recognition (2021, APSIPA ASC)
Pytorch implementation of "A Better Autoencoder for Image: Convolutional Autoencoder" by Yifei Zhang
Train/validate VGGface2 dataset based on L2-constrained softmax loss.
Face recognition in PyTorch.
A coolection of tools for organizing directories, specifically converting the Labeled Faces of the Wild (cropped) to a common standard.
Add a description, image, and links to the lfw topic page so that developers can more easily learn about it.
To associate your repository with the lfw topic, visit your repo's landing page and select "manage topics."