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.
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.
Some handy scripts for processing face datasets
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.
An image recognition process contained in the LFW database http://vis-www.cs.umass.edu/lfw/#download is carried out with extreme simplicity, taking advantage of the ease of sklearn to implement the SVM model. Cascading face recognition is also used to refine the images, obtaining accuracy greater than 70% in the test with images that do not appe…
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