Deep Siamese network for low-resolution face recognition (2021, APSIPA ASC)
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Updated
Apr 19, 2024 - Python
Deep Siamese network for low-resolution face recognition (2021, APSIPA ASC)
A PyTorch Toolbox for Face Recognition
Low-Resolution Face Recognition Based on Identity-Preserved Face Hallucination (2019, ICIP)
Pytorch implementation of "A Better Autoencoder for Image: Convolutional Autoencoder" by Yifei Zhang
Real-Time Semantic Segmentation in Mobile device
Repo for our Paper: Cross Quality LFW: A database for Analyzing Cross-Resolution Image Face Recognition in Unconstrained Environments
A PyTorch Implementation of ShuffleFaceNet.
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…
Official repository for MixFaceNets: Extremely Efficient Face Recognition Networks
center loss for face recognition
Train/validate VGGface2 dataset based on L2-constrained softmax loss.
Face recognition
Some handy scripts for processing face datasets
Deep Face Recognition in PyTorch
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.
This is the Python version of evaluation.m for <SphereFace: Deep Hypersphere Embedding for Face Recognition> in CVPR'17
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."