Face Verification

119 papers with code • 21 benchmarks • 22 datasets

Face Verification is a machine learning task in computer vision that involves determining whether two facial images belong to the same person or not. The task involves extracting features from the facial images, such as the shape and texture of the face, and then using these features to compare and verify the similarity between the images.

( Image credit: Pose-Robust Face Recognition via Deep Residual Equivariant Mapping )


Use these libraries to find Face Verification models and implementations

Most implemented papers

FaceNet: A Unified Embedding for Face Recognition and Clustering

davidsandberg/facenet CVPR 2015

On the widely used Labeled Faces in the Wild (LFW) dataset, our system achieves a new record accuracy of 99. 63%.

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

deepinsight/insightface CVPR 2019

Recently, a popular line of research in face recognition is adopting margins in the well-established softmax loss function to maximize class separability.

VGGFace2: A dataset for recognising faces across pose and age

deepinsight/insightface 23 Oct 2017

The dataset was collected with three goals in mind: (i) to have both a large number of identities and also a large number of images for each identity; (ii) to cover a large range of pose, age and ethnicity; and (iii) to minimize the label noise.

SphereFace: Deep Hypersphere Embedding for Face Recognition

wy1iu/sphereface CVPR 2017

This paper addresses deep face recognition (FR) problem under open-set protocol, where ideal face features are expected to have smaller maximal intra-class distance than minimal inter-class distance under a suitably chosen metric space.

A Light CNN for Deep Face Representation with Noisy Labels

AlfredXiangWu/face_verification_experiment 9 Nov 2015

This paper presents a Light CNN framework to learn a compact embedding on the large-scale face data with massive noisy labels.

Circle Loss: A Unified Perspective of Pair Similarity Optimization

layumi/Person_reID_baseline_pytorch CVPR 2020

This paper provides a pair similarity optimization viewpoint on deep feature learning, aiming to maximize the within-class similarity $s_p$ and minimize the between-class similarity $s_n$.

Additive Margin Softmax for Face Verification

happynear/AMSoftmax 17 Jan 2018

In this work, we introduce a novel additive angular margin for the Softmax loss, which is intuitively appealing and more interpretable than the existing works.

CosFace: Large Margin Cosine Loss for Deep Face Recognition

PaddlePaddle/PaddleClas CVPR 2018

The central task of face recognition, including face verification and identification, involves face feature discrimination.