Face Verification

39 papers with code · Computer Vision

Face verification is the task of comparing a candidate face to another, and verifying whether it is a match. It is a one-to-one mapping: you have to check if this person is the correct one.

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

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Greatest papers with code

FaceNet: A Unified Embedding for Face Recognition and Clustering

CVPR 2015 davidsandberg/facenet

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

FACE IDENTIFICATION FACE RECOGNITION FACE VERIFICATION

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

CVPR 2019 deepinsight/insightface

One of the main challenges in feature learning using Deep Convolutional Neural Networks (DCNNs) for large-scale face recognition is the design of appropriate loss functions that enhance discriminative power.

FACE IDENTIFICATION FACE RECOGNITION FACE VERIFICATION

Classification is a Strong Baseline for Deep Metric Learning

30 Nov 2018microsoft/computervision-recipes

Deep metric learning aims to learn a function mapping image pixels to embedding feature vectors that model the similarity between images.

CONTENT-BASED IMAGE RETRIEVAL FACE VERIFICATION METRIC LEARNING

SphereFace: Deep Hypersphere Embedding for Face Recognition

CVPR 2017 wy1iu/sphereface

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.

FACE IDENTIFICATION FACE RECOGNITION FACE VERIFICATION

A Light CNN for Deep Face Representation with Noisy Labels

9 Nov 2015AlfredXiangWu/face_verification_experiment

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

FACE IDENTIFICATION FACE RECOGNITION FACE VERIFICATION FEATURE SELECTION

SeesawFaceNets: sparse and robust face verification model for mobile platform

arXiv 2019 didi/AoE

Therefore, designing lightweight networks with low memory requirement and computational cost is one of the most practical solutions for face verification on mobile platform.

FACE RECOGNITION FACE VERIFICATION

FacePoseNet: Making a Case for Landmark-Free Face Alignment

24 Aug 2017fengju514/Face-Pose-Net

Instead, we compare our FPN with existing methods by evaluating how they affect face recognition accuracy on the IJB-A and IJB-B benchmarks: using the same recognition pipeline, but varying the face alignment method.

FACE ALIGNMENT FACE IDENTIFICATION FACE RECOGNITION FACE VERIFICATION FACIAL LANDMARK DETECTION