Face Identification
41 papers with code • 4 benchmarks • 5 datasets
Face identification is the task of matching a given face image to one in an existing database of faces. It is the second part of face recognition (the first part being detection). It is a one-to-many mapping: you have to find an unknown person in a database to find who that person is.
Benchmarks
These leaderboards are used to track progress in Face Identification
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Libraries
Use these libraries to find Face Identification models and implementations
MS-Celeb-1M
MegaFace
IJB-A
IJB-B
LTFT
Latest papers
Editable Neural Networks
eric-mitchell/mend
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ICLR 2020
We empirically demonstrate the effectiveness of this method on large-scale image classification and machine translation tasks.
MarginDistillation: distillation for margin-based softmax
david-svitov/margindistillation
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The usage of convolutional neural networks (CNNs) in conjunction with a margin-based softmax approach demonstrates a state-of-the-art performance for the face recognition problem.
FCSR-GAN: Joint Face Completion and Super-resolution via Multi-task Learning
Combined variations containing low-resolution and occlusion often present in face images in the wild, e. g., under the scenario of video surveillance.
VarGFaceNet: An Efficient Variable Group Convolutional Neural Network for Lightweight Face Recognition
To improve the discriminative and generalization ability of lightweight network for face recognition, we propose an efficient variable group convolutional network called VarGFaceNet.
A Supervised Learning Methodology for Real-Time Disguised Face Recognition in the Wild
The modern day scenario, where security is of prime concern, regular face identification techniques do not perform as required when the faces are disguised, which calls for a different approach to handle situations where intruders have their faces masked.
Git Loss for Deep Face Recognition
kjanjua26/Git-Loss-For-Deep-Face-Recognition
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Conventionally, CNNs have been trained with softmax as supervision signal to penalize the classification loss.
Pose-Robust Face Recognition via Deep Residual Equivariant Mapping
penincillin/DREAM
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CVPR 2018
However, many contemporary face recognition models still perform relatively poor in processing profile faces compared to frontal faces.
CosFace: Large Margin Cosine Loss for Deep Face Recognition
PaddlePaddle/PaddleClas
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CVPR 2018
The central task of face recognition, including face verification and identification, involves face feature discrimination.
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
deepinsight/insightface
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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.
Group-level Emotion Recognition using Transfer Learning from Face Identification
In this paper, we describe our algorithmic approach, which was used for submissions in the fifth Emotion Recognition in the Wild (EmotiW 2017) group-level emotion recognition sub-challenge.
