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
CamPro: Camera-based Anti-Facial Recognition
The proliferation of images captured from millions of cameras and the advancement of facial recognition (FR) technology have made the abuse of FR a severe privacy threat.
Fast and Interpretable Face Identification for Out-Of-Distribution Data Using Vision Transformers
DeepFace-EMD (Phan et al. 2022) reaches state-of-the-art accuracy on out-of-distribution data by first comparing two images at the image level, and then at the patch level.
Learning Unified Representations for Multi-Resolution Face Recognition
As per the input, a resolution-specific BNet is used and the output are implanted as feature maps in the feature pyramid of TNet, at a layer with the same resolution.
GhostFaceNets: Lightweight Face Recognition Model From Cheap Operations
serengil/deepface
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IEEE Access 2023
The development of deep learning-based biometric models that can be deployed on devices with constrained memory and computational resources has proven to be a significant challenge.
Open-Set Face Identification on Few-Shot Gallery by Fine-Tuning
1ho0jin1/osfi-by-finetuning
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In this paper, we focus on addressing the open-set face identification problem on a few-shot gallery by fine-tuning.
LAD-RCNN:A Powerful Tool for Livestock Face Detection and Normalization
SheepBreedingLab-HZAU/LAD-RCNN
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However, there is no study on normalizing of the animal face image with arbitrary directions.
Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition
Our search outputs a suite of models which Pareto-dominate all other high-performance architectures and existing bias mitigation methods in terms of accuracy and fairness, often by large margins, on the two most widely used datasets for face identification, CelebA and VGGFace2.
Classifying emotions and engagement in online learning based on a single facial expression recognition neural network
HSE-asavchenko/face-emotion-recognition
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IEEE Transactions on Affective Computing 2022
It is shown that the resulting facial features can be used for fast simultaneous prediction of students’ engagement levels (from disengaged to highly engaged), individual emotions (happy, sad, etc.,) and group-level affect (positive, neutral or negative).
Unified Negative Pair Generation toward Well-discriminative Feature Space for Face Recognition
The goal of face recognition (FR) can be viewed as a pair similarity optimization problem, maximizing a similarity set $\mathcal{S}^p$ over positive pairs, while minimizing similarity set $\mathcal{S}^n$ over negative pairs.
DeepFace-EMD: Re-ranking Using Patch-wise Earth Mover's Distance Improves Out-Of-Distribution Face Identification
anguyen8/deepface-emd
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CVPR 2022
Face identification (FI) is ubiquitous and drives many high-stake decisions made by law enforcement.
