Age-Invariant Face Recognition
5 papers with code • 4 benchmarks • 2 datasets
Age-invariant face recognition is the task of performing face recognition that is invariant to differences in age.
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Latest papers with no code
When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework and A New Benchmark
Extensive experimental results on five benchmark cross-age datasets demonstrate that MTLFace yields superior performance for both AIFR and FAS.
Deep Adaptation of Adult-Child Facial Expressions by Fusing Landmark Features
We propose domain adaptation to concurrently align distributions of adult and child expressions in a shared latent space for robust classification of either domain.
Disentangled Representation for Age-Invariant Face Recognition: A Mutual Information Minimization Perspective
For quantitative measure of the degree of disentanglement, we verify that mutual information can represent as metric.
LIAAD: Lightweight Attentive Angular Distillation for Large-scale Age-Invariant Face Recognition
This work presents a novel Lightweight Attentive Angular Distillation (LIAAD) approach to Large-scale Lightweight AiFR that overcomes these limitations.
Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition
Extensive experiments conducted on the three public domain face aging datasets (MORPH Album 2, CACD-VS and FG-NET) have shown the effectiveness of the proposed approach and the value of the constructed CAF dataset on AIFR.
Temporal Non-Volume Preserving Approach to Facial Age-Progression and Age-Invariant Face Recognition
Modeling the long-term facial aging process is extremely challenging due to the presence of large and non-linear variations during the face development stages.
Latent Factor Guided Convolutional Neural Networks for Age-Invariant Face Recognition
In order to address this problem, we propose a novel deep face recognition framework to learn the age-invariant deep face features through a carefully designed CNN model.
Large age-gap face verification by feature injection in deep networks
This paper introduces a new method for face verification across large age gaps and also a dataset containing variations of age in the wild, the Large Age-Gap (LAG) dataset, with images ranging from child/young to adult/old.
A Maximum Entropy Feature Descriptor for Age Invariant Face Recognition
In this paper, we propose a new approach to overcome the representation and matching problems in age invariant face recognition.
Face Prediction Model for an Automatic Age-invariant Face Recognition System
Automated face recognition and identification softwares are becoming part of our daily life; it finds its abode not only with Facebook's auto photo tagging, Apple's iPhoto, Google's Picasa, Microsoft's Kinect, but also in Homeland Security Department's dedicated biometric face detection systems.