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.

( Image credit: Look Across Elapse )

Most implemented papers

Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition

ZhaoJ9014/High_Performance_Face_Recognition 2 Sep 2018

Benchmarking our model on one of the most popular unconstrained face recognition datasets IJB-C additionally verifies the promising generalizability of AIM in recognizing faces in the wild.

Decorrelated Adversarial Learning for Age-Invariant Face Recognition

neverUseThisName/Decorrelated-Adversarial-Learning CVPR 2019

To reduce such a discrepancy, in this paper we propose a novel algorithm to remove age-related components from features mixed with both identity and age information.

When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework

Hzzone/MTLFace CVPR 2021

We further validate MTLFace on two popular general face recognition datasets, showing competitive performance for face recognition in the wild.

ChildPredictor: A Child Face Prediction Framework with Disentangled Learning

zhaoyuzhi/childpredictor 21 Apr 2022

On this basis, we formulate predictions as a mapping from parents' genetic factors to children's genetic factors, and disentangle them from external and variety factors.

Cross-Age Contrastive Learning for Age-Invariant Face Recognition

FaceOnLive/Face-Recognition-SDK-Android 18 Dec 2023

Cross-age facial images are typically challenging and expensive to collect, making noise-free age-oriented datasets relatively small compared to widely-used large-scale facial datasets.