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computer-vision

Age-Invariant Face Recognition

3260 papers • 126 benchmarks • 313 datasets

Age-invariant face recognition is the task of performing face recognition that is invariant to differences in age. ( Image credit: Look Across Elapse )

(Image credit: Papersgraph)

Benchmarks

These leaderboards are used to track progress in age-invariant-face-recognition

Trend

Dataset

Best Model

Actions

CACDVS

MORPH Album2

CAFR

Libraries

Use these libraries to find age-invariant-face-recognition models and implementations

Datasets

MORPH

FG-NET

Subtasks

No subtasks available.

Most implemented papers

ChildPredictor: A Child Face Prediction Framework With Disentangled Learning

Qiong Yan, Yuzhi Zhao, L. Po, W. Liu, Weifeng Ou, Xuehui Wang, Yujia Zhang, C. Wong, Chiu-Sing Pang, W. Yu, Buhua Liu•Wed Apr 20 2022

A new disentangled learning strategy for children's face prediction called ChildPredictor, which transfers human faces to genetic factors by encoders and back by generators, and learns the relationship between the genetic factors of parents and children through a mapping function.

Content

Introduction Benchmarks Datasets Subtasks Libraries Papers

FG-NET

Paper Graph

Decorrelated Adversarial Learning for Age-Invariant Face Recognition

Zhifeng Li, W. Liu, Dihong Gong, Hao Wang•Tue Apr 09 2019

A novel algorithm to remove age-related components from features mixed with both identity and age information is presented, which learns the decomposed features of age and identity whose correlation is significantly reduced.

92 0

Paper Graph

Cross-Age Contrastive Learning for Age-Invariant Face Recognition

Haoyi Wang, Victor Sanchez, Chang-Tsun Li•Sun Dec 17 2023

This work introduces a novel semi-supervised learning approach named Cross-Age Contrastive Learning (CACon), which achieves state-of-the-art performance in homogeneous-dataset experiments on several age-invariant face recognition benchmarks but also outperforms other methods by a large margin in cross-dataset experiments.

10 0

Paper Graph

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

Jiashi Feng, Shuicheng Yan, Jianshu Li, Jian Zhao, Junliang Xing, Yan Xu, Hengzhu Liu, Yu Cheng, Yi Cheng, Yang Yang, Haochong Lan, F. Zhao, Lin Xiong, Sugiri Pranata, Shengmei Shen•Sat Sep 01 2018

This work proposes a deep Age-Invariant Model (AIM) for face recognition in the wild with three distinct novelties, and proposes a new large-scale Cross-Age Face Recognition (CAFR) benchmark dataset to facilitate existing efforts and push the frontiers of age-invariant face recognition research.

96 0

Paper Graph

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

Junping Zhang, Hongming Shan, Zhizhong Huang•Mon Mar 01 2021

A unified, multi-task framework to jointly handle AIFR and FAS is proposed, which can learn age-invariant identity-related representation while achieving pleasing face synthesis, and a novel identity conditional module is proposed to achieve identity-level FAS.

95 0

Paper Graph

Adding a benchmark result helps the community track progress.

Age-Invariant Face Recognition | State-of-the-Art