Papers Age-Invariant Face Recognition
“Age-Invariant Face Recognition” 태그가 달린 논문 19편 · 필터 해제
From Age Estimation to Age-Invariant Face Recognition: Generalized Age Feature Extraction Using Order-Enhanced Contrastive Learning
Generalized age feature extraction is crucial for age-related facial analysis tasks, such as age estimation and age-invariant face recognition (AIFR). Despite the recent successes of models in homogeneous-dataset experim…
Age EstimationAge-Invariant Face RecognitionContrastive LearningFace Recognition+1Unmasking the Uniqueness: A Glimpse into Age-Invariant Face Recognition of Indigenous African Faces
The task of recognizing the age-separated faces of an individual, Age-Invariant Face Recognition (AIFR), has received considerable research efforts in Europe, America, and Asia, compared to Africa. Thus, AIFR research ef…
Age-Invariant Face RecognitionFace RecognitionSynthetic Face Ageing: Evaluation, Analysis and Facilitation of Age-Robust Facial Recognition Algorithms
The ability to accurately recognize an individual's face with respect to human aging factor holds significant importance for various private as well as government sectors such as customs and public security bureaus, pass…
Age-Invariant Face RecognitionFace RecognitionHuman AgingCross-Age Contrastive Learning for Age-Invariant Face Recognition
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. Additionally, in real scenarios, i…
Age-Invariant Face RecognitionContrastive LearningFace GenerationFace Recognition+1When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework and A New Benchmark
To minimize the impact of age variation on face recognition, age-invariant face recognition (AIFR) extracts identity-related discriminative features by minimizing the correlation between identity- and age-related feature…
Age-Invariant Face RecognitionFace GenerationFace RecognitionMulti-Task LearningDeep Adaptation of Adult-Child Facial Expressions by Fusing Landmark Features
Imaging of facial affects may be used to measure psychophysiological attributes of children through their adulthood for applications in education, healthcare, and entertainment, among others. Deep convolutional neural ne…
Age-Invariant Face RecognitionClassificationDomain AdaptationFace Recognition+2ChildPredictor: A Child Face Prediction Framework with Disentangled Learning
The appearances of children are inherited from their parents, which makes it feasible to predict them. Predicting realistic children's faces may help settle many social problems, such as age-invariant face recognition, k…
Age-Invariant Face RecognitionFace RecognitionImage-to-Image TranslationKinship Verification+2When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework
To minimize the effects of age variation in face recognition, previous work either extracts identity-related discriminative features by minimizing the correlation between identity- and age-related features, called age-in…
Age-Invariant Face RecognitionDomain AdaptationFace GenerationFace Recognition+1Disentangled Representation for Age-Invariant Face Recognition: A Mutual Information Minimization Perspective
General face recognition has seen remarkable progress in recent years. However, large age gap still remains a big challenge due to significant alterations in facial appearance and bone structure. Disentanglement play…
Age-Invariant Face RecognitionDisentanglementFace RecognitionMORPH+2LIAAD: Lightweight Attentive Angular Distillation for Large-scale Age-Invariant Face Recognition
Disentangled representations have been commonly adopted to Age-invariant Face Recognition (AiFR) tasks. However, these methods have reached some limitations with (1) the requirement of large-scale face recognition (FR) t…
Age-Invariant Face RecognitionFace RecognitionDecorrelated Adversarial Learning for Age-Invariant Face Recognition
There has been an increasing research interest in age-invariant face recognition. However, matching faces with big age gaps remains a challenging problem, primarily due to the significant discrepancy of face appearances …
Age-Invariant Face RecognitionFace RecognitionMORPHOrthogonal Deep Features Decomposition for Age-Invariant Face Recognition
As facial appearance is subject to significant intra-class variations caused by the aging process over time, age-invariant face recognition (AIFR) remains a major challenge in face recognition community. To reduce the in…
Age-Invariant Face RecognitionBenchmarkingFace RecognitionMORPHLook Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition
Despite the remarkable progress in face recognition related technologies, reliably recognizing faces across ages still remains a big challenge. The appearance of a human face changes substantially over time, resulting in…
Age-Invariant Face RecognitionBenchmarkingFace GenerationFace Recognition+3Temporal 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. In order to efficiently address the problem, this work first…
Age-Invariant Face RecognitionDensity EstimationFace RecognitionFace Verification+1Latent Factor Guided Convolutional Neural Networks for Age-Invariant Face Recognition
While considerable progresses have been made on face recognition, age-invariant face recognition (AIFR) still remains a major challenge in real world applications of face recognition systems. The major difficulty of AIFR…
Age-Invariant Face RecognitionFace RecognitionMORPHLarge 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/o…
Age-Invariant Face RecognitionFace RecognitionFace VerificationA 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. First, a new maximum entropy feature descriptor (MEFD) is developed that encodes the micros…
Age-Invariant Face RecognitionFace RecognitionMORPHFace 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 i…
Age-Invariant Face RecognitionFace DetectionFace IdentificationFace Recognition+2Blessing of Dimensionality: High-Dimensional Feature and Its Efficient Compression for Face Verification
Making a high-dimensional (e.g., 100K-dim) feature for face recognition seems not a good idea because it will bring difficulties on consequent training, computation, and storage. This prevents further exploration of the …
Age-Invariant Face RecognitionFace RecognitionFace Verificationregression