Face Verification
121 papers with code • 20 benchmarks • 21 datasets
Face Verification is a machine learning task in computer vision that involves determining whether two facial images belong to the same person or not. The task involves extracting features from the facial images, such as the shape and texture of the face, and then using these features to compare and verify the similarity between the images.
( Image credit: Pose-Robust Face Recognition via Deep Residual Equivariant Mapping )
Benchmarks
These leaderboards are used to track progress in Face Verification
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Libraries
Use these libraries to find Face Verification models and implementations
LFW
CASIA-WebFace
MS-Celeb-1M
CK+
IJB-C
MegaFace
IJB-A
IJB-B
VGG Face
Oulu-CASIA
Latest papers with no code
Age-Invariant Face Embedding using the Wasserstein Distance
In this work, we study face verification in datasets where images of the same individuals exhibit significant age differences.
Racial Bias within Face Recognition: A Survey
Facial recognition is one of the most academically studied and industrially developed areas within computer vision where we readily find associated applications deployed globally.
An information-theoretic learning model based on importance sampling
A crucial assumption underlying the most current theory of machine learning is that the training distribution is identical to the test distribution.
Semantic Adversarial Attacks on Face Recognition through Significant Attributes
The probability score method is based on training a Face Verification model for an attribute prediction task to obtain a class probability score for each attribute.
GH-Feat: Learning Versatile Generative Hierarchical Features from GANs
In this work we investigate that such a generative feature learned from image synthesis exhibits great potentials in solving a wide range of computer vision tasks, including both generative ones and more importantly discriminative ones.
Learning Representations for Masked Facial Recovery
The pandemic of these very recent years has led to a dramatic increase in people wearing protective masks in public venues.
A Brief Survey on Person Recognition at a Distance
Person recognition at a distance entails recognizing the identity of an individual appearing in images or videos collected by long-range imaging systems such as drones or surveillance cameras.
Generating 2D and 3D Master Faces for Dictionary Attacks with a Network-Assisted Latent Space Evolution
The results we present demonstrate that it is possible to obtain a considerable coverage of the identities in the LFW or RFW datasets with less than 10 master faces, for six leading deep face recognition systems.
Learning Audio-Visual embedding for Person Verification in the Wild
It has already been observed that audio-visual embedding is more robust than uni-modality embedding for person verification.
Can GAN-induced Attribute Manipulations Impact Face Recognition?
Impact due to demographic factors such as age, sex, race, etc., has been studied extensively in automated face recognition systems.
