18 datasets found

FaceCat: Enhancing Face Recognition Security with a Unified Generative Model Framework

Labeled faces in the wild: Updates and new reporting procedures.

The dataset used in the paper is a color face recognition dataset, which is used to evaluate the performance of the proposed 2DPCA and R2DPCA methods.

Face recognition dataset with labeled nuisance transformations.

Face recognition dataset with annotated facial pose and illumination conditions.

Synthetic face images with detailed annotation of the most relevant nuisance transformations.

FairFace is a dataset of face images for fairness audit and evaluation, intentionally constructed to be approximately racially balanced.

A dataset for metrical reconstruction of human faces.

A diffusion-based 3D facial generative model conditioned on identity embeddings.

The dataset used in this paper is a collection of images, and the authors used it to train and evaluate Variational Autoencoders (VAEs).

The DeepFace dataset is a large-scale face recognition dataset containing over 2 million images of faces.

The VGGFace2 dataset is a large-scale face recognition dataset containing over 2 million images of faces.

The AR face database contains 100 classes of faces with 26 face images per class with various natural variation and occlusions.

The ORL face database includes 40 classes with 10 images per class with occlusions, scale variations and rotations.

The Bosphorus dataset contains 4666 scans collected from 105 subjects (60 men and 45 women aged between 25 and 35) with poses changes, expression variations, and typical...

The Face Recognition Grand Challenge (FRGC) v2.0 dataset contains 4007 scans of 466 subjects in total.

The dataset used in this paper is the VGG16 dataset, a deep neural network trained on the CIFAR-10 and CIFAR-100 datasets.

The dataset used in the paper is VGGFace2, which is a dataset for face recognition tasks.