228 datasets found

The Extended Yale B dataset contains 64 images for each of 38 individuals in frontal view and different illumination conditions.

The CartoonFace dataset is a dataset of images of faces.

The CMU faces dataset contains 624 images of 20 persons with different poses and expressions, with and without sunglasses.

The dataset used for face recognition tasks.

Face verification and recognition dataset

Face verification and recognition dataset

Face verification and recognition dataset

The proposed approach uses the Retinex method and SQI method to smoothed images as the estimation of the extrinsic factor. KPCA offers improved analysis of datasets that have...

Poof: Part-based one-vs.-one features for fine-grained categorization, face verification, and attribute estimation.

Extended Labeled Faces in-the-Wild (ELFW) dataset is an extension of the Labeled Faces in-the-Wild (LFW) dataset, with additional face-related categories and synthetic objects.

The Labeled Face in the Wild (LFW) dataset is a large-scale face recognition dataset containing over 13,000 images of 130 individuals.

A dataset of 105 individuals with varying poses, head rotations, and occlusions.

A dataset of 118 individuals with a variety of facial expressions and corresponding depth profiles.

Face recognition dataset with varying poses, expressions, and lighting conditions

Face recognition dataset with varying poses, expressions, and lighting conditions

The Labeled Faces in the Wild (LFW) dataset contains 13,233 images from 5,749 identities, with large variations in pose, expression and illumination.

The dataset used in the paper is the CMU-PIE face dataset, which contains images of 67 subjects with 13 different poses and 21 different illuminations.

The FRAV2D, FERET, and ORL face databases are used for face recognition.

The proposed technique uses the FRAV2D, FERET, and ORL face databases for face recognition.

The megaface benchmark: 1 million faces for recognition at scale.