20 datasets found

Tags: face images

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  • Labeled Face in the Wild (LFW) dataset

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

    The FaceTracer dataset contains a large collection of face images of children.
  • Children Longitudinal Face (CLF)

    The Children Longitudinal Face (CLF) dataset contains 3,682 face images of 919 children, in the age range of 2 to 18 years. Each subject has an average of 4 images acquired over...
  • ExtYaleB

    The ExtYaleB dataset is a face recognition dataset, containing 2,414 frontal face images of 38 subjects.
  • Facescrub dataset

    The Facescrub dataset contains over 100,000 face images of 530 people.
  • Face dataset

    The dataset used in this paper is a collection of 3D shapes with the same connectivity to train the network.
  • FG-NET

    The FG-NET1 dataset contains 1002 images colored resolution, quality, or gray with variation in illumination, viewpoint, and expression. There are 82 different subjects with...
  • Face Research Lab London (FRLL) dataset

    Face Research Lab London (FRLL) dataset used for evaluating the proposed Fast-DiM algorithm
  • Adience

    Ordinal regression refers to classifying object instances into ordinal categories. It has been widely studied in many scenarios, such as medical disease grading and movie...
  • Deep Funneled LFW

    The deep funneled LFW dataset contains about 13,233 images, 5,749 different identities, and 40 binary attributes for each face image.
  • VGG-Face dataset

    The VGG-Face dataset contains 2.2 million URLs with corresponding face detection locations.
  • CASIA-Webface dataset

    The CASIA-Webface dataset contains 494,414 images of 10,575 subjects.
  • IARPA Janus Benchmark-B (IJB-B) dataset

    The IARPA Janus Benchmark-B (IJB-B) dataset contains 1,026,280 face images of 1,845 individuals.
  • Labeled Faces in the Wild (LFW) dataset

    Labeled Faces in the Wild (LFW) dataset consists of 5749 subjects each having different number of images ranging from 1 to 530.
  • Image pairs of competitors with training instances of train_relationship.csv

    The dataset is used for kinship recognition task, where the goal is to determine if two individuals are biomedically related based solely on images of their faces.
  • Multi-PIE

    The Multi-PIE dataset consists of 754,200 images from 337 subjects with large variations in head pose, illumination, and facial expression.
  • AFHQ

    The dataset used in the paper is a set of images from the AFHQ dataset, containing 1.5K images of different animal faces.
  • VGGFace2

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

    Face recognition and person re-identiļ¬cation using paired image-attribute data, where the attributes (i.e., soft biometrics) are only available during the training phase.
  • FFHQ

    Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...