Near-Duplicate Face Images (NDFI)
The Near-Duplicate Face Images (NDFI) dataset consists of multiple sets of face images, where each set represents slightly altered versions of the same face image. The alterations were induced using 4 photometric transformations. The full dataset contains 27,270 face images corresponding to 468 subjects. A smaller subset containing 12,290 images corresponding to 391 subjects is also available.
YouTube Makeup Dataset (YMU)
A face image dataset obtained from YouTube makeup tutorials. (All images have been curated from the Internet.)
Virtual Makeup Dataset (VMU)
A face image dataset consisting of synthetically generated makeup face images. (All images have been curated from the Internet.)
Makeup in the Wild (MiW)
A dataset containing face images with and without makeup from the internet. (All images have been curated from the Internet.)
Makeup Induced Face Spoofing (MIFS)
A face image dataset where makeup is used to impersonate someone else. (All images have been curated from the Internet.)
MSU AVIS Dataset
MSU-AVIS dataset consists of audio-visual data, from 50 different subjects, freely speaking (text-independent) while walking around in a semi-constrained indoor environment mimicking a real-world surveillance scenario. The face images exhibit variations due to large stand-off distance from the camera, occlusions, pose, indoor-illumination, expressions, accessories, etc. The audio samples exhibit variations due to the distance of the subject from the microphone, indoor reverberations, background noise, etc.