4,253 Pairs of Human Face Images – Before and After Makeup

Face recognition

Make-up image data

facial data

4,253 Pairs of Human Face Images – Before and After Makeup. For each pair, one image without makeup and one image with makeup are included. This dataset can be used for tasks such as face recognition and makeup style analysis.

This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.

Recommended Dataset

5,172 People - Multi-race Juvenile and Multi-pose Facial Images

5,172 People - Multi-race Juvenile and Multi-pose Facial Images. This data includes black people, Caucasian people and brown people. Each subject was collected 10 images. (The 10 images include 10 photos in different lighting, different face poses and different collection environments). This data can be used for face recognition related tasks.

Different face poses and races Different ages Different lighting Different collection environments

21,300 Images - Human Body Segmentation Data

21,300 Images - Human Body Segmentation Data. The data includes indoor scenes and outdoor scenes. The data covers female people and male people. The race distribution includes Asian, black race and Caucasian. The age distribution ranges from teenager to the elderly, the middle-aged and young people are the majorities. The dataset diversity includes multiple scenes, ages, races, postures, and appendages. In terms of annotation, we adpoted pixel-wise segmentation annotations on human body. The data can be used for tasks such as human body segmentation.

Multiple scenes Multiple ages Multiple races Multiple postures Multiple appendages

5,993 People – Infrared Face Recognition Data

5,993 People – Infrared Face Recognition Data. The collecting scenes of this dataset include indoor scenes and outdoor scenes. The data includes male and female. The age distribution ranges from child to the elderly, the young people and the middle aged are the majorities. The collecting device is realsense D453i. The data diversity includes multiple age periods, multiple facial postures, multiple scenes. The data can be used for tasks such as infrared face recognition.

infrared face recognition indoor scenes outdoor scenes realsense D453i multiple age periods multiple facial postures multiple scenes

34,981 Images – Alpha Matte Human Body Segmentation Data (Fine Version)

34,981 Images – Alpha Matte Human Body Segmentation Data. The data includes indoor scenes and outdoor scenes. The dataset diversity includes multiple scenes, multiple age groups, multiple human body angles, multiple postures. In terms of annotation, alpha matte segmentation annotation was adopted for the human body. The data can be used for tasks such as alpha matte human body segmentation.

Alpha matte human body segmentation multiple scenes multiple age groups multiple human body angles multiple postures

4,458 People - 3D Facial Expressions Recognition Data

4,458 People - 3D Facial Expressions Recognition Data. The collection scenes include indoor scenes and outdoor scenes. The dataset includes males and females. The age distribution ranges from juvenile to the elderly, the young people and the middle aged are the majorities. The device includes iPhone X, iPhone XR. The data diversity includes different expressions, different ages, different races, different collecting scenes. This data can be used for tasks such as 3D facial expression recognition.

3D facial expressions recognition different expressions different ages different races different collecting scenes

5,199 People – 3D Face Recognition Images Data

5,199 People – 3D Face Recognition Images Data. The collection scene is indoor scene. The dataset includes males and females. The age distribution ranges from juvenile to the elderly, the young people and the middle aged are the majorities. The device includes iPhone X, iPhone XR. The data diversity includes multiple facial postures, multiple light conditions, multiple indoor scenes. This data can be used for tasks such as 3D face recognition.

3D Face Recognition multiple facial postures multiple light conditions multiple indoor scenes

1,417 People – 3D Living_Face & Anti_Spoofing Data

1,417 People – 3D Living_Face & Anti_Spoofing Data. The collection scenes include indoor and outdoor scenes. The dataset includes males and females. The age distribution ranges from juvenile to the elderly, the young people and the middle aged are the majorities. The device includes iPhone X, iPhone XR. The data diversity includes various expressions, facial postures, anti-spoofing samples, multiple light conditions, multiple scenes. This data can be used for tasks such as 3D face recognition, 3D Living_Face & Anti_Spoofing.

3D Living_Face & Anti_Spoofing various expressions facial postures anti-spoofing samples multiple light conditions multiple scenes

11,113 People - Face Recognition Data with Gauze Mask

11,113 People - Face Recognition Data with Gauze Mask, for each subject, 7 images were collected. The dataset diversity includes multiple mask types, multiple ages, multiple races, multiple light conditions and scenes.This data can be applied to computer vision tasks such as occluded face detection and recognition.

Face recognition Face occlusion Frontal face Gause mask