Computer Vision Datasets

87,871 Images of 106 Facial Landmarks Annotation Data (complicated scenes)，this dataset includes yellow race, black race, white race and Indian people. In order to be more challenging, the data includes multiple scenes, multiple poses, different ages, light conditions and complicated expressions. This data can be used for tasks such as face detection and face recognition.

The 399 Asians - 35,112 Images Multi-pose Face Data with 21 Facial Landmarks Annotation data is collected from 399 people. The data diversity includes multiple poses, different ages, different light conditions and multiple scenes. This data can be used for tasks such as face detection and face recognition. Thee accuracy of labels of gender, face pose, year of birth, light condition, scene and wearing glasses or not is more than 97%;annotation accuracy of facial landmarks is more than 97%

1,142 people facial expression data in online conference scenes, including Asian, Caucasian, black, and brown multitasking, mainly young and middle-aged, collected a variety of indoor office scenes, covering meeting rooms, coffee shops, libraries , bedroom, etc., each collector collected 7 kinds of expressions: normal, happy, surprised, sad, angry, disgusted, and fearful.

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.

25,581 Images - 88 Facial Landmarks Annotation Data. The dataset includes Asian, black race, Caucasian and brown race. In order to be more challenging, the data includes multiple scenes, multiple poses, different ages, light conditions and complicated expressions. For annotation, 88 facial landmarks and visible and invisible attributes of landmarks were annotated. This data can be used for tasks such as face detection and face recognition.

26,090 Images Human Facial Skin Defects Data. The data includes the following five types of facial skin defects: acne, acne marks, stains, wrinkles, and dark circles. This data can be used for tasks such as skin defects detection.

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.

4,484 people multi-race – infrared face recognition data. The collecting scenes of this dataset include indoor scenes and outdoor scenes. The data includes male and female. The race distribution includes Asian, Black, Caucasian and Brown people. The age distribution ranges from child to the elderly, the young people and the middle aged are the majorities. The collecting device is DV-DH4,044S305AD. The data diversity includes multiple age periods, multiple facial postures, multiple scenes. The data can be used for tasks such as infrared face recognition. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

This dataset contains 116,048 sets of 3D handpose data, each set includes hand mask image(RGB, 24-bit), depth image(16-bit), camera intrinsic parameter file(TXT), 3D keypoints file(OBJ), mesh file(OBJ), gesture type file(TXT), keypoints demo image(JPG), and mesh demo image(JPG). The data is collected indoors, with the right hand (no handheld objects), covering both first-person and third-person perspectives, multiple gesture types, finger poses, hand overall rotation poses, individuals and Kinect devices used. This dataset does not include personally identifiable facial information, with hand mask images and depth images aligned. This dataset can be used for tasks such as handpose recognition, hand 3D reconstruction, and hand keypoints detection.