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.

2,499,771 Boxes 7,262 Images Human Facial Skin Defects Dataset.The data includes the following seven types of facial skin defects: acne, moles, scars, herpes (sores), speckles, freckles, and others. This data can be used for tasks such as skin defects detection.

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.

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.

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.

100 People - Face Detection & Face 96 Landmarks Annotation Data. The data includes multiple ages, multiple time periods and multiple races (Caucasian, Black, Indian). The driver behaviors includes dangerous behavior, fatigue behavior and visual movement behavior. In terms of device, infrared cameras were applied. In terms of annotation, each individual consists of 274 to 299 photos, with annotations for detected facial bounding boxes and 96 facial landmarks. The data can be used for tasks such as facial detection, 96 facial landmark recognition.

568 People - Face Detection & Face 106 Landmarks & Human Body Segmentation Annotation Data in Online Conference Scenes. The ethnic groups include East Asians, Caucasians, Blacks, and Browns, with a primary focus on young adults. Various indoor office scenes were captured, including meeting rooms, cafes, libraries, and bedrooms. In terms of annotation, each individual consists of 61 to 64 photos, with annotations for detected facial bounding boxes and 106 facial landmarks, as well as segmentation annotations for the human body. The data can be used for tasks such as facial detection, 106 facial landmark recognition, and human body segmentation.