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568 People Face Detection Dataset & 106 Landmarks with Body Segmentation (Online Conference)
face detection dataset with landmarks
106 facial landmarks dataset
human body segmentation dataset
online conference face dataset
multi-ethnic face images dataset
AI dataset for facial and body analysis
This dataset contains 568 individuals, ethnic groups include East Asians, Caucasians, Blacks, and Browns, primarily young adults. Various indoor office scenes were captured, including meeting rooms, cafes, libraries, and bedrooms. In terms of annotation, each individual has 61 to 64 photos with annotations for detected facial bounding boxes, 106 facial landmarks, and segmentation annotations for the human body. This dataset can be used for tasks like face detection, facial landmark recognition, human body segmentation, and computer vision applications in virtual meeting or office environments.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
![Specifications]()
Specifications
Data size
568 people, each person contains 61-64 images
Race distribution
142 Asians, 142 Caucasians, 142 Blacks, and 142 Browns
Nationality distribution
Vietnam, India, Indonesia, Thailand, Pakistan, Russia, France, Germany, etc.
Gender distribution
323 males, 245 females
Age distribution
ranging from adolescents to the elderly, primarily focusing on young adults
Collection environment
indoor office settings, such as meeting rooms, cafes, libraries, bedrooms, etc.
Collection diversity
various facial angles, facial expressions, age groups, and scenarios
Collection equipment
cellphone, simulating laptop camera perspectives in conference settings
Data format
image data format is .jpg, annotation document format is .json
Annotation content
annotations include detected facial bounding boxes and 106 facial landmarks, as well as body segmentation annotations
Accuracy rate
Face Detection Bounding Box Accuracy: the detection box is considered qualified if the offset does not exceed 5 pixels on all four sides, with a qualification rate of no less than 95%; Facial Landmark Accuracy: the accuracy rate of facial landmark annotation must be no less than 95%; Human Segmentation Accuracy: the mask edge error in the x and y directions must be within 5 pixels to be considered correctly annotated; with the human body as the unit, the annotation accuracy rate should be abov
![Sample]()
Sample
Tell Us Your Special Needs
What types of computer vision applications can Nexdata’s datasets support?
Nexdata’s computer vision datasets support a wide range of AI applications, including image classification, object detection, image segmentation, facial and human-related recognition, scene understanding, autonomous driving, and other visual perception tasks. Depending on the dataset, data may include images, videos, bounding boxes, polygons, keypoints, segmentation masks, text annotations, and other structured labels.
Can Nexdata customize Computer Vision datasets based on our specific requirements?
Yes. If our off-the-shelf Computer Vision datasets do not fully meet your requirements, Nexdata provides flexible custom data collection, annotation, and curation services. We can customize data based on your target objects, environments, scenarios, camera specifications, geographic locations, data volume, annotation formats, and quality standards to support specific model training and evaluation needs.
How does Nexdata ensure the quality and scalability of its Computer Vision datasets?
Nexdata applies multi-stage quality control throughout data collection, annotation, validation, and delivery. Depending on project requirements, we can implement customized annotation guidelines, multi-level reviews, consistency checks, and quality sampling to ensure dataset accuracy and consistency. Our data collection and processing capabilities can also be scaled to support large-volume Computer Vision projects.
33aca919-5c9e-4bc5-9588-fb85cb9aa111
Specifications
Sample
