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1,374,801 Images - 88,880 People – Diverse Face Recognition Dataset (Multi-race, Multi-pose)
diverse face images dataset
multi-pose face dataset
multi-race face recognition dataset
face recognition training dataset
age-diverse face recognition data
This dataset contains 88,880 face images from diverse individuals, each person contains at least 5 images. The race distribution includes Asian, Black, Caucasian and brown individuals, the age distribution is ranging from infant to the elderly, the middle-aged and young people are the majorities. The collection environment includes indoor and outdoor scenes. The data diversity includes multiple age periods, multiple scenes, multiple facial postures and multiple expressions. The data can be used for developing face recognition models, age estimation, and AI-based identity verification systems. 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 is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
Specifications
Data size
88,880 people, 1,374,801 images, at least 5 images per person
Population distribution
race distribution: 79,714 Asians, 458 Black, 7,320Caucasian, 1,388 Brown people; gender distribution: 27,366 males, 61,514 females; age distribution: ranging from infant to the elderly, the middle-aged and young people are the majorities
Collecting environment
indoor scenes, outdoor scenes
Data diversity
multiple age periods, multiple scenes, multiple facial postures, multiple expressions
Device
cellphone, camera
Data format
the image data format is common format such as.jpg
Annotation content
label the person – ID, race, nationality, gender, age group
Accuracy rate
the accuracy of label annotation is not less than 95%
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.