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Home > All Category Datasets > Computer Vision Datasets > 99 People – Face Recognition Dataset with Multi-Angle Images

99 People – Face Recognition Dataset with Multi-Angle Images

face image dataset
face recognition dataset
facial expression dataset
facial attribute dataset
multi angle face dataset

This dataset contains human face images collected from 99 participants, with a balanced distribution across genders and age groups and coverage of diverse skin tones. Each participant contributes approximately 2,100 images captured under varied conditions, including different camera angles, facial expressions, lighting conditions, and eyewear. Facial attributes such as gender, age, and expression are annotated for each image. The overall annotation accuracy is ≥97%. The dataset is suitable for face recognition, facial attribute analysis, facial expression recognition, and face image model training.

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SpecificationsSpecifications
Data size
99 people, 2100 images per person
Race distribution
44 white people, 55 black people
Gender distribution
55 males, 44 females
Age distribution
young people
Collecting environment
indoor scenes
Data diversity
multiple expressions, ages, light conditions and angles
Device
camera
Data format
.jpg, .metadata
Accuracy
the accuracy of labels of gender, age, wearing glasses or not, expression, camera angle and light condition is more than 97%
Sample Sample
  • 99 People – Face Recognition Dataset with Multi-Angle Images
  • 99 People – Face Recognition Dataset with Multi-Angle Images
  • 99 People – Face Recognition Dataset with Multi-Angle Images
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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.

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