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8.3K Images – Facial Landmark Dataset for Face Recognition
facial landmark detection dataset
facial landmark dataset
facial landmark annotation dataset
face landmark dataset
facial keypoint dataset
This dataset contains 8,308 facial images annotated with 106 facial landmarks. It includes Black and Caucasian individuals. In this dataset, most images feature frontal faces, while additional samples capture exaggerated facial expressions. The dataset can be used for facial landmark detection and related computer vision tasks, including face detection, face recognition, face segmentation and other tasks.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
Specifications
Data size
8,308 images. There is only one face in an image
Gender distribution
male: 4,024 images, female: 4,284 images
Race distribution
5,322 images of Caucasian race, 2,986 images of black race
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.
Specifications
Sample
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