Are you searching for high-quality Face Recognition Datasets to elevate your AI and machine learning projects? Look no further! We’ve compiled a list of 19 free facial recognition datasets ideal for tasks like AI algorithm development, model training, and computer vision research.
Why Face Recognition Datasets Are Essential
Face recognition plays a vital role in modern AI applications, from improving security systems to creating personalized user experiences. The global facial recognition market is expected to grow from $5.01 billion in 2023 to $12.67 billion by 2030, with a CAGR of 14.5%, driven by advancements in AI and the rising demand for contactless authentication.
Free datasets are essential for developers and researchers, offering cost-effective, diverse, and well-structured data for training robust models. These datasets support innovation in areas like emotion detection, age estimation, and pose analysis, helping you stay competitive in this rapidly evolving field.
19 Free Facial Datasets for Face Recognition Model Training
A facial recognition system can perform its computer vision tasks only when trained on quality image datasets. Without a quality image recognition dataset, you might not be able to develop a robust facial recognition system. But we have a solution.
Explore a repository of high-quality open-image datasets that can be accessed for free.
Let’s get started.
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Labeled Faces in the Wild (Link)
Another free-to-download large facial image dataset, Labeled Faces in the Wild, contains approximately 13,000 facial photographs specifically designed for performing unconstrained facial recognition tasks. The images are collected from the web and are labeled with the person’s name.
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CelebFaces (Link)
CelebFaces is a freely available image dataset containing face attribute images of more than 200,000 celebrities. Each of these images comes annotated with 40 attributes. Moreover, the annotations also include 10,000 and more identities and landmark localization. It was developed by MMLAB for non-commercial research purposes and face detection, localization, and attribute recognition.
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Tufts Face Database (Link)
Tufts Face database is a large-scale heterogeneous face detection database with various image modalities including photographic images, computerized sketches of faces, and 3D, thermal and infrared images of participants. This comprehensive collection of over 10,000 images has participants of both genders, a wide age range, and from different countries.
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Google Facial Expression Comparison (Link)
Google Facial Expression comparison is another large-scale free dataset containing face image triplets. Humans further annotate the images to specify which pair among the three have the most similar facial expression.
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UMDFaces (Link)
One of the largest datasets, UMDFaces features more than 367,000 annotated faces across 8,200 subjects. The database also contains more than 3.7 million annotated frames from videos using facial key points of 3,100 subjects.
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Face Images with Marked Landmark Points (Link)
This free facial recognition dataset has 7049 images, each marked with up to 15 keypoints. The keypoints per image can vary, but 15 is the maximum. All keypoint data is provided in a CSV file.
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UTKFace (Link)
The UTK Face dataset has 20,000 images of people of all ages. It includes information on age, ethnicity, and gender.
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MORPH (Link)
MORPH is a dataset for estimating age from faces. It has 55,134 images of 13,617 people aged 16 to 77.