19 Free Face Recognition Datasets to Supercharge Your AI Projects in 2025
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.
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.
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.
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.
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.
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.
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.
YouTube With Facial Keypoints contains the facial images of celebrities taken from public forums. The images are cropped from videos and focused on facial key points across each frame.
Wider Face has more than 10,000 images of singles and groups of people. The dataset is grouped based on numerous scenes, such as parades, traffic, parties, meetings, etc.
The Simpsons faces is a collection of images taken from the longest-running TV program, Simpsons, seasons 25 to 28. As the name suggests, this dataset contains 10,000 cropped images of the character faces appearing in the Simpsons show.
The Real and Fake face detection dataset is designed to help facial recognition systems better distinguish between real and fake facial images. The dataset contains more than 1000 real and 900 fake faces with varying recognizable difficulty.
Flickr Faces is a facial image dataset crawled from Flickr. The high-quality dataset features over 70,000 PNG images of people with distinct features such as age, nationality, ethnicity, and image background.
This dataset has 102,476 images of 1,507 Asians (762 males, 745 females). Each person has 62 multi-pose and 6 multi-expression images. The dataset includes various angles, poses, and lighting conditions. It’s useful for face and facial expression recognition.
This dataset has anti-spoofing data for 1,056 people. It includes images from both indoor and outdoor scenes and covers all ages, with a focus on young and middle-aged people. The data includes multiple postures and expressions, useful for tasks like face payment and mobile phone unlocking.
The Multi-Attribute Labelled Faces dataset has 5,250 images with 11,931 labelled faces. It supports detailed analysis of face detection in the wild and was introduced in 2015.
Google Facial Expression Comparison Dataset (Link)
The Google Facial Expression Comparison dataset has over 156k images and 500k triplets. Created by Google researchers, it focuses on analyzing facial expressions, such as emotion classification. It was published in 2018.
Final Thoughts
The demand for accurate and efficient facial recognition systems continues to rise in 2025, and using the right Face Recognition Datasets is the first step toward success. With our curated list of 19 free datasets, you can build, train, and optimize your AI models without breaking the bank. Whether you’re working on security systems, emotion detection, or innovative computer vision applications, these datasets offer the variety and quality you need.
