Computer Vision, a branch of AI, provides computers with the ability to draw useful information from images and videos. The machine learning model then acts on the extracted information. While computer vision acts as the eyes of the computer – observing and understanding the world, the AI allows it to think. The purpose of computer vision technology is to enable computing systems to understand images, videos, and other visual inputs – with context – much like human vision.
Top 15 Free Image Datasets for Facial Recognition
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.
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Kinetics-700 is one of the most extensive video datasets that has quickly become the standard for developing facial recognition solutions. The Kinetics-700 is described on the Deep Mind website as a dataset containing high-quality images, including YouTube links to nearly 650with various owing 700 human action classes.
The images depict human-object interaction (such as closing a door or playing the guitar) and human-human interactions (such as hugging or holding hands). Each of these classes contains at least 600 video clips and is human-annotated.
Labeled Faces in the Wild
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.
IMDB-WiKi is another large publicly available image dataset containing human faces with a name, age, and gender. The images are taken from IMDB and Wikipedia totaling 523, 051 in all. The dataset was collected by crawling the actor’s IMDB profile and Wikipedia.
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.
Face Detection in Images
Face Detection in Images is a free-to-use simple dataset containing more than 500 images with more than 1100 faces. With the help of the bounding box technique, the images are manually tagged and annotated.
Tufts Face Database
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
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.
22+ Most Sought Open-Source Datasets for Computer Vision
YouTube with Facial Keypoints
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.
Yale Face Database
The Yale Face Database has 165 images of 15 subjects under different lighting, expression, emotions, and environmental conditions.
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.
Real and Fake Face Detection
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.
Fishnet Open Image Dataset
The fishnet Open image dataset is touted to be the perfect dataset for training face recognition systems containing 35,000 images of fishing. Each image has been cropped using five bounding boxes.
Having the access to high-quality image datasets is crucial to the training and development of facial recognition systems. Your facial recognition model is as effective, credible, and reliable as the dataset you are using to train the model.
Since data drives AI and Computer Vision, you need high-quality data to develop a winning facial recognition system. This free-to-use and annotated image datasets can further your development goals. However, if you require highly-customized and accurately annotated image datasets, Shaip is the only solution.
We are the most preferred AI solutions partner with years of experience providing clients with customized data solutions for their specific needs. To know more about our data proficiency, contact our team today.