Popular Computer Vision Datasets for Face Recognition
LFW (Labeled Faces in the Wild)
Dataset link: https://vis-www.cs.umass.edu/lfw/
LFW is composed of 13,000 labelled face pairs which are obtained from the web. This is intended for the large scale face recognition with no restrictions as to pose, expression or illumination. The images contain the identity of the person, and there is a commonly used test set of protocols for judging the facial recognition rate.
CelebA
Dataset link: https://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
CelebA or CelebFaces Attributes primarily consists of over 200,000 celebrity images and 40 labels per image, including age, gender, and all the features on the face. The dataset has also marked several key features on the faces among them being forehead, right cheek, left cheek and the chin. CelebA is also used for the tasks like; face attribute recognition, face detection, and generative modeling.
Dataset for Computer Vision
Computer Vision is an area in the field of Artificial Intelligence that enables machines to interpret and understand visual information. As in case of any other AI application, Computer vision also requires huge amount of data to give accurate results. These datasets provide all the necessary training material for these algorithms.
A dataset that will well-prepared and maintained will allow the model to learn from examples, recognize pattern and then make predictions about the unseen data. Therefore, the quality of datasets matters a lot, as it impacts the performance and robustness of computer vision applications.