Labeled Faces in the Wild (LFW)
- The Labeled Faces in the Wild (LFW) dataset is a collection of labeled human faces designed for studying the problem of unconstrained face recognition.
- It contains over 13,000 images of faces collected from the web, each with a label indicating the person’s name. This dataset is widely used for benchmarking face verification and recognition algorithms.
- It was developed by the University of Massachusetts, Amherst.
Dataset for Face Recognition
Face recognition is a rapidly evolving field within computer vision, with applications spanning security, social media, and personalized user experiences. A key component of developing effective face recognition systems is access to high-quality datasets. These datasets provide the foundation for training machine learning models, evaluating their performance, and benchmarking against state-of-the-art techniques. In this article, we will discuss some of the famous datasets fot face recognition.