VGGFace2
- The VGGFace2 dataset consists of 3.31 million images of 9,131 individuals, sourced from the web. It includes a wide range of poses, ages, and lighting conditions, making it suitable for training robust face recognition models.
- VGGFace2 is known for its diversity and scale, contributing to advancements in face recognition research. This dataset was created by the Visual Geometry Group at the University of Oxford.
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.