SphereFace: Deep Hypersphere Embedding for Face Recognition
时间: 2024-05-23 10:10:27 浏览: 11
SphereFace is a deep learning model that was proposed for face recognition tasks. It is based on the idea of embedding face images into a hypersphere space, where the distance between different face embeddings can be used to measure the similarity between faces.
The SphereFace model consists of a deep convolutional neural network (CNN) that learns to extract high-level features from face images. The output of the CNN is then fed into a fully connected layer, which maps the features onto a hypersphere with a fixed radius. The final face embedding is obtained by normalizing the feature vector to lie on the hypersphere.
SphereFace was shown to achieve state-of-the-art performance on several face recognition benchmarks, including LFW, CFP, and MegaFace. Its success is attributed to its ability to learn discriminative features that are robust to variations in pose, illumination, and expression.
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