Unsupervised face recognition
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Unsupervised Face Recognition using Unlabeled Synthetic Data
Papers
Federated Learning Method for Preserving Privacy in Face Recognition System
The state-of-the-art face recognition systems are typically trained on a single computer, utilizing extensive image datasets collected from various number of users. However, these datasets often contain sensitive persona…
Face RecognitionFederated LearningPrivacy PreservingUnsupervised face recognitionUnsupervised Face Recognition using Unlabeled Synthetic Data
Over the past years, the main research innovations in face recognition focused on training deep neural networks on large-scale identity-labeled datasets using variations of multi-class classification losses. However, man…
Face RecognitionMulti-class ClassificationUnsupervised face recognitionFace Recognition Accuracy Across Demographics: Shining a Light Into the Problem
We explore varying face recognition accuracy across demographic groups as a phenomenon partly caused by differences in face illumination. We observe that for a common operational scenario with controlled image acquisitio…
Face RecognitionUnsupervised face recognitionEffect of Super Resolution on High Dimensional Features for Unsupervised Face Recognition in the Wild
Majority of the face recognition algorithms use query faces captured from uncontrolled, in the wild, environment. Often caused by the cameras limited capabilities, it is common for these captured facial images to be blur…
3D Face AlignmentFace AlignmentFace RecognitionImage Super-Resolution+2Discriminative Invariant Kernel Features: A Bells-and-Whistles-Free Approach to Unsupervised Face Recognition and Pose Estimation
We propose an explicitly discriminative and `simple' approach to generate invariance to nuisance transformations modeled as unitary. In practice, the approach works well to handle non-unitary transformations as well. Our…
Face RecognitionPose EstimationUnsupervised face recognition