Disguised Face Verification
2 papers with code • 2 benchmarks • 2 datasets
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Most implemented papers
FaceNet: A Unified Embedding for Face Recognition and Clustering
On the widely used Labeled Faces in the Wild (LFW) dataset, our system achieves a new record accuracy of 99. 63%.
DisguiseNet : A Contrastive Approach for Disguised Face Verification in the Wild
The experiments show the effectiveness of the approach on the DFW data.