3260 papers • 126 benchmarks • 313 datasets
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These leaderboards are used to track progress in disguised-face-verification
Use these libraries to find disguised-face-verification models and implementations
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A system that directly learns a mapping from face images to a compact Euclidean space where distances directly correspond to a measure offace similarity, and achieves state-of-the-art face recognition performance using only 128-bytes perface.
This paper describes the approach for the Disguised Faces in the Wild (DFW) 2018 challenge, based on VGG-face architecture paired with Contrastive loss based on cosine distance metric, and achieves 27.13% absolute increase in accuracy over the DFW baseline.
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