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Towards Universal Representation Learning for Deep Face Recognition
CVPR 2020 | Traditional recognition models require target domain data to adapt from high-quality training data to conduct unconstrained/low-quality face recognition. Model ensemble is further needed for a universal representation purpose, which significantly increases model complexity. In contrast, our universal face representation learning (URFace) works only on original training data without any target domain data information. It can also deal with unconstrained and unseen testing scenarios.
