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Current face recognition models miss key features in twin identification, achieving only 76% accuracy despite the potential for significant improvement through skin marks and asymmetry.
1-consistency achieves oracle-level accuracy in face matching without the need for pre-set thresholds, outperforming traditional methods in degraded conditions.
