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Adapting foundation models with synthetic data can dramatically enhance face recognition accuracy, with some methods even surpassing traditional baselines.
Achieving an 8.00% equal error rate, the top solution highlights the critical role of temporal patterns in footstep recognition, yet reveals persistent challenges with unseen footwear.