AI RESEARCH
CO-EVO: Co-evolving Semantic Anchoring and Style Diversification for Federated DG-ReID
arXiv CS.LG
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ArXi:2604.26363v1 Announce Type: cross Federated domain generalization for person re-identification (FedDG-ReID) aims to collaboratively train a pedestrian retrieval model across multiple decentralized source domains such that it can generalize to unseen target environments without compromising raw data privacy. However, this task is significantly challenged by the inherent stylistic gaps across decentralized clients. Without global supervision, models easily succumb to shortcut learning where representations overfit to domain specific camera biases rather than universal identity features.