AI RESEARCH
CPCANet: Deep Unfolding Common Principal Component Analysis for Domain Generalization
arXiv CS.CV
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ArXi:2605.05136v1 Announce Type: new Domain Generalization (DG) aims to learn representations that remain robust under out-of-distribution (OOD) shifts and generalize effectively to unseen target domains. While recent invariant learning strategies and architectural advances have achieved strong performance, explicitly discovering a structured domain-invariant subspace through second-order statistics remains underexplored.