A two-stage color transfer framework uses flow-matching optimization with hierarchical color coupling to generate pseudo-supervised data, then trains a feed-forward model for real-time, semantically-aligned stylization.
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ColorFM: An Optimization-to-Learning Framework for Color Transfer via Flow Matching
A two-stage color transfer framework uses flow-matching optimization with hierarchical color coupling to generate pseudo-supervised data, then trains a feed-forward model for real-time, semantically-aligned stylization.