QC-FM constructs flow-matching source samples by mapping projected data ranks to Gaussian quantiles, without solving a batch assignment, and reports FID improvements up to 12.9% over the independent-coupling baseline.
InProceedings of the IEEE/CVF Confer- ence on Computer Vision and Pattern Recognition (CVPR), 37992–38003
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One-Sided Quantile Coupling for Flow Matching
QC-FM constructs flow-matching source samples by mapping projected data ranks to Gaussian quantiles, without solving a batch assignment, and reports FID improvements up to 12.9% over the independent-coupling baseline.