Researchers propose a method for cross-modal alignment of independently trained models without the need for paired data. They introduce a Wasserstein Procrustes method that estimates a single orthogonal map to align representations across different modalities. The method is shown to be effective across various datasets, models, and modalities, and can even outperform pair-based methods in the very few-pair regime.