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A recent trend in multimodal retrieval is related to postprocessing test setresults via the dual-softmax loss (DSL). While this approach can bringsignificant improvements, it usually presumes that an entire matrix of testsamples is available as DSL input. This work introduces a new postprocessingapproach based on Sinkhorn transformations that outperforms DSL. Further, wepropose a new postprocessing setting that does not require access to multipletest queries. We show that our approach can significantly improve the resultsof state of the art models such as CLIP4Clip, BLIP, X-CLIP, and DRL, thusachieving a new state-of-the-art on several standard text-video retrievaldatasets both with access to the entire test set and in the single-querysetting.

Sinkhorn Transformations for Single-Query Postprocessing in Text-Video Retrieval