document: Automatic multimedia cross-modal correlation discovery Given an image ( or video clip , or audio song ) , how do we automatically assign keywords to it ? The general problem is to find correlations across the media in a collection of multimedia objects like video clips , with colors , and\/or motion , and\/or audio , and\/or text scripts . We propose a novel , graph-based approach , `` MMG '' , to discover such cross-modal correlations . Our `` MMG '' method requires no tuning , no clustering , no user-determined constants ; it can be applied to any multimedia collection , as long as we have a similarity function for each medium ; and it scales linearly with the database size . We report auto-captioning experiments on the `` standard '' Corel image database of 680 MB , where it outperforms domain specific , fine-tuned methods by up to 10 percentage points in captioning accuracy ( 50 % relative improvement ) .
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