cross-modal alignment

Cross-modal Alignment is a multimodal learning technique aimed at establishing correspondences between different modalities of data to achieve alignment and integration across these modalities. Its primary goal is to enhance the accuracy and robustness of models when handling multimodal tasks, such as image-text matching and cross-modal retrieval. By optimizing the consistency and complementarity of feature representations across modalities, Cross-modal Alignment demonstrates significant application value in areas like human-computer interaction, multimedia analysis, and intelligent recommendation.