Image-Text matching (ITM) is a common task for evaluating the quality of Vision and
Language (VL) models. However, existing ITM benchmarks have a significant limitation …

The difficulty of image-text retrieval is further exacerbated by the phenomenon of one-to-
many correspondence, where multiple semantic manifestations of the other modality could …

Image-Text Matching (ITM) task, a fundamental vision-language (VL) task, suffers from the
inherent ambiguity arising from multiplicity and imperfect annotations. Deterministic …

Nowadays, image–text matching (retrieval) has frequently attracted attention due to the
growth of multimodal data. This task returns the relevant images to a textual query or …

Cross-modal metric learning is a prominent research topic that bridges the semantic
heterogeneity between vision and language. Existing methods frequently utilize simple …

With the rapid development of information technology, image and text data have increased
dramatically. Image and text matching techniques enable computers to understand …

Recently, image-text matching has been intensively explored to bridge vision and language.
Previous methods explore an inter-modality relationship between an image-text pair from …

Image-text matching remains a challenging task due to heterogeneous semantic diversity
across modalities and insufficient distance separability within triplets. Different from previous …

Cross-modal representation learning learns a shared embedding between two or more
modalities to improve performance in a given task compared to using only one of the …

Image-text retrieval serves as a bridge connecting vision and language. Mainstream modal
cross matching methods can effectively perform cross-modal interactions with high …