In this paper, we study a challenging but less-touched problem in cross-modal retrieval, ie,
partially mismatched pairs (PMPs). Specifically, in real-world scenarios, a huge number of …

In this paper, we propose a multi-task learning approach for cross-modal image-text
retrieval. First, a correlation network is proposed for relation recognition task, which helps …

Despite the recent developments in the field of cross-modal retrieval, there has been less
research focusing on low-resource languages due to the lack of manually annotated …

Cross-modal retrieval methods are the preferred tool to search databases for the text that
best matches a query image and vice versa However, image-text retrieval models commonly …

The abundance of multimodal data (eg social media posts) has inspired interest in cross-
modal retrieval methods. Popular approaches rely on a variety of metric learning losses …

This article focuses on tackling the task of the cross-modal image–text retrieval which has
been an interdisciplinary topic in both computer vision and natural language processing …

Cross-modality retrieval encompasses retrieval tasks where the fetched items are of a
different type than the search query, eg, retrieving pictures relevant to a given text query. The …

Cross-modal image-text retrieval has been a long-standing challenge in the multimedia
community. Existing methods explore various complicated embedding spaces to assess the …

Cross-modal retrieval, eg, using an image query to search related text and vice-versa, has
become a highlighted research topic, to provide flexible retrieval experience across multi …

Cross-modal retrieval has been a compelling topic in the multimodal community. Recently,
to mitigate the high cost of data collection, the co-occurred pairs (eg, image and text) could …