In the past few years, cross-modal image-text retrieval (ITR) has experienced increased
interest in the research community due to its excellent research value and broad real-world …

With the exponential surge in diverse multimodal data, traditional unimodal retrieval
methods struggle to meet the needs of users seeking access to data across various …

Fashion image retrieval based on a query pair of reference image and natural language
feedback is a challenging task that requires models to assess fashion related information …

Visual appearance is considered to be the most important cue to understand images for
cross-modal retrieval, while sometimes the scene text appearing in images can provide …

Most existing cross-modal language-to-video retrieval (VR) research focuses on single-
modal input from video, ie, visual representation, while the text is omnipresent in human …

Abstract Knowledge graphs serve as crucial resources for various applications. However,
most existing knowledge graphs present symbolic knowledge in the form of natural …

Pretraining has proven successful in Document Intelligence tasks where deluge of
documents are used to pretrain the models only later to be finetuned on downstream tasks …

The task of image-text matching aims to map representations from different modalities into a
common joint visual-textual embedding. However, the most widely used datasets for this …

Text-to-image person retrieval aims to retrieve relevant target individuals based on given
textual descriptions. The main challenge faced by this task is how to better combine and …

With the rapid development of the Internet and the expanding scale of social media,
incomplete social event classification has increasingly become a challenging task. The key …