Cross-modal retrieval has developed remarkably recently and received extensive attention
as an essential method for multimodal interaction study. However, most existing models are …

Existing mainstream image-text matching methods usually measure the relevance of image-
text pairs by capturing and aggregating the affinities between textual words and visual …

Semi-supervised learning leverages both labeled and unlabeled images for model training,
addressing the scarcity of labeled data. However, challenges persist, including the …

Text-based person search (TBPS) aims to retrieve images of a specific person from a large
image gallery based on a natural language description. Existing methods rely on massive …

Due to the large-scale and multiscale natures of social media data, sparse representation
(SR) learning methods are widely followed. However, there are three problems associated …

In order to improve the accuracy of cross-modal retrieval tasks and achieve flexible retrieval
between different modalities, we propose a Dual Discriminant Adversarial cross-modal …

The image-text cross-modal retrieval task, which aims to retrieve the relevant image from text
and vice versa, is now attracting widespread attention. To quickly respond to the large-scale …

In recent years, hashing technologies have garnered substantial attention and achieved
notable results due to their low storage costs and excellent retrieval efficiency. However, the …

如何在视角对齐关系错位时有效进行非对齐多视角学习是一类新的挑战性问题. 针对这一问题,
提出面向视角非对齐数据的多视角学习方法. 一方面, 为了捕获多视角异构特征的跨视角相似度 …