Diffusion-based text-to-video generation has witnessed impressive progress in the past year
yet still falls behind text-to-image generation. One of the key reasons is the limited scale of …

Exploiting fine-grained correspondence and visual-semantic alignments has shown great
potential in image-text matching. Generally, recent approaches first employ a cross-modal …

Image-text matching is a fundamental task to bridge vision and language. The critical
challenge lies in accurately learning the semantic similarity between these two …

Image-text retrieval has developed rapidly in recent years. However, it is still a challenge in
remote sensing due to visual-semantic imbalance, which leads to incorrect matching of …

In this paper, we propose a novel visual Semantic-Spatial Self-Highlighting Network (termed
3SHNet) for high-precision, high-efficiency and high-generalization image–sentence …

Although the attention mechanism in transformers has proven successful in image-text
retrieval tasks, most transformer models suffer from a large number of parameters. Inspired …

Image-text matching, as a fundamental cross-modal task, bridges vision and language. The
key challenge lies in accurately learning the semantic similarity of these two heterogeneous …

Image-text matching plays an important role in solving the problem of cross-modal
information processing. Since there are nonnegligible semantic differences between …

Abstract Recently, Video Question-Answering (VideoQA) has drawn more and more
attention from both industry and research community. Despite all the success achieved by …

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