Recently, exciting progress has been made in the research of supervised image captioning.
However, manually annotated image-annotation pair data is difficult and expensive to …

Although image captioning models have made significant advancements in recent years, the
majority of them heavily depend on high-quality datasets containing paired images and texts …

News Captioning involves generating the descriptions for news images based on the
detailed content of related news articles. Given that these articles often contain extensive …

Recently, zero-shot image captioning has gained increasing attention, where only text data
is available for training. The remarkable progress in text-to-image diffusion model presents …

Introduction: Image caption generation has long been a fundamental challenge in the area
of computer vision (CV) and natural language processing (NLP). In this research, we present …

Non-annotated visual description (NaVD) aims to describe generic visuals without human-
annotated pairwise data. The generic visuals refer to images and videos. Existing works …

Unpaired Image Captioning (UIC) is designed to describe an image without relying on
matched vision-language training data. It is a challenging task since (1) the implicit and …

Plant disease captioning is crucial for agricultural pest and disease prevention. However,
generating accurate captions for plant disease images remains challenging because of the …

Recently, training an image captioner without annotated image-sentence pairs has gained
traction. Previous methods have faced limitations due to either using mismatched corpora for …

Deep learning approaches have been pivotal in identifying multi-plant diseases, yet they
often struggle with unseen data. The challenge of handling unseen data is significant due to …