Diffusion models are increasingly favored over traditional approaches like generative
adversarial networks (GANs) and auto-regressive transformers due to their remarkable …

While transformers have indeed improved image retrieval accuracy in computer vision,
challenges persist, including insufficient and imbalanced feature extraction and the inability …

For current image caption tasks used to encode region features and grid features
Transformer-based encoders have become commonplace, because of their multi-head self …

Fine-grained image captioning with attribute information has garnered significant attention in
the realms of computer vision and natural language processing, demanding precise and …

In recent years, transformer-based photo captioning frameworks plays a crucial role in
improving individuals' overall well-being, self-reliance, and inclusivity by giving them access …

Transformer-based encoders that encode both region and grid features are the preferred
choice for the image captioning task due to their multi-head self-attention mechanism. This …

In light of the remarkable progress made in automated image caption generation, it is still
challenging to create captions that accurately reflect factual information and yet capture the …

Image captioning is a challenging task that involves generating natural language
descriptions of images by integrating visual and textual data. This study presents a novel …

Image Captioning—це динамічна галузь, яка поєднує комп'ютерний зір і обробку
природної мови для автоматичного створення текстових описів зображень. Її головне …

In recent years, there has been growing interest among researchers in the field of image
captioning, which involves generating one or more descriptions for an image that closely …