Тенденції розвитку генерації текстового опису зображень

Abstract

This paper covers advanced approaches and challenges in generating textual descriptions for images. Modern models, such as BLIP, CLIP, and others that use self-learning, contrastive learning, and noise robustness to improve the accuracy and reliability of descriptions are considered. The main trends and problems of the development of textual descriptions for images are viewed.