UIT-ViIC: A Dataset for the First Evaluation on Vietnamese Image Captioning
This provides a foundational dataset for Vietnamese image captioning research, addressing a language-specific gap, but it is incremental as it adapts existing methods to a new language.
The paper tackles the lack of a Vietnamese image captioning dataset by creating UIT-ViIC, which includes 19,250 captions for 3,850 images, and evaluates it using deep neural networks to compare with English and other Vietnamese datasets.
Image Captioning, the task of automatic generation of image captions, has attracted attentions from researchers in many fields of computer science, being computer vision, natural language processing and machine learning in recent years. This paper contributes to research on Image Captioning task in terms of extending dataset to a different language - Vietnamese. So far, there is no existed Image Captioning dataset for Vietnamese language, so this is the foremost fundamental step for developing Vietnamese Image Captioning. In this scope, we first build a dataset which contains manually written captions for images from Microsoft COCO dataset relating to sports played with balls, we called this dataset UIT-ViIC. UIT-ViIC consists of 19,250 Vietnamese captions for 3,850 images. Following that, we evaluate our dataset on deep neural network models and do comparisons with English dataset and two Vietnamese datasets built by different methods. UIT-ViIC is published on our lab website for research purposes.